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Jun 15 ,2018. https://doi.org/10.5072/ro-id.BPIH2F2WOA. datasets produced software web services inputs main nested results config used biblio setup workflows components scripts ggg 143 https://api.rohub.org/api/resources/906a758b-2781-462c-8c3b-41cd882f632d/download/ 2018-05-10 08:09:44.546000+00:00 2022-03-24 19:49:43.581239+00:00 .txt Input-Master.txt 2018-05-10 08:09:44.546000+00:00 11 https://api.rohub.org/api/resources/9e39ca91-b2a0-4177-96d4-90d5a32b549a/download/ 2018-05-10 10:50:29.452000+00:00 2022-03-24 19:49:45.325235+00:00 .txt Copyright.txt 2018-05-10 10:50:29.452000+00:00 4 https://api.rohub.org/api/resources/d547a8e8-0d4f-4a73-9a3c-3be2ff00ce67/download/ 2018-05-10 08:19:07.994000+00:00 2022-03-24 19:49:49.392487+00:00 .txt workflow.txt 2018-05-10 08:19:07.994000+00:00 0 https://api.rohub.org/api/resources/f948aa0c-f8c4-45e3-b9a8-456307449a48/download/ 2018-05-10 08:21:25.852000+00:00 2022-03-24 19:49:47.742295+00:00 .txt definition.txt 2018-05-10 08:21:25.852000+00:00 test 25.018764073054793 100.0 geology 26.632741500408624 0.9956269264221191 earth sciences 26.214273292711976 0.9799830913543701 geology 17.014721850579107 0.6360710263252258 earth sciences 18.57463758996624 0.6943862438201904 oceanography 11.563625766334056 0.43228960037231445 master image 50.02501250625313 100.0 image 4.736419587904736 17.7 geosciences 22.1282807437931 0.33686426281929016 Satcen 2018 25.018764073054793 100.0 change Detection over Madrid 0.7003501750875437 1.4 astronautics 15.408499143145692 0.23456737399101257 uniform resource identifier 4.194470924690181 8.8 Madrid 6.208188386406208 23.2 Madrid 11.1534795042898 23.4 geophysics 8.407055595076324 0.12798267602920532 atmospheric sciences 18.57463758996624 0.6943862438201904 spacecraft design, testing and performance 15.408499143145692 0.23456737399101257 Detection over Madrid 31.715857928964482 63.4 image 13.203050524308864 27.7 URI: http://box.everest.psnc.pl:8000/f/aa333acec2/ 4.928696522391794 19.7 expert 2.573879885605338 5.4 test 47.66444232602478 100.0 atmospheric sciences 26.214273292711976 0.9799830913543701 test 26.75943270002676 100.0 data 8.482740165908483 31.7 space sciences (general) 3.3287645856718493 0.05067460238933563 geosciences 8.407055595076324 0.12798267602920532 change Detection 17.55877938969485 35.1 earth resources and remote sensing 50.727399932313034 0.7722356915473938 centric 1.9542421353670159 4.1 http 4.242135367016206 8.9 Madrid S1A_IW_GRDH_1SDV_20170808T061754_20170808T061819_017828_01DE2C_F086.zip 16.135937918116138 60.3 Satcen 26.75943270002676 100.0 Detection 10.917848541610917 40.8 S1A_IW_GRDH_1SDV_20170808T061754_20170808T061819_017828_01DE2C_F086.zip 14.360770577933451 57.4 Change Detection over Madrid 10.28271203402552 41.1 geosciences 50.727399932313034 0.7722356915473938 service-account-enrichment service-account-generation-service Geophysics Elisa Trasatti Document geodetic data at Campi Flegrei (Italy) IREAINGV_ 2018-02-26T15:49:49.800+01:00 http://everest.psnc.pl/users/elisa.trasatti https://w3id.org/ro-id/57294633-c17e-40d2-a2c4-408f81e4c72e Campi Flegrei ascii file GPS data American Standard Code for Information Interchange data file caldera Ascii dataset png image InSAR data GPS Italy image gamma software telecommunications GPS data from INGV file gamma software Italy SAR interferometry service-account-enrichment http://sandbox.rohub.org/rodl/ROs/InSAR_GPS_Campi_Fregrei_2011_2013-release/ http://rohub.org/performedtasks/26048903/ 1648739 https://api.rohub.org/api/ros/57294633-c17e-40d2-a2c4-408f81e4c72e/crate/download/ http://rohub.org/users/portal/26975763/ 2017-12-13 20:45:37.381000+00:00 2025-03-05 00:55:15.411045+00:00 2017-12-13 20:45:37.381000+00:00 This Research Object contains the InSAR data (COSMO-Skymed ascending and descending orbits) and GPS data from INGV related to the Campi Flegrei caldera during 2011-2013. The dataset was processed with GAMMA software and was subsampled with step 100m-150m. Ascii file and png images are stored. application/ld+json https://w3id.org/ro-id/57294633-c17e-40d2-a2c4-408f81e4c72e InSAR and GPS data of the 2011-2013 unrest at Campi Flegrei (Italy) Open Elisa Trasatti Elisa Trasatti. "InSAR and GPS data of the 2011-2013 unrest at Campi Flegrei (Italy)." ROHub. Dec 13 ,2017. https://w3id.org/ro-id/57294633-c17e-40d2-a2c4-408f81e4c72e. Dataset Data Documentation Metadata Biblio Used Raw Data Produced 81 https://api.rohub.org/api/resources/1c9749bd-fcb1-4104-8a8a-541ece5c3e9f/download/ 2017-12-14 14:56:48.154000+00:00 2022-03-24 20:58:05.484914+00:00 PNG SAR_RESULTS_DSC_SAR_RESULTS_OBS_col.pngw 2017-12-14 14:56:48.154000+00:00 http://onlinelibrary.wiley.com/doi/10.1002/2015GL063621/full 2017-12-13 20:45:37.381000+00:00 2022-03-24 20:58:00.348297+00:00 http://onlinelibrary.wiley.com/doi/10.1002/2015GL063621/full 2017-12-13 20:45:37.381000+00:00 661 https://api.rohub.org/api/resources/500f201c-039e-4970-9c7a-66b6ef37aa2e/download/ 2017-12-14 14:49:46.677000+00:00 2022-03-24 20:58:03.676983+00:00 text ASC-DSC-disp.rtf 2017-12-14 14:49:46.677000+00:00 318333 https://api.rohub.org/api/resources/7c707754-def5-452a-b307-c7b43ae56d83/download/ 2017-12-14 14:48:37.059000+00:00 2022-03-24 20:58:01.567160+00:00 ascii obs_sar.dat 2017-12-14 14:48:37.059000+00:00 1966 https://api.rohub.org/api/resources/80af1036-e303-45c5-b173-d659759cc182/download/ 2017-12-14 15:01:16.873000+00:00 2022-03-24 20:58:06.570506+00:00 text Method.rtf 2017-12-14 15:01:16.873000+00:00 1575 https://api.rohub.org/api/resources/8464dc9b-fd91-478c-a86b-393a224fe366/download/ 2017-12-14 14:48:50.965000+00:00 2022-03-24 20:58:02.643427+00:00 ascii obs_gps.dat 2017-12-14 14:48:50.965000+00:00 3382 https://api.rohub.org/api/resources/907e93c1-28bb-4d5e-b87c-6adc4df0754c/download/ 2017-12-14 14:55:38.393000+00:00 2022-03-24 20:57:53.806993+00:00 PNG SAR_RESULTS_ASC_SAR_RESULTS_OBS_col.png 2017-12-14 14:55:38.393000+00:00 6038 https://api.rohub.org/api/resources/ced68f5f-fa02-4e8e-8263-5288b37e1819/download/ 2017-12-14 14:56:33.068000+00:00 2022-03-24 20:57:55.662736+00:00 PNG SAR_RESULTS_DSC_SAR_RESULTS_OBS_col.png 2017-12-14 14:56:33.068000+00:00 81 https://api.rohub.org/api/resources/d1fb025e-acb9-4c7d-bac6-4af94011530c/download/ 2017-12-14 14:56:17.431000+00:00 2022-03-24 20:58:04.577002+00:00 PNG SAR_RESULTS_ASC_SAR_RESULTS_OBS_col.pngw 2017-12-14 14:56:17.431000+00:00 1579356 https://api.rohub.org/api/resources/fe2d8782-3dd0-41bc-85c8-dcd6534ac3e9/download/ 2017-12-14 15:03:17.780000+00:00 2022-03-24 20:58:07.678371+00:00 image/png ASC_DSC_GPS.png 2017-12-14 15:03:17.780000+00:00 service-account-generation-service Geophysics Elisa Trasatti Docoument geodetic data at Campi Flegrei IREAINGV_ 2018-02-26T15:45:15.335+01:00 http://everest.psnc.pl/users/elisa.trasatti https://w3id.org/ro-id/02204bef-b3c3-448e-9d99-9685006f2ded memory descending orbit Campi Flegrei contain the InSAR data ascii file Research Object American Standard Code for Information Interchange data file Ascii dataset png image InSAR data Italy image InSAR data file ferment unrest Italy SAR interferometry service-account-enrichment http://sandbox.rohub.org/rodl/ROs/InSAR_Campi_Flegrei_2004_2006-release/ http://rohub.org/performedtasks/36071950/ 1037570 https://api.rohub.org/api/ros/02204bef-b3c3-448e-9d99-9685006f2ded/crate/download/ http://rohub.org/users/portal/26975763/ 2017-12-08 11:22:53.432000+00:00 2025-03-05 00:55:15.805905+00:00 2017-12-08 11:22:53.432000+00:00 This Research Object contains the InSAR data (ENVISAT ascending and descending orbits) at Campi Flegrei during 2004-2006. The dataset was processed with SBAS and is subsampled with step 100m-150m. Ascii file and png images are stored. application/ld+json https://w3id.org/ro-id/02204bef-b3c3-448e-9d99-9685006f2ded InSAR data of 2004-2006 unrest at Campi Flegrei (Italy) Open Elisa Trasatti Elisa Trasatti. "InSAR data of 2004-2006 unrest at Campi Flegrei (Italy)." ROHub. Dec 08 ,2017. https://w3id.org/ro-id/02204bef-b3c3-448e-9d99-9685006f2ded. Documentation Documentation Biblio Used Raw_Data Dataset documentation Dataset Produced ASCII 645 https://api.rohub.org/api/resources/4746a8d8-ff1e-4c14-b46d-7d2bf6057be5/download/ 2017-12-14 14:53:43.276000+00:00 2022-03-24 21:01:13.446478+00:00 text ASC-DSC-disp.rtf 2017-12-14 14:53:43.276000+00:00 81 https://api.rohub.org/api/resources/9244fff7-d17a-429a-b94d-4cb054ccf6d1/download/ 2017-12-08 12:06:26.426000+00:00 2022-03-24 21:01:11.321713+00:00 PNG SAR_RESULTS_ASC_SAR_RESULTS_OBS_col.pngw 2017-12-08 12:06:26.426000+00:00 4209 https://api.rohub.org/api/resources/c27e32c2-4673-489f-86d9-3ce85fc8a423/download/ 2017-12-08 12:06:12.180000+00:00 2022-03-24 21:01:01.262842+00:00 PNG SAR_RESULTS_ASC_SAR_RESULTS_OBS_col.png 2017-12-08 12:06:12.180000+00:00 1539 https://api.rohub.org/api/resources/d0d538e7-fb88-4ad6-8978-89ea608d0e53/download/ 2017-12-08 11:44:13.062000+00:00 2022-03-24 21:01:09.493808+00:00 ASCII Method.rtf 2017-12-08 11:44:13.062000+00:00 http://onlinelibrary.wiley.com/doi/10.1029/1998GL900033/abstract 2017-12-08 11:22:53.432000+00:00 2022-03-24 21:01:07.449755+00:00 http://onlinelibrary.wiley.com/doi/10.1029/1998GL900033/abstract 2017-12-08 11:22:53.432000+00:00 4080 https://api.rohub.org/api/resources/d8f704f1-fa16-4d64-9945-8293c984735c/download/ 2017-12-08 12:06:44.114000+00:00 2022-03-24 21:01:04.042057+00:00 PNG SAR_RESULTS_DSC_SAR_RESULTS_OBS_col.png 2017-12-08 12:06:44.114000+00:00 1013108 https://api.rohub.org/api/resources/df95e927-b75c-4ba2-8f17-e6870dee97d8/download/ 2017-12-08 11:38:47.295000+00:00 2022-03-24 21:01:08.632536+00:00 image/png ASC_DSC.png 2017-12-08 11:38:47.295000+00:00 81 https://api.rohub.org/api/resources/e4b9a950-0112-4f30-9ede-84c489589309/download/ 2017-12-08 12:07:00.217000+00:00 2022-03-24 21:01:12.343097+00:00 PNG SAR_RESULTS_DSC_SAR_RESULTS_OBS_col.pngw 2017-12-08 12:07:00.217000+00:00 http://onlinelibrary.wiley.com/doi/10.1029/2007GL033091/abstract 2017-12-08 11:22:53.432000+00:00 2022-03-24 21:01:07.519588+00:00 http://onlinelibrary.wiley.com/doi/10.1029/2007GL033091/abstract 2017-12-08 11:22:53.432000+00:00 service-account-generation-service WebProcessingServiceExecution 2 http://box.everest.psnc.pl:8000/f/0c4347ad9d/ 2022-03-25 15:09:39.543771+00:00 2022-03-25 15:09:52.874890+00:00 .png cd.png 2022-03-25 15:09:39.543771+00:00 WebProcessingServiceExecution 2018-05-08T16:22:04.503000+00:00 WebProcessingServiceExecution 2 http://box.everest.psnc.pl:8000/f/6157842c73/ 2022-03-25 15:09:39.543368+00:00 2022-03-25 15:09:53.454536+00:00 .tgz cd.tgz 2022-03-25 15:09:39.543368+00:00 WebProcessingServiceExecution 2018-05-08T16:22:04.503000+00:00 985000 http://box.everest.psnc.pl:8000/f/6a67815420/ 2022-03-25 15:09:39.544187+00:00 2022-03-25 15:09:51.086061+00:00 .zip S1A_IW_GRDH_1SDV_20170820T061754_20170820T061819_018003_01E376_9EC3.zip 2022-03-25 15:09:39.544187+00:00 WebProcessingServiceExecution 2 http://box.everest.psnc.pl:8000/f/a25b04c564/ 2022-03-25 15:09:39.542816+00:00 2022-03-25 15:09:57.372474+00:00 .pngw cd.pngw 2022-03-25 15:09:39.542816+00:00 WebProcessingServiceExecution 2018-05-08T16:22:04.503000+00:00 985000 http://box.everest.psnc.pl:8000/f/aa333acec2/ 2022-03-25 15:09:39.544631+00:00 2022-03-25 15:09:55.954370+00:00 .zip S1A_IW_GRDH_1SDV_20170808T061754_20170808T061819_017828_01DE2C_F086.zip 2022-03-25 15:09:39.544631+00:00 Cartography anca popescu EU SatCen EU SatCen POLYGON((-3.6384382604 40.5622470252, -3.3858490478 40.5622470252, -3.3858490478 40.3847421816, -3.6384382604 40.3847421816, -3.6384382604 40.5622470252)) WebProcessingService AreaofInterest MasterSentinel-1product Polarization SlaveSentinel-1product SatCen Change Detection Workflow execution Result Files Distribution Package com.terradue.wps_oozie.process.OozieAbstractAlgorithm SatCen Change Detection Workflow POLYGON( ( -3.611394871468983 40.53713623661004, -3.5125914250302666 40.53713623661004, -3.4137879785915506 40.53713623661004, -3.4137879785915506 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"Change Detection Data Centric." ROHub. Jun 15 ,2018. https://w3id.org/ro-id/f8fafb66-4349-4d35-a695-0db97605e324. setup components datasets produced web services inputs results biblio main scripts workflows nested used software config 0 https://api.rohub.org/api/resources/0dfaa382-a57d-4f1b-b160-2aed85cb2b36/download/ 2018-05-10 08:21:25.852000+00:00 2022-03-25 15:09:55.345849+00:00 .txt definition.txt 2018-05-10 08:21:25.852000+00:00 4 https://api.rohub.org/api/resources/549abf24-05cc-4ad6-a9f4-1d276eaf0dde/download/ 2018-05-10 08:19:07.994000+00:00 2022-03-25 15:09:57.149262+00:00 .txt workflow.txt 2018-05-10 08:19:07.994000+00:00 ggg 143 https://api.rohub.org/api/resources/5c385343-84f6-4709-8095-e4a2a699cc5f/download/ 2018-05-10 08:09:44.546000+00:00 2022-03-25 15:09:50.104320+00:00 .txt Input-Master.txt 2018-05-10 08:09:44.546000+00:00 11 https://api.rohub.org/api/resources/7d4f074b-cc46-4cad-9b31-79d72d8a1fef/download/ 2018-05-10 10:50:29.452000+00:00 2022-03-25 15:09:52.004094+00:00 .txt Copyright.txt 2018-05-10 10:50:29.452000+00:00 service-account-enrichment service-account-generation-service Elisa Trasatti LOADING M. Polcari mathematics deformation velocity vector Riccardo Lanari phase pattern Institute of Electrical and Electronics Engineers physics decorrelation phenomena velocity component deformations phase signal pixel signal subsets results phase artifact Baseline norm episode phase Italy Section technique 1992-2010 displacement 9.29705215419501 8.2 Colli Albani 1.0070493454179255 1.0 volcanic area 20.365168539325843 14.5 cumulate displacements in ascending 0.6042296072507553 0.6 cumulate displacement 9.164149043303123 9.1 volcanic area 16.666666666666668 14.7 ERS 11.791383219954648 10.4 displacement 11.516853932584267 8.2 dataset 17.346938775510203 15.3 satellite 15.079365079365079 13.3 Italy https://www.wikidata.org/wiki/Q38 satellite 18.820224719101123 13.4 engineering 100.0 0.6484560966491699 earth sciences 100.0 0.6677627563476562 contain cumulate displacement 0.5035246727089627 0.5 geology 100.0 0.6677627563476562 Satellite technology Economy, business and finance/Economic sector/Computing and information technology/Satellite technology This dataset contains cumulate displacements in Ascending and Descending Line of Sights from ERS/Envisat satellites during 1992-2010 at Colli Albani (Italy), a volcanic area close to Rome. 92.29229229229229 92.2 envisat satellite 88.72104733131924 88.1 Italy 17.977528089887638 12.8 Rome 10.674157303370785 7.6 Italy 14.399092970521542 12.7 during 1992-2010 Rome https://www.wikidata.org/wiki/Q220 ENVISAT 15.419501133786847 13.6 Colli Albani (Italy) InSAR Data 1992-2010. 7.707707707707708 7.7 dataset 20.646067415730336 14.7 Hardware Economy, business and finance/Economic sector/Computing and information technology/Hardware communications and radar 100.0 0.6484560966491699 astronautics 100.0 2.6 service-account-enrichment 10.5072/ro-id.X2XTIJE5PA 2017-10-23T09:23:26.566+02:00 http://everest.psnc.pl/users/elisa.trasatti http://sandbox.rohub.org/rodl/ROs/Colli_Albani_InSAR_1992_2010/ http://rohub.org/performedtasks/75935672/ 339289 https://api.rohub.org/api/ros/f29e9cb2-2c95-4db8-af48-13d6bb5fe2b5/crate/download/ INGV 2017-10-23 07:23:26.566000+00:00 2025-03-05 00:46:59.559997+00:00 2017-10-23 07:23:26.566000+00:00 This dataset contains cumulate displacements in Ascending and Descending Line of Sights from ERS/Envisat satellites during 1992-2010 at Colli Albani (Italy), a volcanic area close to Rome. application/ld+json https://w3id.org/ro-id/f29e9cb2-2c95-4db8-af48-13d6bb5fe2b5 Colli Albani (Italy) InSAR Data 1992-2010 open access E. Trasatti https://w3id.org/ro-id/eefec9f5-bb20-48ee-974a-e641c683983f https://w3id.org/ro-id/59ad65f2-068a-4130-9367-1041453c0b2a https://w3id.org/ro-id/bc3225f0-68f1-482d-95b3-aa7a905c421c https://w3id.org/ro-id/1de087e1-140b-4478-b01f-206f0d62ec4f https://w3id.org/ro-id/38f0fcc7-19aa-438b-8af3-52bf1f03d1fe https://w3id.org/ro-id/5b68b054-40da-4793-9c97-e55ff246384d https://w3id.org/ro-id/ad99b684-8ee6-4a3a-89b4-d801ee3eb53f https://w3id.org/ro-id/b3af6844-0fa4-4604-90e3-5bad78c891d0 https://w3id.org/ro-id/d4ba00a6-c3b2-42ff-a9a4-6a15ba880641 https://w3id.org/ro-id/68ffdeff-678a-4b96-b838-28b07d59338d https://w3id.org/ro-id/8f77e33d-a7ef-4132-a793-bf81286330e3 https://w3id.org/ro-id/95248884-51fe-4f0e-baa9-c8e9e4e13dab https://w3id.org/ro-id/e8504614-fdd8-43f9-89a4-5bf7dd7f17bd https://w3id.org/ro-id/0b8583f3-050c-43e5-b5ac-48fac44b8e30 https://w3id.org/ro-id/253bc09f-d50e-4f16-9027-6082c1f238ae https://w3id.org/ro-id/344db0bb-2d23-493c-9ee5-7a4139139cf8 https://w3id.org/ro-id/44999bcd-c856-4488-8321-8d3eaf7310cc https://w3id.org/ro-id/4cbb2335-d38f-4bf5-9b73-21689c7bdce6 https://w3id.org/ro-id/b9374aba-7097-4147-bfa4-789e7f52efe8 https://w3id.org/ro-id/cd159223-b3a1-4472-a1f7-307b07146add https://w3id.org/ro-id/649052c9-0027-4318-854b-938b6493476f https://w3id.org/ro-id/eeb0086c-f767-4732-9b80-4b9a94c594ab https://w3id.org/ro-id/1b2f0a0c-eb39-46d4-81bb-e513430c2c8b https://w3id.org/ro-id/208756b4-b33a-46a3-8154-c2644291ea11 https://w3id.org/ro-id/20deb0b8-8195-42ad-80ed-d795d87be8d8 https://w3id.org/ro-id/730b8665-feba-474d-8ff0-24512d846197 https://w3id.org/ro-id/aa145f30-3902-48ba-b982-d2dabd629936 https://w3id.org/ro-id/a3cadfa8-a86b-49ce-9c28-b9b0f0c1b926 https://w3id.org/ro-id/d3f35e50-15da-43ca-b8a0-45e7af617403 https://w3id.org/ro-id/0ae1a3a8-fc54-46a0-b575-da7d053620d6 https://w3id.org/ro-id/b98d7a85-2361-4da4-9f1e-9fa25e102c7d Elisa Trasatti. "Colli Albani (Italy) InSAR Data 1992-2010." ROHub. Oct 23 ,2017. https://doi.org/10.5072/ro-id.X2XTIJE5PA. Used Metadata Produced Dataset Biblio Documentation Raw Data Data 78336 https://api.rohub.org/api/resources/07ebd403-715b-45c8-ba07-66a1fd09492e/download/ 2017-10-22 16:21:50.378000+00:00 2022-03-25 15:14:02.732573+00:00 Excel file containing the list of the ERS ENVISAT ascending and descending data used for the time-series analysis. excel file List of ERS ENVISAT data 2017-10-22 16:21:50.378000+00:00 229897 https://api.rohub.org/api/resources/2be5dbbf-ba61-4cfb-81db-089e3ba50caa/download/ 2017-10-22 17:09:12.906000+00:00 2022-03-25 15:13:59.686497+00:00 image/jpeg asc-dsc.jpg 2017-10-22 17:09:12.906000+00:00 https://pdfs.semanticscholar.org/b89d/ad1cc6b319f9d98887902c4a2d58426b3914.pdf 2022-03-25 15:13:40.224034+00:00 2022-03-25 15:13:57.775477+00:00 application/pdf Radar interferogram filtering for geophysical applications 2022-03-25 15:13:40.224034+00:00 420 KB 421932 https://api.rohub.org/api/resources/4199574c-1ddd-44df-ba60-bcb5d2361ca0/download/ 2017-10-22 16:43:52.767000+00:00 2022-03-25 15:13:55.684347+00:00 Ascending component. ASCII ASC-300-disp-R16.dat 2017-10-22 16:43:52.767000+00:00 360 KB 364812 https://api.rohub.org/api/resources/5577efde-dfa4-4a9e-a405-0bd00469a0b5/download/ 2017-10-22 16:46:14.095000+00:00 2022-03-25 15:14:01.870106+00:00 Descending component. ASCII DSC-300-disp-R16.dat 2017-10-22 16:46:14.095000+00:00 2684 https://api.rohub.org/api/resources/64de4fc2-37df-4491-bf30-87898bdaf714/download/ 2017-10-22 16:40:03.563000+00:00 2022-03-25 15:13:53.428529+00:00 text method.rtf 2017-10-22 16:40:03.563000+00:00 http://onlinelibrary.wiley.com/doi/10.1029/1998GL900033/abstract 2022-03-25 15:13:40.224374+00:00 2022-03-25 15:14:00.869323+00:00 SBAS Algorithm 2022-03-25 15:13:40.224374+00:00 701 https://api.rohub.org/api/resources/800d2bfb-8546-4ed0-889d-e69708b50064/download/ 2017-10-22 16:42:43.069000+00:00 2022-03-25 15:13:52.423243+00:00 text Metadata associated to the ASC and DSC data files 2017-10-22 16:42:43.069000+00:00 http://ieeexplore.ieee.org/document/1295516/?reload=true 2022-03-25 15:13:40.223593+00:00 2022-03-25 15:14:02.815395+00:00 Interferometric point target analysis for deformation mapping 2022-03-25 15:13:40.223593+00:00 service-account-generation-service Elisa Trasatti M. Polcari mathematics deformation velocity vector Riccardo Lanari phase pattern Institute of Electrical and Electronics Engineers physics decorrelation phenomena velocity component deformations phase signal pixel signal subsets results phase artifact Baseline norm episode phase Italy Section technique service-account-enrichment 336324 https://api.rohub.org/api/ros/c313affd-5afd-4981-9a70-9d76470ab3ca/crate/download/ INGV 2017-10-18 13:18:18.157000+00:00 2025-03-05 00:46:59.798483+00:00 2017-10-18 13:18:18.157000+00:00 This dataset contains cumulate displacements in Ascending and Descending Line of Sights from ERS/Envisat satellites during 1992-2010 at Colli Albani (Italy), a volcanic area close to Rome. application/ld+json https://w3id.org/ro-id/c313affd-5afd-4981-9a70-9d76470ab3ca Colli Albani (Italy) InSAR Data 1992-2010 Italy Rome dataset displacement satellite volcanic area earth sciences Hardware Satellite technology ENVISAT ERS Italy dataset displacement satellite volcanic area engineering Colli Albani contain cumulate displacement cumulate displacement cumulate displacements in ascending envisat satellite Colli Albani (Italy) InSAR Data 1992-2010. This dataset contains cumulate displacements in Ascending and Descending Line of Sights from ERS/Envisat satellites during 1992-2010 at Colli Albani (Italy) a volcanic area close to Rome. 1992-2010 during 1992-2010 E. Trasatti astronautics Italy Rome Elisa Trasatti. "Colli Albani (Italy) InSAR Data 1992-2010." ROHub. Oct 18 ,2017. https://w3id.org/ro-id/c313affd-5afd-4981-9a70-9d76470ab3ca. Metadata Documentation Used Dataset Produced Data Raw Data Biblio http://onlinelibrary.wiley.com/doi/10.1029/1998GL900033/abstract 2017-10-18 13:18:18.157000+00:00 2022-03-25 15:14:38.810276+00:00 SBAS Algorithm 2017-10-18 13:18:18.157000+00:00 78336 https://api.rohub.org/api/resources/3a2fa6e9-91b5-4212-b4e7-2fbe037ed9b1/download/ 2017-10-22 16:21:50.378000+00:00 2022-03-25 15:14:38.514111+00:00 Excel file containing the list of the ERS ENVISAT ascending and descending data used for the time-series analysis. excel file List of ERS ENVISAT data 2017-10-22 16:21:50.378000+00:00 701 https://api.rohub.org/api/resources/640f5e73-82d8-4138-b34e-a8cebe8e93cc/download/ 2017-10-22 16:42:43.069000+00:00 2022-03-25 15:14:41.487649+00:00 text Metadata associated to the ASC and DSC data files 2017-10-22 16:42:43.069000+00:00 2684 https://api.rohub.org/api/resources/6f0a6796-efd2-414d-8b4d-add3efa5038e/download/ 2017-10-22 16:40:03.563000+00:00 2022-03-25 15:14:39.809544+00:00 text method.rtf 2017-10-22 16:40:03.563000+00:00 https://pdfs.semanticscholar.org/b89d/ad1cc6b319f9d98887902c4a2d58426b3914.pdf 2017-10-18 13:18:18.157000+00:00 2022-03-25 15:14:38.874393+00:00 application/pdf Radar interferogram filtering for geophysical applications 2017-10-18 13:18:18.157000+00:00 360 KB 364812 https://api.rohub.org/api/resources/82e6a484-0c7d-4a91-ad57-a1c829e21125/download/ 2017-10-22 16:46:14.095000+00:00 2022-03-25 15:14:46.213573+00:00 Descending component. ASCII DSC-300-disp-R16.dat 2017-10-22 16:46:14.095000+00:00 420 KB 421932 https://api.rohub.org/api/resources/8a914aa7-906d-4b94-9cab-c088fd7a50ee/download/ 2017-10-22 16:43:52.767000+00:00 2022-03-25 15:14:45.143842+00:00 Ascending component. ASCII ASC-300-disp-R16.dat 2017-10-22 16:43:52.767000+00:00 229897 https://api.rohub.org/api/resources/8b3532ff-6894-44fc-ba49-510c37f3ac71/download/ 2017-10-22 17:09:12.906000+00:00 2022-03-25 15:14:44.223626+00:00 image/jpeg asc-dsc.jpg 2017-10-22 17:09:12.906000+00:00 http://ieeexplore.ieee.org/document/1295516/?reload=true 2017-10-18 13:18:18.157000+00:00 2022-03-25 15:14:38.949804+00:00 Interferometric point target analysis for deformation mapping 2017-10-18 13:18:18.157000+00:00 service-account-generation-service Applied sciences Earth sciences service-account-enrichment 2022-05-12 10:06:01.082494+00:00 https://orcid.org/0000-0002-2983-045X https://w3id.org/ro-id/03c34c87-6a8d-4ef1-a22e-67e96d52b607 True 2032004 https://api.rohub.org/api/ros/261f85b0-1ba1-4d27-8a42-df2816937f1e/crate/download/ 2022-05-12 09:54:45.242361+00:00 2024-03-05 12:24:28.622853+00:00 2022-05-12 09:54:45.242361+00:00 This Research Object contains the raster file of the mean ground velocity at the Changbaishan Volcano (China/North Korea) from ALOS-2 satellite data during 2018-2020. Find more on processing and results in the related paper: 'Upward Magma Migration within the Multi-level Plumbing System of the Changbaishan Volcano (China/North Korea) Revealed by the Modeling of 2018-2020 SAR Data' by E. Trasatti, C. Tolomei, L. Wei, G. Ventura. DOI: 10.3389/feart.2021.741287 . Raw data property of JAXA (Japan). application/ld+json https://w3id.org/ro-id/261f85b0-1ba1-4d27-8a42-df2816937f1e ALOS test DEMO - archive test DEMO MANUAL China North Korea demonstration file plumbing processing raster soil test velocity earth sciences Executive (government) Government department Newspaper Satellite technology Changbaishan Volcano China North Korea Research Object raster satellite data velocity aeronautics ground velocity property of JAXA raster file raw data property test demo Find more on processing and results in the related paper: 'Upward Magma Migration within the Multi-level Plumbing System of the Changbaishan Volcano (China/North Korea) Revealed by the Modeling of 2018-2020 SAR Data' by E. Trasatti, C. Tolomei, L. Wei, G. Ventura. This Research Object contains the raster file of the mean ground velocity at the Changbaishan Volcano (China/North Korea) from ALOS-2 satellite data during 2018-2020. test DEMO. during 2018-2020 aerospace engineering school systems Interior China Japan North Korea Trasatti, Elisa. "test DEMO." ROHub. May 12 ,2022. https://doi.org/10.24424/0x0k-6772. data biblio raw data metadata 10222 https://api.rohub.org/api/resources/06712ff7-1be4-4043-b549-3d2fac395d70/download/ 2022-05-12 10:01:50.355873+00:00 2022-05-12 10:05:59.703678+00:00 application/vnd.openxmlformats-officedocument.spreadsheetml.sheet list of images 2022-05-12 10:01:50.355873+00:00 460884 https://api.rohub.org/api/resources/35e407ff-fdeb-4140-babf-345502633787/download/ 2022-05-12 10:02:26.720307+00:00 2022-05-12 10:06:00.868037+00:00 image/png image 2022-05-12 10:02:26.720307+00:00 499011 https://api.rohub.org/api/resources/731dc8af-d55e-440f-b0fc-8c278bc044cb/download/ 2022-05-12 09:58:37.948679+00:00 2022-05-12 10:05:56.827888+00:00 text/csv data 2022-05-12 09:58:37.948679+00:00 https://www.frontiersin.org/articles/10.3389/feart.2021.741287/full 2022-05-12 09:57:38.006648+00:00 2022-05-12 10:05:59.806322+00:00 paper 2022-05-12 09:57:38.006648+00:00 1548320 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https://w3id.org/ro-id/3a5459f8-8145-4062-b51b-86e7edfb8208/annotations/3b2a30cc-ae88-4045-8d2a-91996907ff5c/628e3d90a8a689c5035c5329/coverage https://w3id.org/ro-id/3a5459f8-8145-4062-b51b-86e7edfb8208/annotations/3b2a30cc-ae88-4045-8d2a-91996907ff5c/628e3d90a8a689c5035c5329/temporal TROPOMI S5P L2 55406151 https://api.rohub.org/api/ros/3a5459f8-8145-4062-b51b-86e7edfb8208/crate/download/ 2022-06-28 18:46:58.536426+00:00 2025-10-18 11:32:10.096137+00:00 2022-06-28 18:46:58.536426+00:00 Sentinel-5P: SO2 total column (OFFL) - time range: 2022-06-26T19:57:45Z/2018-11-28T12:46:38Z - min/max Value: -10/60 - DataType: Float32 - Resolution: 0 - application/ld+json https://w3id.org/ro-id/3a5459f8-8145-4062-b51b-86e7edfb8208 How to create a Research Object using adamapi and rohub api - 28.06.22a MANUAL Palma, Raul. "How to create a Research Object using adamapi and rohub api - 28.06.22a." ROHub. Jun 28 ,2022. https://w3id.org/ro-id/3a5459f8-8145-4062-b51b-86e7edfb8208. tools data raw data metadata 98599 https://api.rohub.org/api/resources/14349e56-1829-41de-b721-f66467217b00/download/ 2022-07-11 08:35:48.879483+00:00 2022-07-11 08:35:54.725674+00:00 desc application/pdf res-new2 2022-07-11 08:35:48.879483+00:00 3995950 https://api.rohub.org/api/resources/23d1da17-c362-4cc6-984b-97e7564b5902/download/ 2022-07-06 14:41:34.377702+00:00 2022-07-06 14:41:38.979078+00:00 desc8 application/pdf res8 2022-07-06 14:41:34.377702+00:00 884558 https://api.rohub.org/api/resources/4fda69d6-1b50-4c96-a1e4-7b6bf06ab12e/download/ 2022-07-11 08:34:14.057431+00:00 2022-07-11 08:34:21.923033+00:00 description1 image/png res-new1 2022-07-11 08:34:14.057431+00:00 2949626 https://api.rohub.org/api/resources/50fa27ec-f07f-4eb5-86d7-225bff89ae86/download/ 2022-07-06 14:34:34.528035+00:00 2022-07-06 14:34:39.254099+00:00 desc3 application/pdf res3 2022-07-06 14:34:34.528035+00:00 1490272 https://api.rohub.org/api/resources/52aa7ec0-cb2d-4e7a-a178-ae42b9a26c9a/download/ 2022-07-06 14:29:31.444767+00:00 2022-07-06 14:29:36.329683+00:00 desc application/pdf resx-title 2022-07-06 14:29:31.444767+00:00 439045 https://api.rohub.org/api/resources/87653312-15fe-4cb8-8e50-e08e357ddc11/download/ 2022-07-06 14:39:59.233484+00:00 2022-07-06 14:40:04.479965+00:00 desc6 application/pdf res6 2022-07-06 14:39:59.233484+00:00 74929 https://api.rohub.org/api/resources/92cce42c-4aea-40fa-9487-e725fed07d27/download/ 2022-07-06 14:39:02.119007+00:00 2022-07-06 14:39:06.449582+00:00 desc5 application/json res5 2022-07-06 14:39:02.119007+00:00 133508 https://api.rohub.org/api/resources/9c9b17a3-2f4f-42a7-aafc-9e27ad9cd362/download/ 2022-07-06 14:40:59.356130+00:00 2022-07-06 14:41:05.005548+00:00 desc7 application/pdf res7 2022-07-06 14:40:59.356130+00:00 2286908 https://api.rohub.org/api/resources/9f67e243-3af0-4233-98a1-474c59c8799e/download/ 2022-07-06 14:32:11.189177+00:00 2022-07-06 14:32:16.726685+00:00 desc2 application/pdf res2 2022-07-06 14:32:11.189177+00:00 825126 https://api.rohub.org/api/resources/bbbdd03e-f69a-4aa5-9d39-84ad633ae821/download/ 2022-07-06 14:37:00.365389+00:00 2022-07-06 14:37:05.897069+00:00 desc3 application/pdf res4 2022-07-06 14:37:00.365389+00:00 43791839 https://api.rohub.org/api/resources/e9c09afd-6f02-4de4-9165-9c6ae5b2c2a3/download/ 2022-07-11 08:38:16.698689+00:00 2022-07-11 08:38:24.464397+00:00 desc application/pdf res-new3 2022-07-11 08:38:16.698689+00:00 ci 2.288135593220339 5.4 Madrid iridium 3.4422198805760456 9.8 A scien fic or computa onal workflow is the descrip on of the sequence of processing steps they use for a par cular data processing task their data analysis pipeline. 5.1063829787234045 10.8 maximum 4.214963119072708 12.0 scrip 2.1426062521952933 6.1 data 7.11864406779661 16.8 earth sciences 24.605547838852317 0.7781310677528381 linguistics 18.316831683168317 14.799999999999999 workflow 5.690200210748156 16.2 environmental sciences 22.02377407201785 0.6964845061302185 scop 2.4152542372881354 5.7 column 5.169491525423729 12.2 user datum 2.63724434876211 4.9 researcher 3.0508474576271185 7.2 Science and technology Science and technology computer 3.020723568668774 8.6 Pompy Logatherm WLW 6.864406779661017 16.2 Rock and roll music Arts, culture and entertainment/Arts and entertainment/Music/Musical style/Rock and roll music information 2.247980330172111 6.4 research 7.1610169491525415 16.9 aim 3.301721109940288 9.4 datum 3.6440677966101696 8.6 system sterowania Logamatic EMS Plus 1.7761033369214208 3.3 European Commission Library and museum Arts, culture and entertainment/Culture/Library and museum European Community meteorology and climatology 43.255104527007774 0.5567314624786377 mathematical and computer sciences 14.52922542616331 0.1870039850473404 dataset 3.0084745762711864 7.1 object 4.279661016949152 10.1 geosciences 43.255104527007774 0.5567314624786377 a. Sentinel-5P 7.3735199138858984 13.7 Poetry Arts, culture and entertainment/Arts and entertainment/Literature/Poetry sentinel-5 precursor 4.576271186440678 10.8 value 7.584745762711863 17.9 data intensive 2.4219590958019372 4.5 max 5.338983050847458 12.6 computer programming and software 14.52922542616331 0.1870039850473404 Ir 3.728813559322034 8.8 Hardware Economy, business and finance/Economic sector/Computing and information technology/Hardware Wsp czynnik scop si gaj cy warto ci 1.93756727664155 3.6 job market 2.9702970297029703 2.4 research object 24.70398277717976 45.9 workflow part 3.9289558665231428 7.3 computer science 33.29207920792079 26.900000000000002 max value 18.89128094725511 35.1 Science and technology Science and technology minim 2.7046013347383213 7.7 research datum 1.8837459634015068 3.5 dataset 6.252195293291184 17.8 geology 53.37067808912983 1.6878056526184082 dom 3.0084745762711864 7.1 Arkansas 5.169491525423729 12.2 value 6.392694063926941 18.2 research technique 3.4445640473627552 6.4 Genetics Science and technology/Natural science/Biology/Genetics column 4.495960660344222 12.8 document object model 2.669476642079382 7.6 Wf Ever 2.288135593220339 5.4 data management plan information reliance data management plan 2.099031216361679 3.9 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences Such data data include various large Earth Observation datasets and products, in particular from Copernicus programme, as well as other data used for the analysis/simulations, along with the resulting datasets produced by those processes. 2.647754137115839 5.6 metadata 3.090972953986653 8.8 general 42.21567004682892 0.5433530211448669 Comment: There will be two types of data such as research data and user data. 1.5130023640661938 3.2 Jun-28-1922 Language Arts, culture and entertainment/Culture/Language Klasyfikacja efektywno ci energetycznej Logatherm WLW i AR E / WLW i IR E w zestawie z regulatorem Logamatic HMC . 6.997635933806147 14.8 data utility 1.7761033369214208 3.3 general (general) 42.21567004682892 0.5433530211448669 total column 2.7448869752421956 5.1 Interior oceanography 24.605547838852317 0.7781310677528381 OGC EO dataset metadata GeoJSON 2.47578040904198 4.6 earth sciences 53.37067808912983 1.6878056526184082 system 3.4070951879171054 9.7 software 18.81188118811881 15.2 datum 5.690200210748156 16.2 Ir nadaje si 1.7761033369214208 3.3 research 6.498068141903759 18.5 data 9.167544783983141 26.099999999999998 AR Logatherm WLW 3.9289558665231428 7.3 Workflows and Digital Libraries Making a workflow part of the research record is a way of capturing the methods used in a piece of research it makes it easier to interpret the results, and helps repeat and reproduce it. 5.4373522458628845 11.5 SO2 5.805084745762712 13.7 workflow 5.889830508474576 13.9 researcher 2.9504741833508956 8.4 Pompy Logatherm WLW i AR / WLW i IR wykorzystuj powietrze do zapewnienia d ugotrwa ego komfortu w zakresie ogrzewania i ciep ej wody u ytkowej. 7.1867612293144205 15.2 scien fic workflow 3.7674919268030136 7.0 Arkansas computa onal workflow 3.1216361679224973 5.8 Arkansas 4.8823322795925534 13.9 database 26.60891089108911 21.5 Workflows the New Rock and Roll Research in many disciplines is increasingly data intensive, and researchers are using computa onal techniques to manipulate and analyse the data. 11.725768321513002 24.8 How to create a Research Object using adamapi and rohub api - 28.06.22a. Sentinel-5P: SO2 total column (OFFL) - time range: 2022-06-26T19:57:45Z/2018-11-28T12:46:38Z - min/max Value: -10/60 - DataType: Float32 - Resolution: 0 - 47.28132387706856 100.0 sampleor specimen data 1.8299246501614639 3.4 environmental science and management 22.02377407201785 0.6964845061302185 Wherewas user data is concerned with data collected by the RELIANCE services such as ROhub services which collects user data. 1.8439716312056738 3.9 Jeden system do wszystkich zastosowa Niezale nie od tego czy budujesz nowy dom, modernizujesz stary, czy tylko wymieniasz tradycyjn instalacj grzewcz nasza nowa wielofunkcyjna pompa ciep a Logatherm WLW i AR / WLW i IR nadaje si do dom w jednorodzinnych i niewielkich budynk w wielorodzinnych, a tak e budowy nowych i rozbudowy istniej cych system w grzewczych. 10.260047281323876 21.7 Kangar Securities Economy, business and finance/Market and exchange/Securities Raul Palma service-account-enrichment Applied sciences 5429 https://api.rohub.org/api/ros/1be0f190-6a64-4696-89ba-3509748d84fa/crate/download/ 2022-07-18 13:07:15.313202+00:00 2025-10-18 11:31:44.980651+00:00 2022-07-18 13:07:15.313202+00:00 The goal is to generate automatically a RO from a DMP using RDA DMP Common Standard for Machine-actionable DMP. application/ld+json https://w3id.org/ro-id/1be0f190-6a64-4696-89ba-3509748d84fa Data Management Plan using RDA DMP Common Standard for Machine-actionable DMP MANUAL Anne Foilloux. "Data Management Plan using RDA DMP Common Standard for Machine-actionable DMP." ROHub. Jul 18 ,2022. https://w3id.org/ro-id/1be0f190-6a64-4696-89ba-3509748d84fa. data raw data biblio metadata data management 22.174840085287848 10.4 Machine-actionable DMP 25.154004106776178 24.5 earth sciences 100.0 0.5071393251419067 goal 20.25586353944563 9.5 plan 9.814612868047982 9.0 mathematical and computer sciences 100.0 0.8756278157234192 DMP Common Standard 5.236139630390142 5.1 standard 10.021321961620469 4.7 Language Arts, culture and entertainment/Culture/Language computer operations and hardware 100.0 0.8756278157234192 Ro from a DMP 4.928131416837782 4.8 Ro 26.865671641791046 12.6 goal 10.032715376226825 9.2 RDA DMP 28.644763860369608 27.9 plan 20.68230277185501 9.7 RDA 19.73827699018539 18.1 data management plan 36.03696098562628 35.1 geophysics 100.0 0.5071393251419067 The goal is to generate automatically a RO from a DMP using RDA DMP Common Standard for Machine-actionable DMP. 53.35335335335335 53.3 Ro 14.394765539803707 13.2 Data Management Plan using RDA DMP Common Standard for Machine-actionable DMP. 46.646646646646644 46.6 Machine 22.57360959651036 20.7 data management 11.995637949836423 11.0 Common Standard 11.450381679389313 10.5 Anne Fouilloux service-account-enrichment Applied sciences 2459 https://api.rohub.org/api/ros/095cd4b8-7027-4b97-bf9d-511fc5351d6d/crate/download/ 2022-07-22 08:45:34.245892+00:00 2025-10-18 11:24:46.077488+00:00 2022-07-22 08:45:34.245892+00:00 Data on beach litter application/ld+json https://w3id.org/ro-id/095cd4b8-7027-4b97-bf9d-511fc5351d6d Marine litter MANUAL Bocci, Martina. "Marine litter." ROHub. Jul 22 ,2022. https://w3id.org/ro-id/095cd4b8-7027-4b97-bf9d-511fc5351d6d. life sciences (general) 100.0 0.7818937301635742 marine litter 39.0992835209826 38.2 Data on beach litter 61.56156156156156 61.5 life sciences 100.0 0.7818937301635742 information 51.42857142857143 30.6 Marine litter. 38.43843843843844 38.4 litter 48.57142857142857 28.9 data 31.934493346980553 31.2 beach litter 6.506506506506506 6.5 earth sciences 100.0 0.8758946061134338 litter 28.96622313203685 28.3 oceanography 100.0 0.8758946061134338 data on beach litter 93.49349349349349 93.4 Martina Bocci service-account-enrichment Earth sciences 10.13039/501100000780 European Commission 10.13039/501100000781 European Commission Elisa Trasatti https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-11-08 16:30:52.813503+00:00 2021-11-08 17:06:22.193615+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-11-08 16:30:52.813503+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-11-08 16:31:25.130170+00:00 2021-11-08 17:06:22.296703+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-11-08 16:31:25.130170+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-11-08 16:31:09.076275+00:00 2021-11-08 17:06:22.491861+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-11-08 16:31:09.076275+00:00 101017501 RELIANCE 101017502 RELIANCE POINT (38.0 38.0) 5926d4c9-986f-42f2-a840-79ae265f653f POINT (38.0 38.0) 38.0 38.0 POINT (38.0 38.0) False 2021-11-08 17:06:28.738078+00:00 79418 https://api.rohub.org/api/ros/bcb5cdba-0605-4602-bd60-b59f2701e05b/crate/download/ 2021-11-08 15:12:22.689370+00:00 2025-10-16 10:35:19.041970+00:00 2021-11-08 15:12:22.689370+00:00 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified application/ld+json https://w3id.org/ro-id/bcb5cdba-0605-4602-bd60-b59f2701e05b 8th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot MANUAL Jose Perez, and Elisa Trasatti. "8th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot." ROHub. Nov 08 ,2021. https://doi.org/10.24424/1k12-x394. ICHB-PAS Jose Perez PSNC 73394 https://api.rohub.org/api/resources/1f611f7e-a4b7-45de-be8e-d6f0e39d2fde/download/ 2021-11-08 16:30:06.553639+00:00 2021-11-08 17:06:22.592157+00:00 image/png flow-dcro.png 2021-11-08 16:30:06.553639+00:00 Daily PM10 concentration for 1st September 2018 over Europe Daily PM10 concentration This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental. EU_CAMS_SURFACE_PM10_G Flow to compute monthly map Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services List of hourly PM10 concentration data for September 1st 2018 over Europe Index of daily PM10 concentration for September 1st 2018 research object 83.11557788944724 82.7 map 17.05639614855571 12.4 PM10 13.541666666666666 13.0 Copernicus Atmosphere Monitoring Service 8.229166666666666 7.9 object 25.208333333333332 24.2 Nov-8 research 31.145833333333332 29.9 data cube research object 1.0050251256281406 1.0 8th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot. 30.330330330330334 30.3 aim 31.499312242090785 22.9 country 8.541666666666666 8.2 earth sciences 100.0 0.8168788552284241 atmospheric sciences 100.0 0.8168788552284241 research 39.61485557083906 28.8 map 13.333333333333334 12.8 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified 69.66966966966967 69.6 country 11.829436038514443 8.6 monthly map 6.231155778894473 6.2 map of PM10 9.246231155778894 9.2 astronautics 100.0 0.3785407543182373 astronautics (general) 100.0 0.3785407543182373 data cube 0.4020100502512563 0.4 https://zenodo.org/record/5554786#.YYlWo9nMI-Q 2021-11-08 16:59:14.401521+00:00 2021-11-08 17:06:22.390417+00:00 https://zenodo.org/record/5554786#.YYlWo9nMI-Q 2021-11-08 16:59:14.401521+00:00 Raul Palma service-account-enrichment Earth sciences https://github.com/NordicESMhub/RELIANCE/blob/main/MOD_Aqua_ADAM.ipynb 2021-11-08 21:09:59.780719+00:00 2021-11-08 21:09:59.781169+00:00 This notebook shows how to use ADAM API and ROHub API Jupyter Notebook for using ADAM-API to access MODIS Aqua 2021-11-08 21:09:59.780719+00:00 concentration chlorophyll concentration 10.32064128256513 10.3 concentration 13.554216867469878 13.5 analysis 6.526104417670682 6.5 concentration 22.02852614896989 13.9 Research Object 15.863453815261042 15.8 This Research Object aggregates the resources associated with the analysis of MOD_Aqua mass concentration chlorophyll concentration in sea water 65.36536536536536 65.3 Analysis of MOD_Aqua mass concentration chlorophyll concentration in sea water. 34.63463463463463 34.6 geochemistry 100.0 0.7202270030975342 salt water 29.001584786053883 18.3 geosciences 100.0 0.9254304766654968 geophysics 100.0 0.9254304766654968 chlorophyll 37.717908082408876 23.8 109619 https://api.rohub.org/api/ros/9e533d0d-b1de-4b0d-9dd8-14d136aacea5/crate/download/ 2021-11-08 21:06:20.914340+00:00 2025-12-17 10:08:29.660011+00:00 2021-11-08 21:06:20.914340+00:00 This Research Object aggregates the resources associated with the analysis of MOD_Aqua mass concentration chlorophyll concentration in sea water application/ld+json https://w3id.org/ro-id/9e533d0d-b1de-4b0d-9dd8-14d136aacea5 Analysis of MOD_Aqua mass concentration chlorophyll concentration in sea water MANUAL https://w3id.org/ro-id/0db12483-1d72-4ec5-8f43-7244a0ef5cb5 https://w3id.org/ro-id/3e602429-165b-4c38-821b-b185c2d19566 https://w3id.org/ro-id/95d3e2f1-2706-446e-a12f-00e5f22e43aa https://w3id.org/ro-id/a6cca92d-f385-4230-a0e1-881e29db8601 https://w3id.org/ro-id/34fd419d-c014-4140-b4a8-92a58fe19b07 https://w3id.org/ro-id/b925e277-dafb-48da-b69b-443ee492e971 https://w3id.org/ro-id/02d44787-a55c-4dc5-8968-38360eb4712c https://w3id.org/ro-id/033fe89c-7935-4136-94ab-bc6b8e4631fb https://w3id.org/ro-id/2280c53a-ef9b-4fd6-ad25-331b51fd21ce https://w3id.org/ro-id/9f1673cc-ed44-43c0-a513-13baff083467 https://w3id.org/ro-id/bb654c5f-afb3-4284-a3ae-7e0eada02b24 https://w3id.org/ro-id/c9755e58-000b-4ff3-9ac0-e5c8a600f8ee https://w3id.org/ro-id/e5495369-d48b-4536-bee2-676a5ed66a7f https://w3id.org/ro-id/549fc843-cefc-4f70-ae2f-6e4bd6397645 https://w3id.org/ro-id/7cbd7a86-f1b1-4244-8b15-00af8d6c53fe https://w3id.org/ro-id/0140bc8c-4555-4103-acf5-334ab798e827 https://w3id.org/ro-id/d8454f8f-1581-4f2a-b45c-7cef3a7285e8 https://w3id.org/ro-id/f0492ea2-a97b-4c28-837a-82528d4fb014 https://w3id.org/ro-id/ff180a79-e2a8-4156-bdd5-aeaaefc1d8b9 https://w3id.org/ro-id/297b7d28-5cbd-49ba-b01b-ecf37bd32a05 https://w3id.org/ro-id/30408fdd-52d2-41a1-b306-962f6bf9e3c3 Anne Foilloux, and Anne Foilloux. "Analysis of MOD_Aqua mass concentration chlorophyll concentration in sea water." ROHub. Nov 08 ,2021. https://w3id.org/ro-id/9e533d0d-b1de-4b0d-9dd8-14d136aacea5. 106111 https://api.rohub.org/api/resources/1be16907-9d03-456d-a2ec-db11e3a8af2f/download/ 2021-11-08 21:08:02.599866+00:00 2021-11-08 21:08:02.600559+00:00 image/png Mass concentration chlorophyll concentration in sea water Year 2013 over the Mediteranean region 2021-11-08 21:08:02.599866+00:00 MOD_Aqua 14.257028112449799 14.2 resource 11.251980982567353 7.1 2022-03-24 11:53:42.281517+00:00 earth sciences 100.0 0.7202270030975342 resource 7.228915662650602 7.2 chlorophyll 24.196787148594375 24.1 chlorophyll concentration 84.1683366733467 84.0 sea water 18.373493975903614 18.3 aggregate the resource 5.01002004008016 5.0 mass concentration chlorophyll concentration 0.5010020040080161 0.5 Anne Fouilloux Raul Palma service-account-enrichment Earth sciences research object 83.11557788944724 82.7 map 17.05639614855571 12.4 country 11.829436038514443 8.6 False https://w3id.org/ro-id/321e3b22-04a7-48f8-a647-7ebc49c19301 2021-11-09 16:18:39.029666+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl POINT (38.0 38.0) Nov-9 38.0 38.0 POINT (38.0 38.0) 9b071de5-4738-4072-9e66-4822fb20d61a POINT (38.0 38.0) service-account-enrichment https://w3id.org/ro-id/0e5f85c2-45ce-4b79-af5b-a940086cc802 https://w3id.org/ro-id/48eb1f98-3c64-4dd2-95b7-fe7044b08ff1 https://w3id.org/ro-id/4df864f9-4427-4f6d-a11a-b6f1a340eb42 https://w3id.org/ro-id/56840bfe-6946-4cb1-a8a4-e4e3c4927063 False https://w3id.org/ro-id/2755900c-b77c-4a29-ac59-f6f51af20fa7 2021-11-09 16:23:28.991236+00:00 mailto:rpalma@man.poznan.pl 81973 https://api.rohub.org/api/ros/321e3b22-04a7-48f8-a647-7ebc49c19301/crate/download/ 2021-11-09 15:51:17.774513+00:00 2025-03-05 00:45:33.607132+00:00 2021-11-09 15:51:17.774513+00:00 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified application/ld+json https://w3id.org/ro-id/321e3b22-04a7-48f8-a647-7ebc49c19301 9th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot MANUAL https://w3id.org/ro-id/321e3b22-04a7-48f8-a647-7ebc49c19301/bc445fcb-5960-4feb-a1ae-5ca50453ad6e https://w3id.org/ro-id/0b1f7680-3fc1-47db-b176-0440853ecde0 https://w3id.org/ro-id/0bcf2515-210c-4717-8b9a-e337adbcef55 https://w3id.org/ro-id/7d9815be-40e5-4718-ac91-8d865d795324 https://w3id.org/ro-id/e5b7d130-4697-4a7b-9a2c-16756071ba04 https://w3id.org/ro-id/8284ac3e-dc7f-4d20-806c-0a94b344af89 https://w3id.org/ro-id/e7c9062c-5cba-473f-bf89-259f6dcaae5d https://w3id.org/ro-id/a7e8d560-a7df-4aa4-9472-3811d8ee43c6 https://w3id.org/ro-id/aa3e2a7e-7135-44ca-8d61-39390c727761 https://w3id.org/ro-id/c303edac-f3f8-470c-be5f-0d776c719869 https://w3id.org/ro-id/e6323df0-add4-4f69-9a0b-b464fbe20b56 https://w3id.org/ro-id/eb46cc83-dbea-468f-9d40-48d383c42557 https://w3id.org/ro-id/ebf1d891-b6d4-4462-9a93-e7c0bea64e81 https://w3id.org/ro-id/da144e0f-548b-4ba9-a351-6fe62c0e6635 https://w3id.org/ro-id/ff422ab5-a055-493a-b016-fb9dec5db6cb https://w3id.org/ro-id/096fd79f-1da7-4130-8560-50bf8860e376 https://w3id.org/ro-id/6d5cd942-1e2f-4661-9460-e31f9cd16732 https://w3id.org/ro-id/db392796-e679-4c0a-ae88-4db03f91ac9c https://w3id.org/ro-id/e21fdf10-81c2-4d5e-ba0e-f27768551e15 https://w3id.org/ro-id/f241bce9-3878-4c85-a937-860380c8cd3e https://w3id.org/ro-id/3f23826e-7037-4a82-84c0-954a1fac2062 https://w3id.org/ro-id/bcc38d7f-6ca4-4809-a13e-3afbdd362efe https://w3id.org/ro-id/2bba2635-0803-4822-bfe2-7c15d2f0bba4 Palma, Raul. "9th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot." ROHub. Nov 09 ,2021. https://doi.org/10.24424/j2gh-5322. List of hourly PM10 concentration data for September 1st 2018 over Europe Index of daily PM10 concentration for September 1st 2018 https://zenodo.org/record/5554786#.YYlWo9nMI-Q 2021-11-09 15:52:03.894247+00:00 2021-11-09 16:23:26.891779+00:00 https://zenodo.org/record/5554786#.YYlWo9nMI-Q 2021-11-09 15:52:03.894247+00:00 73394 https://api.rohub.org/api/resources/440e3907-011c-4185-936a-16a0a868a444/download/ 2021-11-09 15:51:45.742090+00:00 2021-11-09 16:23:26.956721+00:00 image/png flow-dcro.png 2021-11-09 15:51:45.742090+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-11-09 15:51:59.534956+00:00 2021-11-09 16:23:26.855020+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-11-09 15:51:59.534956+00:00 This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental. EU_CAMS_SURFACE_PM10_G Flow to compute monthly map https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-11-09 15:51:51.850517+00:00 2021-11-09 16:23:26.816350+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-11-09 15:51:51.850517+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-11-09 15:51:56.143768+00:00 2021-11-09 16:23:26.923462+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-11-09 15:51:56.143768+00:00 Daily PM10 concentration for 1st September 2018 over Europe Daily PM10 concentration Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services This Research Object demonstrate how to compute monthly map of PM10 over your country - modified 69.66966966966967 69.6 False https://w3id.org/ro-id/321e3b22-04a7-48f8-a647-7ebc49c19301 2021-11-09 16:19:16.618594+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl False https://w3id.org/ro-id/321e3b22-04a7-48f8-a647-7ebc49c19301 2021-11-09 16:06:58.516914+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl False https://w3id.org/ro-id/321e3b22-04a7-48f8-a647-7ebc49c19301 2021-11-09 16:15:26.873492+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl monthly map 6.231155778894473 6.2 aim 31.499312242090785 22.9 atmospheric sciences 100.0 0.7866491675376892 object 25.208333333333332 24.2 PM10 13.541666666666666 13.0 9th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot. 30.330330330330334 30.3 research 31.145833333333332 29.9 astronautics (general) 100.0 0.38756152987480164 data cube research object 1.0050251256281406 1.0 data cube 0.4020100502512563 0.4 research 39.61485557083906 28.8 map 13.333333333333334 12.8 earth sciences 100.0 0.7866491675376892 Copernicus Atmosphere Monitoring Service 8.229166666666666 7.9 country 8.541666666666666 8.2 map of PM10 9.246231155778894 9.2 astronautics 100.0 0.38756152987480164 Raul Palma Earth sciences False https://w3id.org/ro-id/164e222b-0bdd-4638-93e7-010bad13d655 2021-11-09 16:18:39.029666+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl monthly map 6.231155778894473 6.2 38.0 38.0 POINT (38.0 38.0) ee61e733-5a21-43d3-a8b9-1e7e3cd58df1 POINT (38.0 38.0) service-account-enrichment https://w3id.org/ro-id/0e5f85c2-45ce-4b79-af5b-a940086cc802 https://w3id.org/ro-id/321e3b22-04a7-48f8-a647-7ebc49c19301 https://w3id.org/ro-id/48eb1f98-3c64-4dd2-95b7-fe7044b08ff1 https://w3id.org/ro-id/4df864f9-4427-4f6d-a11a-b6f1a340eb42 https://w3id.org/ro-id/56840bfe-6946-4cb1-a8a4-e4e3c4927063 False https://w3id.org/ro-id/2755900c-b77c-4a29-ac59-f6f51af20fa7 2021-11-09 16:38:47.238379+00:00 mailto:rpalma@man.poznan.pl 82295 https://api.rohub.org/api/ros/164e222b-0bdd-4638-93e7-010bad13d655/crate/download/ 2021-11-09 15:51:17.774513+00:00 2025-03-05 00:45:33.909189+00:00 2021-11-09 15:51:17.774513+00:00 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified application/ld+json https://w3id.org/ro-id/164e222b-0bdd-4638-93e7-010bad13d655 9th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot MANUAL https://w3id.org/ro-id/164e222b-0bdd-4638-93e7-010bad13d655/bc445fcb-5960-4feb-a1ae-5ca50453ad6e https://w3id.org/ro-id/7dc16fbc-7188-4209-9937-a7a2932d2997 https://w3id.org/ro-id/82a04fbd-62bc-4b45-9d39-7cf5f1034dc8 https://w3id.org/ro-id/8ffcf3e4-af24-4061-a08e-5ed6c080b739 https://w3id.org/ro-id/eb545d52-4143-4b2a-be9d-c074ac089f17 https://w3id.org/ro-id/9b55ecf3-2e9a-4a92-a0fe-484a62c91593 https://w3id.org/ro-id/a8b59a03-2bf8-4736-a216-fbe8f75e6e67 https://w3id.org/ro-id/531895fd-615d-47cd-97ab-61244289921e https://w3id.org/ro-id/84fc9958-604b-4750-a50f-9638ad628bdf https://w3id.org/ro-id/91354b80-10cb-4027-9832-cb9ed4792db6 https://w3id.org/ro-id/913c9817-553d-458a-a319-0ec12c61a2b7 https://w3id.org/ro-id/f4db0903-93b0-4f0f-b25c-904a33dbc608 https://w3id.org/ro-id/f70dd780-e275-4682-8ac2-fcc47d3307f4 https://w3id.org/ro-id/1af0e739-034c-4d44-87b7-0af39b5ad382 https://w3id.org/ro-id/24eec82c-8ece-445a-8e1a-73d98222c0c2 https://w3id.org/ro-id/0f6a7d8f-9ba6-4741-8687-cad255b1516c https://w3id.org/ro-id/6c3b3f18-4625-48c0-8594-bf13fc863dd7 https://w3id.org/ro-id/cb1a64b5-d528-48f4-8151-0c7684cfa128 https://w3id.org/ro-id/d3e198c4-80cb-4099-8414-e97c9798c120 https://w3id.org/ro-id/d9523df2-d927-46e8-8379-02a12a2e92ce https://w3id.org/ro-id/6bf626d2-4ee2-4fed-a8f6-4aed427ef252 https://w3id.org/ro-id/886380ba-096d-4c04-ba1d-ff6f0d57f001 https://w3id.org/ro-id/afec8c8a-2d85-4ef7-9efb-6c5579d4c1bb Palma, Raul. "9th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot." ROHub. Nov 09 ,2021. https://doi.org/10.24424/yw22-x266. List of hourly PM10 concentration data for September 1st 2018 over Europe Index of daily PM10 concentration for September 1st 2018 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-11-09 15:51:56.143768+00:00 2021-11-09 16:38:44.990014+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-11-09 15:51:56.143768+00:00 73394 https://api.rohub.org/api/resources/0369a2c2-53af-4929-a325-ecaa4f28eb78/download/ 2021-11-09 15:51:45.742090+00:00 2021-11-09 16:38:45.030794+00:00 image/png flow-dcro.png 2021-11-09 15:51:45.742090+00:00 https://zenodo.org/record/5554786#.YYlWo9nMI-Q 2021-11-09 15:52:03.894247+00:00 2021-11-09 16:38:44.952284+00:00 https://zenodo.org/record/5554786#.YYlWo9nMI-Q 2021-11-09 15:52:03.894247+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-11-09 15:51:51.850517+00:00 2021-11-09 16:38:44.873578+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-11-09 15:51:51.850517+00:00 This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental. EU_CAMS_SURFACE_PM10_G https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-11-09 15:51:59.534956+00:00 2021-11-09 16:38:44.915292+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-11-09 15:51:59.534956+00:00 Flow to compute monthly map Daily PM10 concentration for 1st September 2018 over Europe Daily PM10 concentration Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services astronautics (general) 100.0 0.38756152987480164 astronautics 100.0 0.38756152987480164 POINT (38.0 38.0) False https://w3id.org/ro-id/164e222b-0bdd-4638-93e7-010bad13d655 2021-11-09 16:23:28.979805+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl False https://w3id.org/ro-id/164e222b-0bdd-4638-93e7-010bad13d655 2021-11-09 16:19:16.618594+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl False https://w3id.org/ro-id/164e222b-0bdd-4638-93e7-010bad13d655 2021-11-09 16:06:58.516914+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl map 13.333333333333334 12.8 False https://w3id.org/ro-id/164e222b-0bdd-4638-93e7-010bad13d655 2021-11-09 16:15:26.873492+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl 9th November - 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modified 69.66966966966967 69.6 False https://w3id.org/ro-id/7740459a-b9fc-411b-88af-763a0de9d9b1 2021-11-09 16:06:58.516914+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl False https://w3id.org/ro-id/7740459a-b9fc-411b-88af-763a0de9d9b1 2021-11-09 16:15:26.873492+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl map of PM10 9.246231155778894 9.2 atmospheric sciences 100.0 0.7866491675376892 map 13.333333333333334 12.8 country 8.541666666666666 8.2 country 11.829436038514443 8.6 4faa9adb-0eb7-402e-903d-120affa6ab89 POLYGON ((14.049395 40.779358, 14.240586 40.779358, 14.240586 40.912968, 14.049395 40.912968, 14.049395 40.779358)) 38.0 38.0 POINT (38.0 38.0) c6da8692-3f04-4fe7-a9bc-2e4e13362649 POINT (38.0 38.0) POLYGON ((14.049395 40.779358, 14.240586 40.779358, 14.240586 40.912968, 14.049395 40.912968, 14.049395 40.779358)) 14.049395 40.779358, 14.240586 40.779358, 14.240586 40.912968, 14.049395 40.912968, 14.049395 40.779358 service-account-enrichment https://w3id.org/ro-id/0e5f85c2-45ce-4b79-af5b-a940086cc802 https://w3id.org/ro-id/164e222b-0bdd-4638-93e7-010bad13d655 https://w3id.org/ro-id/321e3b22-04a7-48f8-a647-7ebc49c19301 https://w3id.org/ro-id/48eb1f98-3c64-4dd2-95b7-fe7044b08ff1 https://w3id.org/ro-id/4df864f9-4427-4f6d-a11a-b6f1a340eb42 https://w3id.org/ro-id/56840bfe-6946-4cb1-a8a4-e4e3c4927063 https://w3id.org/ro-id/ad8a8265-109b-4979-b78a-15b205d71029 False https://w3id.org/ro-id/2755900c-b77c-4a29-ac59-f6f51af20fa7 2021-11-10 19:38:10.173024+00:00 mailto:rpalma@man.poznan.pl 83923 https://api.rohub.org/api/ros/7740459a-b9fc-411b-88af-763a0de9d9b1/crate/download/ 2021-11-09 15:51:17.774513+00:00 2025-03-05 00:45:34.213972+00:00 2021-11-09 15:51:17.774513+00:00 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified application/ld+json https://w3id.org/ro-id/7740459a-b9fc-411b-88af-763a0de9d9b1 9th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot MANUAL https://w3id.org/ro-id/7740459a-b9fc-411b-88af-763a0de9d9b1/67781900-3d58-4580-83ff-ffe019453c87 https://w3id.org/ro-id/7740459a-b9fc-411b-88af-763a0de9d9b1/bc445fcb-5960-4feb-a1ae-5ca50453ad6e https://w3id.org/ro-id/7740459a-b9fc-411b-88af-763a0de9d9b1/c5a0801c-994d-4e19-bf26-ff781f3f6e36 https://w3id.org/ro-id/7740459a-b9fc-411b-88af-763a0de9d9b1/f6717a94-7781-4efa-9ee0-8fd556e40e99 https://w3id.org/ro-id/1d77df20-e490-49c8-9251-9bedde3ecbfd https://w3id.org/ro-id/1e65d495-bf36-4cca-a348-1a65e28faa72 https://w3id.org/ro-id/6c12088b-4028-40a1-9b17-d7b44398d83a https://w3id.org/ro-id/c6cf3921-2183-47f1-8c3e-8c1b2e142daf https://w3id.org/ro-id/1a5d3a2b-9d57-4992-bdea-f8967834dfea https://w3id.org/ro-id/5fcc2bc3-9f18-4b0e-aa5a-0b95da2b65cd https://w3id.org/ro-id/24b9443b-552e-4446-969a-50cf57263083 https://w3id.org/ro-id/60683ed5-1558-4679-9c87-1ea1e483e7aa https://w3id.org/ro-id/63bccedb-7934-4485-b9c2-f6eaebde1d89 https://w3id.org/ro-id/8659b679-e36f-4037-9895-1ac4108abb4e https://w3id.org/ro-id/af51d342-c1aa-44d2-b29c-7543440d5cd4 https://w3id.org/ro-id/e79319cb-ebfc-44a1-8c41-c4273808b87a https://w3id.org/ro-id/38cf7bac-6c3e-4fed-b621-c8e830d0e8f9 https://w3id.org/ro-id/423b1fd4-a43a-4d06-9f0c-b2f52ca3445e https://w3id.org/ro-id/0914de84-5bc1-48f3-94d2-68ccf5582581 https://w3id.org/ro-id/5828c608-ea04-4b9b-b4d6-63e085ee9af5 https://w3id.org/ro-id/8d4a3c33-d433-4ba4-a51e-2b741cba348b https://w3id.org/ro-id/a29cb4cb-f1a2-4732-8e1a-707045d6ebda https://w3id.org/ro-id/cebe33f2-566b-4310-bb05-f040eaf81892 https://w3id.org/ro-id/4b19d903-158f-45a4-8f8a-80cf55d3d997 https://w3id.org/ro-id/b0c0763c-f99f-4e9a-b32c-0dd7de567ccd https://w3id.org/ro-id/b7592ce2-424e-435f-b9e7-036738c1f17e Palma, Raul. "9th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot." ROHub. Nov 09 ,2021. https://doi.org/10.24424/zt8j-c157. List of hourly PM10 concentration data for September 1st 2018 over Europe Index of daily PM10 concentration for September 1st 2018 https://zenodo.org/record/5554786#.YYlWo9nMI-Q 2021-11-09 15:52:03.894247+00:00 2021-11-10 19:38:07.510465+00:00 https://zenodo.org/record/5554786#.YYlWo9nMI-Q 2021-11-09 15:52:03.894247+00:00 This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental. EU_CAMS_SURFACE_PM10_G 73394 https://api.rohub.org/api/resources/7f087685-b1b1-42dc-90b0-ee6b56b2ab75/download/ 2021-11-09 15:51:45.742090+00:00 2021-11-10 19:38:07.580119+00:00 image/png flow-dcro.png 2021-11-09 15:51:45.742090+00:00 Flow to compute monthly map https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-11-09 15:51:51.850517+00:00 2021-11-10 19:38:07.439709+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-11-09 15:51:51.850517+00:00 Daily PM10 concentration for 1st September 2018 over Europe Daily PM10 concentration https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-11-09 15:51:59.534956+00:00 2021-11-10 19:38:07.476563+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-11-09 15:51:59.534956+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-11-09 15:51:56.143768+00:00 2021-11-10 19:38:07.545500+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-11-09 15:51:56.143768+00:00 Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services Copernicus Atmosphere Monitoring Service 8.229166666666666 7.9 data cube 0.4020100502512563 0.4 monthly map 6.231155778894473 6.2 False https://w3id.org/ro-id/7740459a-b9fc-411b-88af-763a0de9d9b1 2021-11-10 12:04:39.530811+00:00 https://w3id.org/ro-id/users/rpalma%40man.poznan.pl object 25.208333333333332 24.2 9th November - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot. 30.330330330330334 30.3 Nov-9 aim 31.499312242090785 22.9 research object 83.11557788944724 82.7 PM10 13.541666666666666 13.0 Raul Palma Oceanography Earth sciences Biochemistry https://datahub.egi.eu/api/v3/onezone/shares/data/00000000007E46B7736861726547756964236161643239616133666234633734356464393231356539663536613733616366636836643138233732356634616233366362323664306662666330633132346337373565666565636865653439236361386634383464346533366532646439643230336131383431616362656563636834393661/content 2022-11-29 15:26:53.739562+00:00 2023-06-22 10:59:50.791762+00:00 Data at the Acqua Alta oceanographic tower is a collection of physical and biogeochemical observation in the northern Adriatic Sea https://www.comune.venezia.it/it/content/3-piattaforma-ismar-cnr http://www.ismar.cnr.it/infrastrutture/piattaforma-acqua-alta PTF dataset(2009-2020) Piattaforma acqua allta 2022-11-29 15:26:53.739562+00:00 https://datahub.egi.eu/api/v3/onezone/shares/data/00000000007ECE4C736861726547756964236337653135323330333033383136356532663365646530343262646537343038636836643138233732356634616233366362323664306662666330633132346337373565666565636865653439233836663339353466636461353034663331326637636464363962333037383234636864343237/content 2021-12-22 14:38:45.256955+00:00 2022-11-29 16:15:06.244156+00:00 Jupyter notebook using R 2021-12-22 14:38:45.256955+00:00 https://doi.org/10.5194/essd-12-215-2020 2022-11-29 16:05:17.920104+00:00 2022-11-29 16:06:05.302894+00:00 In this paper, we describe a 50-year (1965–2015) ecological database containing data on plankton communities and related abiotic parameters collected in the northern Adriatic Sea (NAS). Plankton communities, which are at the base of aquatic ecosystem functioning, have a broad and diversified range of seasonal patterns, multi-annual trends, and shifts across different marine ecosystems: making long-term series of plankton and oceanographic observations available provides unique and precious tools for depicting reliable patterns of average annual cycles and for detecting significant changes and trends in response to global or local pressures and impacts. Dataset description 2022-11-29 16:05:17.920104+00:00 CNR-ISMAR malek.belgacem@ve.ismar.cnr.it Malek Belgacem 0000-0003-0745-4155 case study 4.890738813735692 4.7 Adriatic Sea POLYGON ((11.762694865465166 44.67038775819365, 11.762694865465166 45.60037251154824, 13.618163913488388 45.60037251154824, 13.618163913488388 44.67038775819365, 11.762694865465166 44.67038775819365)) 11.762694865465166 44.67038775819365, 11.762694865465166 45.60037251154824, 13.618163913488388 45.60037251154824, 13.618163913488388 44.67038775819365, 11.762694865465166 44.67038775819365 9babe6b2-4629-4111-a574-f1511da18104 POLYGON ((11.762694865465166 44.67038775819365, 11.762694865465166 45.60037251154824, 13.618163913488388 45.60037251154824, 13.618163913488388 44.67038775819365, 11.762694865465166 44.67038775819365)) 1785382 https://api.rohub.org/api/ros/0869e396-3733-4aff-8fb2-94c8937b28aa/crate/download/ 2021-11-29 14:45:39.803487+00:00 2025-03-05 01:19:07.795226+00:00 2021-11-29 14:45:39.803487+00:00 This is a case study of snapshot project http://snapshot.cnr.it/ to investigate the lockdown impact on the water quality at a selected site in the northern Adriatic Sea, precisely in Northern Adriatic Sea, the case of the Gulf of Venice using Machine Learning model. application/ld+json https://w3id.org/ro-id/0869e396-3733-4aff-8fb2-94c8937b28aa Adriatic Sea Biogeochemistry inorganic nutrients lockdown impact marine platform Research Object Snapshot 2021 study case: Lockdown impacts on the Northern Adriatic Sea at selected site: AcquaAlta Platform Water quality MANUAL https://w3id.org/ro-id/32364e73-ae45-4c01-a14a-bc51e70320d5 https://w3id.org/ro-id/de6cb8e6-8634-4db9-9d89-3de77159038a https://w3id.org/ro-id/081c77a2-2454-4a9d-bf06-ba5ee57ac30f https://w3id.org/ro-id/5cdf50db-4c51-4498-9100-209eebb8fc94 https://w3id.org/ro-id/04c5003a-5357-4cbd-81d2-2027c870062c https://w3id.org/ro-id/186ce286-667e-4048-afd6-37115e55a749 https://w3id.org/ro-id/21ee4901-d22c-47d6-99d7-26db44dae53d https://w3id.org/ro-id/3a8bd7a3-3845-4f8d-9702-9c021a451812 https://w3id.org/ro-id/4fb2baef-3923-4609-9fc8-4de57885bf4b https://w3id.org/ro-id/7b02f0ce-4765-43ab-aa20-41d165264a86 https://w3id.org/ro-id/7c6c4ba8-875e-4403-93e3-4154b66d97b3 https://w3id.org/ro-id/87c08759-3c26-4ff0-8327-d2842c4bb5ef https://w3id.org/ro-id/ac088099-0316-403c-bbe8-271e9cec491e https://w3id.org/ro-id/c6c2224d-2b1d-434e-bcf0-ea556d3dcb50 https://w3id.org/ro-id/dbca260c-e9f1-4cd4-b5da-3d4f74708ce1 https://w3id.org/ro-id/0d32d2db-ea94-4733-aa43-fb079fb997d1 https://w3id.org/ro-id/7f13e266-3c8e-4bbb-a4d0-4576f222927d https://w3id.org/ro-id/35020f27-6e26-4a1b-84e4-ef25c652158c https://w3id.org/ro-id/50b46e80-e71d-4772-83b7-8a5ea277b052 https://w3id.org/ro-id/185f2270-805a-4669-bb44-830bee256947 https://w3id.org/ro-id/75a11d78-b8e5-41f0-a8d8-de167380dff9 https://w3id.org/ro-id/7e3d3c52-6921-4ab1-b486-ae86b5d9cf05 https://w3id.org/ro-id/9d236df1-a6ef-4bd1-85a3-0f4a88675bf6 https://w3id.org/ro-id/b3e44687-2358-497d-8fb4-478467ea19a8 https://w3id.org/ro-id/e11ad585-3fb3-4399-9d94-839faf7fb8a0 https://w3id.org/ro-id/f771803a-7ae9-43f8-8c15-41b214fec39c https://w3id.org/ro-id/4684e0f2-d68e-4ca9-97d8-fb71e6ffb984 https://w3id.org/ro-id/919b433d-808c-4b6d-a635-2e4197524edc https://w3id.org/ro-id/3294b71f-7f2d-41c1-a42a-61a33dd0ed98 https://w3id.org/ro-id/6be9833b-436d-4998-adf3-541da8dd9c03 https://w3id.org/ro-id/99970636-75e9-4088-a200-6ff7de907159 https://w3id.org/ro-id/a131b587-56fe-48ea-a938-d9009236b975 https://w3id.org/ro-id/c23b36ca-c91c-4a5f-8a8c-759d21d9cc67 https://w3id.org/ro-id/1cd3ffb4-ad25-4b0e-ac58-66c6d300234c https://w3id.org/ro-id/a1cdf83b-c6cf-43e8-8ebd-0dbef6a88205 https://w3id.org/ro-id/638d85ed-0513-4a62-9dd8-a8e5ce7ba5eb Belgacem, Malek, Mauro Bastianini, and Jacopo Chiggiato. "Snapshot 2021 study case: Lockdown impacts on the Northern Adriatic Sea at selected site: AcquaAlta Platform Water quality." ROHub. Nov 29 ,2021. https://w3id.org/ro-id/0869e396-3733-4aff-8fb2-94c8937b28aa. POLYGON ((11.762694865465166 44.67038775819365, 11.762694865465166 45.60037251154824, 13.618163913488388 45.60037251154824, 13.618163913488388 44.67038775819365, 11.762694865465166 44.67038775819365)) Output Dataset Jupyter_tool 26131 https://api.rohub.org/api/resources/1b950828-28e0-4725-abcb-73f33d0bf32e/download/ 2021-12-22 14:05:23.636780+00:00 2021-12-22 14:05:23.638961+00:00 image/png NO3_change_obsvspred2020.png 2021-12-22 14:05:23.636780+00:00 1049814 https://api.rohub.org/api/resources/28208669-c1ef-475e-85ac-8114691c154d/download/ 2023-06-09 11:33:24.938835+00:00 2023-06-09 11:33:25.669288+00:00 image/png reliance deliv dec2021.png 2023-06-09 11:33:24.938835+00:00 41569 https://api.rohub.org/api/resources/32f66214-fac2-44b8-af57-559916593747/download/ 2021-12-22 14:06:14.381079+00:00 2021-12-22 14:06:44.434429+00:00 image/png NO3_ts_ptf_decompose.png 2021-12-22 14:06:14.381079+00:00 55841 https://api.rohub.org/api/resources/548ed54f-2d96-4e0c-9633-cbb22a04fd20/download/ 2021-12-22 14:06:01.775038+00:00 2021-12-22 14:06:01.777430+00:00 image/png NO3_predict_obsvspred2020vs20092019.png 2021-12-22 14:06:01.775038+00:00 49353 https://api.rohub.org/api/resources/aa6894c2-5c4d-4c39-817b-d63fb155141d/download/ 2021-12-22 14:05:43.603856+00:00 2021-12-22 14:05:43.605820+00:00 image/png NO3_predict_obsvspred2020.png 2021-12-22 14:05:43.603856+00:00 296189 https://api.rohub.org/api/resources/d87d7c73-70c4-4243-9f8b-1b22ad5f4338/download/ 2021-12-22 12:23:51.989470+00:00 2021-12-22 12:23:51.990626+00:00 image/jpeg Study area 2021-12-22 12:23:51.989470+00:00 88174 https://api.rohub.org/api/resources/eaee63ca-aaa5-46eb-8b8a-0d696d1340e9/download/ 2022-07-15 16:29:07.183540+00:00 2023-06-22 10:56:15.115165+00:00 image.jfif 2022-07-15 16:29:07.183540+00:00 444613 https://api.rohub.org/api/resources/fad0f0b1-a385-40df-8698-a1e61df13161/download/ 2021-12-15 15:16:09.372184+00:00 2021-12-15 15:16:09.373777+00:00 image/png RO workflow 2021-12-15 15:16:09.372184+00:00 environmental sciences 100.0 0.5102767944335938 Gulf of Venice 8.92018779342723 7.6 Gulf of Venice 7.075962539021853 6.8 Snapshot 2021 study case: Lockdown impacts on the Northern Adriatic Sea at selected site: AcquaAlta Platform Water quality. 33.83383383383383 33.8 snapshot 4.474505723204995 4.3 hydrography 39.42307692307692 4.1 northern Adriatic Sea 17.122473246135556 14.4 Crime Crime, law and justice/Crime machine learning 6.76378772112383 6.5 geophysics 100.0 0.33035168051719666 Adriatic Sea 25.390218522372532 24.4 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences Gulf of Venice 2021 case of the Gulf of Venice 7.134363852556481 6.0 machine learning 8.685446009389672 7.4 lockdown 23.621227887617067 22.7 impact 6.139438085327784 5.9 project 7.15962441314554 6.1 environmental science and management 100.0 0.5102767944335938 project 6.243496357960458 6.0 geosciences 100.0 0.33035168051719666 machine learning model 17.954815695600477 15.1 impact 7.511737089201878 6.4 snapshot project http 39.00118906064209 32.8 This is a case study of snapshot project http://snapshot.cnr.it/ to investigate the lockdown impact on the water quality at a selected site in the northern Adriatic Sea, precisely in Northern Adriatic Sea, the case of the Gulf of Venice using Machine Learning model. 66.16616616616616 66.1 site 3.121748178980229 3.0 Adriatic Sea 28.990610328638496 24.7 lockdown impact 18.7871581450654 15.8 http 8.844953173777316 8.5 Synoptic Assessment of Human Pressures on key Mediterranean Hot Spots The SNAPSHOT project contributes to the informed public debate trying to answer the above questions through an observation campaign involving scientists and citizens with the commo jacopo.chiggiato@ismar.cnr.it SNAPSHOT: the pandemic and post-pandemic marine environment at a glance http://www.bluemed-initiative.eu/snapshot/ snapshot 3.433922996878252 3.3 computer science 60.57692307692309 6.3 http 10.798122065727698 9.2 lockdown 27.934272300469484 23.8 https://zenodo.org/record/3516717#.YboDGWjMI2x 2022-11-29 16:06:59.179645+00:00 2022-11-29 16:07:01.609968+00:00 The present database contains observations for 22 parameters of abiotic, phyto and zooplankton data collected in the Northern Adriatic Sea region (Italy). It relies on a Comma Separated Values file and it is composed by 108687 records. Due to its long temporal coverage, it is classifiable as Long Term Ecological data. Due to the long temporal coverage, the great part of parameters changed collection and analysis method in time. These variations are reported in the database. A long term database can be useful for multiple purposes. This database has been released under a research project focused on Open Science principles application to marine ecology. Dataset source 2022-11-29 16:06:59.179645+00:00 direttore@ismar.cnr.it CNR-ISMAR CNR-ISMAR jacopo.chiggiato@ismar.cnr.it Jacopo Chiggiato CNR-ISMAR mauro.bastianini@ismar.cnr.it Mauro Bastianini service-account-enrichment Geology Applied sciences Earth sciences Ecology giorgio.castellan@bo.ismar.cnr.it Giorgio Castellan 0000-0001-6084-1504 CNR-ISMAR malek.belgacem@ve.ismar.cnr.it Malek Belgacem 0000-0003-0745-4155 geosciences 100.0 0.4974074065685272 concentrations in seawater 22.285067873303166 19.7 Spatial and temporal distribution of Cold Water Corals (CWC) in the Mediterranean Sea - Data. 42.24224224224224 42.2 distribution 10.340314136125654 7.9 7ce41391-7238-4cff-811b-cbd4c074e2d8 POLYGON ((-10.265629291534426 29.22888417844566, -10.265629291534426 46.12198587773459, 38.812497854232795 46.12198587773459, 38.812497854232795 29.22888417844566, -10.265629291534426 29.22888417844566)) POLYGON ((-10.265629291534426 29.22888417844566, -10.265629291534426 46.12198587773459, 38.812497854232795 46.12198587773459, 38.812497854232795 29.22888417844566, -10.265629291534426 29.22888417844566)) -10.265629291534426 29.22888417844566, -10.265629291534426 46.12198587773459, 38.812497854232795 46.12198587773459, 38.812497854232795 29.22888417844566, -10.265629291534426 29.22888417844566 service-account-enrichment 163620 https://api.rohub.org/api/ros/1c87c3d6-46f0-4bfe-bc73-88282fb8c3c5/crate/download/ 2021-12-07 15:20:52.205188+00:00 2025-03-05 01:19:13.509426+00:00 2021-12-07 15:20:52.205188+00:00 Data on temperature, salinity, dissolved oxygen, pH, and nutrient concentrations in seawater used to explore how environmental variables influence the distribution of CWC in the Mediterranean Sea application/ld+json https://w3id.org/ro-id/1c87c3d6-46f0-4bfe-bc73-88282fb8c3c5 MediterraneanSea ResearchProject SeaMonitoring Spatial and temporal distribution of Cold Water Corals (CWC) in the Mediterranean Sea - Data MANUAL https://w3id.org/ro-id/1c87c3d6-46f0-4bfe-bc73-88282fb8c3c5/3ebad49a-f8d8-4dce-9b9a-9f6e27cd5106 https://w3id.org/ro-id/f9cd2ada-3259-4b76-b78f-27d117798018 https://w3id.org/ro-id/eb8c6e5f-abba-4bd0-adb2-7b68c6fe21d9 https://w3id.org/ro-id/1b203cf0-20a3-4696-9581-d6c43d88bcf7 https://w3id.org/ro-id/2484625e-7f31-48c9-97b2-d26dc38f75aa https://w3id.org/ro-id/2c06d311-7204-4595-bf4a-6b56897adf72 https://w3id.org/ro-id/2e99157b-d1de-4959-ba0b-2e549e045edf https://w3id.org/ro-id/432f04ac-dd43-4c14-abbf-c9ae57c765b6 https://w3id.org/ro-id/a9538610-68ae-451c-bc7d-560f17078a3d https://w3id.org/ro-id/b58da8e5-7398-4627-9119-97124ac0e93a https://w3id.org/ro-id/c178a52b-5691-4812-a757-783016e57ab2 https://w3id.org/ro-id/fec59027-5488-4d8b-abbd-3ee2c526e1c9 https://w3id.org/ro-id/851af502-a5ea-4aaf-bca8-85c20b70a773 https://w3id.org/ro-id/a6bbb46e-3b81-4b38-8ca8-d0bb1ce8c772 https://w3id.org/ro-id/437a80c8-c002-4cbf-8e41-a2b675c3c47c https://w3id.org/ro-id/9d533f05-d7e2-4dbb-b4d6-33983ac155d3 https://w3id.org/ro-id/1d1c0aef-740f-4ba4-bf7e-0cff00e317ea https://w3id.org/ro-id/3fa367c5-3f3e-4ba8-bee4-d3fe054485b0 https://w3id.org/ro-id/45c39300-6165-4ae7-8a22-c73be6cad966 https://w3id.org/ro-id/5f5968b3-478b-420b-a827-a3c953c3ca57 https://w3id.org/ro-id/6690fbf2-b62b-4ad9-96b0-73382001b959 https://w3id.org/ro-id/a01f9ba2-684a-4133-8870-fc9c756538f0 https://w3id.org/ro-id/ae3a4178-a3fa-48c1-83b3-b5b0f67752c6 https://w3id.org/ro-id/01fb6ffe-0f0e-49c4-b575-2c1f86aeb1ff https://w3id.org/ro-id/a74077ed-f9f0-4410-95c5-5629cac76b3f https://w3id.org/ro-id/0678163f-e370-4fc2-a839-7142301e3b6c https://w3id.org/ro-id/3356e64a-99ee-4770-a248-3cf3d24adeb4 https://w3id.org/ro-id/38ab2e3f-9e8e-41b8-9cd0-9360880b5ce0 https://w3id.org/ro-id/9824b34e-5944-4bd6-9bae-abac9dc046ca https://w3id.org/ro-id/be906dbc-5d30-4da1-b93b-6a5c63d51730 https://w3id.org/ro-id/1a06e5e7-3b5a-46d8-bd1f-0fc6d0659384 https://w3id.org/ro-id/20867b26-5388-4fe9-88ab-2a5b6c9335c5 Paolo Montagna, Jacopo Chiggiato, Giorgio Castellan, and Malek Belgacem. "Spatial and temporal distribution of Cold Water Corals (CWC) in the Mediterranean Sea - Data." ROHub. Dec 07 ,2021. https://w3id.org/ro-id/1c87c3d6-46f0-4bfe-bc73-88282fb8c3c5. POLYGON ((-10.265629291534426 29.22888417844566, -10.265629291534426 46.12198587773459, 38.812497854232795 46.12198587773459, 38.812497854232795 29.22888417844566, -10.265629291534426 29.22888417844566)) data input data 30306 https://api.rohub.org/api/resources/3dedb472-6ac3-4ca9-9530-7e7c745a10b8/download/ 2023-06-22 07:48:36.686799+00:00 2023-06-22 07:58:20.937783+00:00 Location and description of living Mediterranean CWC ecosystems application/vnd.openxmlformats-officedocument.spreadsheetml.sheet Living location of Mediterranean CWC 2023-06-22 07:48:36.686799+00:00 145169 https://api.rohub.org/api/resources/f2d36cb2-2662-499e-9130-171e4b904c8f/download/ 2023-06-22 07:40:08.037639+00:00 2023-06-22 07:40:08.549408+00:00 image/jpeg cwc_med.jpg 2023-06-22 07:40:08.037639+00:00 data 14.558823529411764 9.9 Data on temperature, salinity, dissolved oxygen, pH, and nutrient concentrations in seawater used to explore how environmental variables influence the distribution of CWC in the Mediterranean Sea 57.75775775775775 57.7 pH 8.507853403141361 6.5 variable 10.471204188481675 8.0 Mediterranean Sea 16.8848167539267 12.9 environmental variable 11.877828054298641 10.5 distribution of Cold Water Corals 39.59276018099547 35.0 variable 12.205882352941178 8.3 information 13.089005235602093 10.0 Jewellery Arts, culture and entertainment/Arts and entertainment/Fashion/Jewellery Cold Water Coral 17.352941176470587 11.8 Mediterranean Sea 19.11764705882353 13.0 concentration 13.52941176470588 9.2 earth sciences 100.0 0.9809685945510864 data on temperature 7.466063348416289 6.6 Animal Human interest/Animal salinity 11.470588235294118 7.8 oceanography 100.0 0.9809685945510864 geophysics 100.0 0.4974074065685272 salinity 10.078534031413612 7.7 distribution 11.764705882352942 8.0 temperature 8.900523560209423 6.8 nutrient concentration 18.778280542986426 16.6 salt water 9.947643979057592 7.6 Mediterranean Sea https://www.wikidata.org/wiki/Q4918 chemistry 100.0 15.9 concentration 11.780104712041885 9.0 direttore@ismar.cnr.it CNR-ISMAR CNR-ISMAR jacopo.chiggiato@ismar.cnr.it Jacopo Chiggiato paolo.montagna@cnr.it Paolo Montagna Optics Physical sciences Applied sciences Earth sciences Giorgio Castellan POLYGON ((12.002563476562502 45.54098421805078, 12.123413085937502 44.146739625584985, 14.221801757812502 45.174292524076726, 13.9306640625 45.80199916666154, 12.952880859375002 45.84410779560204, 12.002563476562502 45.54098421805078)) d5e5335a-ae75-40ba-8f43-ac9aca05c92d POLYGON ((12.002563476562502 45.54098421805078, 12.123413085937502 44.146739625584985, 14.221801757812502 45.174292524076726, 13.9306640625 45.80199916666154, 12.952880859375002 45.84410779560204, 12.002563476562502 45.54098421805078)) POLYGON ((12.002563476562502 45.54098421805078, 12.123413085937502 44.146739625584985, 14.221801757812502 45.174292524076726, 13.9306640625 45.80199916666154, 12.952880859375002 45.84410779560204, 12.002563476562502 45.54098421805078)) 12.002563476562502 45.54098421805078, 12.123413085937502 44.146739625584985, 14.221801757812502 45.174292524076726, 13.9306640625 45.80199916666154, 12.952880859375002 45.84410779560204, 12.002563476562502 45.54098421805078 service-account-enrichment 91591 https://api.rohub.org/api/ros/894d3a33-8340-497d-beaf-5b9d85c9bfc7/crate/download/ 2021-12-07 15:44:04.866966+00:00 2025-03-05 01:21:25.016018+00:00 2021-12-07 15:44:04.866966+00:00 Satellite Data on Chlorophyll-a and diffuse attenuation coefficient at 490 nm (Kd490) for the Venice Lagoon application/ld+json https://w3id.org/ro-id/894d3a33-8340-497d-beaf-5b9d85c9bfc7 Satellite data on water clarity in the Venice Lagoon during the COVID 19 lockdown MANUAL Venice absorption coefficient chlorophyll a clarity water earth sciences Nanotechnology Satellite technology Venice Lagoon Venice attenuation coefficient chlorophyll a clarity satellite data water geosciences Venice Lagoon during the COVID 19 lockdown Venice Venice Lagoon diffuse attenuation coefficient satellite data on chlorophyll a satellite data on water clarity Satellite Data on Chlorophyll-a and diffuse attenuation coefficient at 490 nm (Kd490) for the Venice Lagoon Satellite data on water clarity in the Venice Lagoon during the COVID 19 lockdown. https://w3id.org/ro-id/894d3a33-8340-497d-beaf-5b9d85c9bfc7/01ac8fa1-202d-44dc-aeca-189b3b2603cb Venice Castellan, Giorgio. "Satellite data on water clarity in the Venice Lagoon during the COVID 19 lockdown." ROHub. Dec 07 ,2021. https://w3id.org/ro-id/894d3a33-8340-497d-beaf-5b9d85c9bfc7. 29487 https://api.rohub.org/api/resources/4735e2cd-a746-455e-bf0d-02022be56eca/download/ 2021-12-13 15:48:13.309224+00:00 2021-12-13 15:48:13.310234+00:00 Satelite data on Chl-a for the Venice Lagoon application/zip Satelite data on Chl-a for the Venice Lagoon 2021-12-13 15:48:13.309224+00:00 70005 https://api.rohub.org/api/resources/629e9125-130e-4742-b32b-6eaf05fec072/download/ 2021-12-14 08:57:52.941298+00:00 2021-12-14 08:57:52.942495+00:00 image/png Diffuse attenuation coefficient at 490 nm (Kd490) for north Adriatic Sea in 2018 2021-12-14 08:57:52.941298+00:00 23937 https://api.rohub.org/api/resources/982e29d3-e27c-4a2d-ba63-d0edeade9a48/download/ 2021-12-13 15:47:41.772362+00:00 2021-12-13 15:47:41.774296+00:00 Satellite data on Kd490for the Venice Lagoon application/zip Satellite data on Kd490 for the Venice Lagoon 2021-12-13 15:47:41.772362+00:00 Earth sciences published v1 monthly map of PM10 Copernicus Atmosphere Monitoring Service Data Cube Ro country map Ro monthly map map of PM10 PCSS example3@hotmail.com Pepito Bato 0000-0002-8316-3192 UNO-Recoletos npepito@hotmail.com Nieves Pepito 0000-0003-3784-6651 office@man.poznan.pl 025cj6e44 Poznan Supercomputing and Networking Center POINT (38.0 38.0) 38.0 38.0 POINT (38.0 38.0) eb1c7b49-7116-4587-aced-c1a1210cbb1d POINT (38.0 38.0) service-account-enrichment False https://w3id.org/ro-id/9177a694-e747-4d7f-ae7e-87672850e0ec 2021-12-08 22:01:26.136904+00:00 mailto:rpalma@man.poznan.pl 86656 https://api.rohub.org/api/ros/abebc0e7-87b6-4ed5-8a0e-9b71dc30e333/crate/download/ 2021-12-08 21:40:02.447472+00:00 2024-03-05 12:17:25.502621+00:00 2021-12-08 21:40:02.447472+00:00 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified application/ld+json https://w3id.org/ro-id/abebc0e7-87b6-4ed5-8a0e-9b71dc30e333 8th December - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot Copernicus Atmosphere Monitoring Service Data Cube RO December 8th - published v1 MANUAL https://w3id.org/ro-id/abebc0e7-87b6-4ed5-8a0e-9b71dc30e333/df4db37c-7304-430d-b08e-ba41cdc33e9e Anne Foilloux, Nieves Pepito, and Pepito Bato. "Copernicus Atmosphere Monitoring Service Data Cube RO December 8th - published v1." ROHub. Dec 08 ,2021. https://doi.org/10.24424/fehe-jb26. metadata data biblio raw data https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-12-08 21:44:49.477592+00:00 2021-12-08 22:01:19.894769+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-12-08 21:44:49.477592+00:00 Flow to compute monthly map 73394 https://api.rohub.org/api/resources/25e31ee1-9f77-40d0-a4c3-5bef88b9adc3/download/ 2021-12-08 21:44:36.949407+00:00 2021-12-08 22:01:19.428175+00:00 image/png flow-dcro.png 2021-12-08 21:44:36.949407+00:00 This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental. EU_CAMS_SURFACE_PM10_G https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-12-08 21:44:42.801819+00:00 2021-12-08 22:01:19.788776+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-12-08 21:44:42.801819+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-12-08 21:44:46.533341+00:00 2021-12-08 22:01:20.217111+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-12-08 21:44:46.533341+00:00 List of hourly PM10 concentration data for September 1st 2018 over Europe Index of daily PM10 concentration for September 1st 2018 Catch data records sample from 2019 Catch data from Norway https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2021-12-08 21:44:52.711669+00:00 2023-05-16 16:52:12.400121+00:00 https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2021-12-08 21:44:52.711669+00:00 Daily PM10 concentration for 1st September 2018 over Europe Daily PM10 concentration https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2021-12-08 21:44:55.989277+00:00 2021-12-08 22:01:19.992473+00:00 https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2021-12-08 21:44:55.989277+00:00 Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services Nordic e-Infrastructure Collaboration (NeIC) annefou@geo.uio.no Anne Fouilloux neworg1@example.org abcd123 Example Org 1 Earth sciences published v2 monthly map of PM10 Copernicus Atmosphere Monitoring Service Data Cube Ro country map Ro monthly map map of PM10 PCSS example3@hotmail.com Pepito Bato 0000-0002-8316-3192 UNO-Recoletos npepito@hotmail.com Nieves Pepito 0000-0003-3784-6651 office@man.poznan.pl 025cj6e44 Poznan Supercomputing and Networking Center POINT (38.0 38.0) 38.0 38.0 POINT (38.0 38.0) 6aa2b88b-ca50-4d9b-81fb-b18cf3b25d74 POINT (38.0 38.0) service-account-enrichment False https://w3id.org/ro-id/9177a694-e747-4d7f-ae7e-87672850e0ec 2021-12-08 22:04:49.342182+00:00 mailto:rpalma@man.poznan.pl 86622 https://api.rohub.org/api/ros/c737f695-6715-4916-8bef-8fc0ce879760/crate/download/ 2021-12-08 21:40:02.447472+00:00 2024-03-05 12:17:25.629746+00:00 2021-12-08 21:40:02.447472+00:00 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified application/ld+json https://w3id.org/ro-id/c737f695-6715-4916-8bef-8fc0ce879760 8th December - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot Copernicus Atmosphere Monitoring Service Data Cube RO December 8th - published v2 MANUAL https://w3id.org/ro-id/c737f695-6715-4916-8bef-8fc0ce879760/df4db37c-7304-430d-b08e-ba41cdc33e9e Anne Foilloux, Nieves Pepito, and Pepito Bato. "Copernicus Atmosphere Monitoring Service Data Cube RO December 8th - published v2." ROHub. Dec 08 ,2021. http://doi.org/10.23728/b2share.3c82435c669b49fcaa5541b465e055fa. biblio data raw data metadata https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2021-12-08 21:44:55.989277+00:00 2021-12-08 22:04:44.732746+00:00 https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2021-12-08 21:44:55.989277+00:00 Flow to compute monthly map https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-12-08 21:44:42.801819+00:00 2021-12-08 22:04:44.543287+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-12-08 21:44:42.801819+00:00 73394 https://api.rohub.org/api/resources/287efd15-0bd1-474d-88c2-4542e1393d8d/download/ 2021-12-08 21:44:36.949407+00:00 2021-12-08 22:04:44.160524+00:00 image/png flow-dcro.png 2021-12-08 21:44:36.949407+00:00 This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental. EU_CAMS_SURFACE_PM10_G List of hourly PM10 concentration data for September 1st 2018 over Europe Index of daily PM10 concentration for September 1st 2018 https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2021-12-08 21:44:52.711669+00:00 2023-05-16 16:53:21.645987+00:00 https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2021-12-08 21:44:52.711669+00:00 Catch data records sample from 2019 Catch data from Norway Daily PM10 concentration for 1st September 2018 over Europe Daily PM10 concentration https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-12-08 21:44:46.533341+00:00 2021-12-08 22:04:44.869071+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-12-08 21:44:46.533341+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-12-08 21:44:49.477592+00:00 2021-12-08 22:04:44.654574+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-12-08 21:44:49.477592+00:00 Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services Nordic e-Infrastructure Collaboration (NeIC) annefou@geo.uio.no Anne Fouilloux neworg1@example.org abcd123 Example Org 1 Earth sciences 10.13039/501100000781 European Commission published v1 monthly map of PM10 Copernicus Atmosphere Monitoring Service Data Cube Ro country map Ro monthly map map of PM10 PCSS example4@hotmail.com Pepito Bato 0000-0002-8316-3192 UNO-Recoletos npepito@hotmail.com Nieves Pepito 0000-0003-3784-6651 office@man.poznan.pl 025cj6e44 Poznan Supercomputing and Networking Center 101017502 RELIANCE POINT (38.0 38.0) 0a113f7e-5c4d-411e-985e-2d71e8dcbd28 POINT (38.0 38.0) 38.0 38.0 POINT (38.0 38.0) service-account-enrichment False https://w3id.org/ro-id/93ece8d0-3be4-4658-a840-156bda47f612 2021-12-09 15:19:11.307501+00:00 mailto:rpalma@man.poznan.pl 87394 https://api.rohub.org/api/ros/a08ddcb2-ae5f-40ba-b1b6-c64dd2e4d68c/crate/download/ 2021-12-09 15:05:57.255344+00:00 2024-03-05 12:17:25.978567+00:00 2021-12-09 15:05:57.255344+00:00 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified application/ld+json https://w3id.org/ro-id/a08ddcb2-ae5f-40ba-b1b6-c64dd2e4d68c 8th December - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot Copernicus Atmosphere Monitoring Service Data Cube RO December 9th - published v1 MANUAL https://w3id.org/ro-id/a08ddcb2-ae5f-40ba-b1b6-c64dd2e4d68c/ea782618-0dff-4cfa-8604-e121ce29d3cf Anne Foilloux, Nieves Pepito, and Pepito Bato. "Copernicus Atmosphere Monitoring Service Data Cube RO December 9th - published v1." ROHub. Dec 09 ,2021. https://doi.org/10.24424/w44h-8089. metadata data biblio raw data https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-12-09 15:07:51.036076+00:00 2021-12-09 15:19:08.564064+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-12-09 15:07:51.036076+00:00 List of hourly PM10 concentration data for September 1st 2018 over Europe Index of daily PM10 concentration for September 1st 2018 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-12-09 15:07:43.448712+00:00 2021-12-09 15:19:08.515865+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-12-09 15:07:43.448712+00:00 Flow to compute monthly map https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2021-12-09 15:07:55.588569+00:00 2023-05-16 16:54:04.603729+00:00 https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2021-12-09 15:07:55.588569+00:00 Daily PM10 concentration for 1st September 2018 over Europe Daily PM10 concentration 73394 https://api.rohub.org/api/resources/7733e68b-7b14-45b8-96ef-b0ff1e3b6a45/download/ 2021-12-09 15:07:22.892363+00:00 2021-12-09 15:19:08.338406+00:00 image/png flow-dcro.png 2021-12-09 15:07:22.892363+00:00 Catch data records sample from 2019 Catch data from Norway This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental. EU_CAMS_SURFACE_PM10_G https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-12-09 15:07:47.272247+00:00 2021-12-09 15:19:08.713366+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-12-09 15:07:47.272247+00:00 Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2021-12-09 15:07:59.055468+00:00 2021-12-09 15:19:08.607528+00:00 https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2021-12-09 15:07:59.055468+00:00 Nordic e-Infrastructure Collaboration (NeIC) annefou@geo.uio.no Anne Fouilloux neworg2@example.org abcd123 Example Org 2 Earth sciences 10.13039/501100000781 European Commission published v2 monthly map of PM10 Copernicus Atmosphere Monitoring Service Data Cube Ro country map Ro monthly map map of PM10 PCSS example4@hotmail.com Pepito Bato 0000-0002-8316-3192 UNO-Recoletos npepito@hotmail.com Nieves Pepito 0000-0003-3784-6651 office@man.poznan.pl 025cj6e44 Poznan Supercomputing and Networking Center 101017502 RELIANCE 38.0 38.0 POINT (38.0 38.0) 86a33d62-4541-495f-a640-2b60e0394266 POINT (38.0 38.0) service-account-enrichment False https://w3id.org/ro-id/93ece8d0-3be4-4658-a840-156bda47f612 2021-12-09 15:20:23.441762+00:00 mailto:rpalma@man.poznan.pl 87383 https://api.rohub.org/api/ros/57cf76e1-2179-4650-b48b-b5990dca86c1/crate/download/ 2021-12-09 15:05:57.255344+00:00 2024-03-05 12:17:26.248043+00:00 2021-12-09 15:05:57.255344+00:00 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified application/ld+json https://w3id.org/ro-id/57cf76e1-2179-4650-b48b-b5990dca86c1 8th December - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot Copernicus Atmosphere Monitoring Service Data Cube RO December 9th - published v2 MANUAL https://w3id.org/ro-id/57cf76e1-2179-4650-b48b-b5990dca86c1/ea782618-0dff-4cfa-8604-e121ce29d3cf Anne Foilloux, Nieves Pepito, and Pepito Bato. "Copernicus Atmosphere Monitoring Service Data Cube RO December 9th - published v2." ROHub. Dec 09 ,2021. https://doi.org/10.24424/yptf-km76. biblio metadata raw data data List of hourly PM10 concentration data for September 1st 2018 over Europe Index of daily PM10 concentration for September 1st 2018 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-12-09 15:07:51.036076+00:00 2021-12-09 15:20:20.634446+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-12-09 15:07:51.036076+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-12-09 15:07:47.272247+00:00 2021-12-09 15:20:20.738000+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-12-09 15:07:47.272247+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-12-09 15:07:43.448712+00:00 2021-12-09 15:20:20.597858+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-12-09 15:07:43.448712+00:00 Flow to compute monthly map Daily PM10 concentration for 1st September 2018 over Europe Daily PM10 concentration https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2021-12-09 15:07:59.055468+00:00 2021-12-09 15:20:20.669306+00:00 https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2021-12-09 15:07:59.055468+00:00 73394 https://api.rohub.org/api/resources/7bfd4974-4bf8-4922-ae40-36a2ca9ef7fe/download/ 2021-12-09 15:07:22.892363+00:00 2021-12-09 15:20:20.444066+00:00 image/png flow-dcro.png 2021-12-09 15:07:22.892363+00:00 Catch data records sample from 2019 Catch data from Norway This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental. EU_CAMS_SURFACE_PM10_G https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2021-12-09 15:07:55.588569+00:00 2023-05-16 16:54:33.185954+00:00 https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2021-12-09 15:07:55.588569+00:00 Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services POINT (38.0 38.0) Nordic e-Infrastructure Collaboration (NeIC) annefou@geo.uio.no Anne Fouilloux neworg2@example.org abcd123 Example Org 2 Earth sciences 10.13039/501100000781 European Commission published v2 monthly map of PM10 Copernicus Atmosphere Monitoring Service Data Cube Ro country map Ro monthly map map of PM10 PCSS example4@hotmail.com Pepito Bato 0000-0002-8316-3192 UNO-Recoletos npepito@hotmail.com Nieves Pepito 0000-0003-3784-6651 office@man.poznan.pl 025cj6e44 Poznan Supercomputing and Networking Center 101017502 RELIANCE 56289eeb-73b2-4076-852c-6bf6fee8f381 POINT (38.0 38.0) 38.0 38.0 POINT (38.0 38.0) service-account-enrichment False https://w3id.org/ro-id/93ece8d0-3be4-4658-a840-156bda47f612 2021-12-09 15:24:39.649872+00:00 mailto:rpalma@man.poznan.pl 87396 https://api.rohub.org/api/ros/6440c36b-44c8-48c5-9a2a-a3c47de70c8a/crate/download/ 2021-12-09 15:05:57.255344+00:00 2024-03-05 12:17:26.121572+00:00 2021-12-09 15:05:57.255344+00:00 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified application/ld+json https://w3id.org/ro-id/6440c36b-44c8-48c5-9a2a-a3c47de70c8a 8th December - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot Copernicus Atmosphere Monitoring Service Data Cube RO December 9th - published v2 MANUAL https://w3id.org/ro-id/6440c36b-44c8-48c5-9a2a-a3c47de70c8a/ea782618-0dff-4cfa-8604-e121ce29d3cf Anne Foilloux, Nieves Pepito, and Pepito Bato. "Copernicus Atmosphere Monitoring Service Data Cube RO December 9th - published v2." ROHub. Dec 09 ,2021. https://doi.org/10.24424/80ze-vx74. biblio data raw data metadata List of hourly PM10 concentration data for September 1st 2018 over Europe Index of daily PM10 concentration for September 1st 2018 https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2021-12-09 15:07:55.588569+00:00 2023-05-16 16:55:20.098335+00:00 https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2021-12-09 15:07:55.588569+00:00 Flow to compute monthly map Daily PM10 concentration for 1st September 2018 over Europe Daily PM10 concentration https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2021-12-09 15:07:59.055468+00:00 2021-12-09 15:24:36.452503+00:00 https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2021-12-09 15:07:59.055468+00:00 Catch data records sample from 2019 Catch data from Norway This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental. EU_CAMS_SURFACE_PM10_G https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-12-09 15:07:51.036076+00:00 2021-12-09 15:24:36.409139+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2021-12-09 15:07:51.036076+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-12-09 15:07:47.272247+00:00 2021-12-09 15:24:36.536458+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2021-12-09 15:07:47.272247+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-12-09 15:07:43.448712+00:00 2021-12-09 15:24:36.359834+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2021-12-09 15:07:43.448712+00:00 Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services 73394 https://api.rohub.org/api/resources/fe10d6ac-bc5f-4f26-a4ff-2b617fd1b443/download/ 2021-12-09 15:07:22.892363+00:00 2021-12-09 15:24:36.183105+00:00 image/png flow-dcro.png 2021-12-09 15:07:22.892363+00:00 POINT (38.0 38.0) Nordic e-Infrastructure Collaboration (NeIC) annefou@geo.uio.no Anne Fouilloux neworg2@example.org abcd123 Example Org 2 Earth sciences Fundamental Research Funds for Central Universities European Space Agency (ESA) and Ministry of Science and Technology (MOST), China Natural Science Foundation of China Italian Ministry of University aerospace engineering data at Changbaishan Changbaishan Volcano property of JAXA raw data property soil China North Korea velocity ground velocity file raster file raster Changbaishan JAXA Magma Migration North Korea Interior China Japan INGV cristiano.tolomei@ingv.it Tolomei, Cristiano 0000-0001-7378-0712 - Pianeta Dinamico 42071453 - 58029 Dragon 5 N2001027 - POLYGON ((127.82938662 41.702706825, 128.35894877 41.702706825, 128.35894877 42.1858125, 127.82938662 42.1858125, 127.82938662 41.702706825)) 127.82938662 41.702706825, 128.35894877 41.702706825, 128.35894877 42.1858125, 127.82938662 42.1858125, 127.82938662 41.702706825 dea23d92-11ac-4e7b-87c3-8465437d0bfa POLYGON ((127.82938662 41.702706825, 128.35894877 41.702706825, 128.35894877 42.1858125, 127.82938662 42.1858125, 127.82938662 41.702706825)) service-account-enrichment False https://w3id.org/ro-id/677cf91e-880d-485a-b027-30ba523dac73 2021-12-13 17:51:45.412526+00:00 https://orcid.org/0000-0002-2983-045X 5016613 https://api.rohub.org/api/ros/61bceafe-5b48-4548-8caf-4142153b1b1b/crate/download/ 2021-12-13 17:49:07.069454+00:00 2024-03-05 12:19:21.893221+00:00 2021-12-13 17:49:07.069454+00:00 This Research Object contains the raster file of the mean ground velocity at the Changbaishan Volcano (China/North Korea) from ALOS-2 satellite data during 2018-2020. Find more on processing and results in the related paper: 'Upward Magma Migration within the Multi-level Plumbing System of the Changbaishan Volcano (China/North Korea) Revealed by the Modeling of 2018-2020 SAR Data' by E. Trasatti, C. Tolomei, L. Wei, G. Ventura. DOI: 10.3389/feart.2021.741287 . Raw data property of JAXA (Japan). application/ld+json https://w3id.org/ro-id/61bceafe-5b48-4548-8caf-4142153b1b1b Ground Velocities from ALOS-2 Data of the Changbaishan Volcanic Area (China/North Korea) - snapshot Mean ground velocities from ALOS-2 data at Changbaishan volcano (China/North Korea) during 2018-2020 MANUAL https://w3id.org/ro-id/61bceafe-5b48-4548-8caf-4142153b1b1b/3a69827c-fd1c-4765-a147-5d25c8b8cd38 Trasatti, Elisa, and Tolomei, Cristiano. "Mean ground velocities from ALOS-2 data at Changbaishan volcano (China/North Korea) during 2018-2020." ROHub. Dec 13 ,2021. https://doi.org/10.24424/vfp6-r230. metadata raw data biblio data 978596 https://api.rohub.org/api/resources/17d678c6-4274-4475-9fb0-bc6fc00199ae/download/ 2021-12-13 17:49:37.806878+00:00 2021-12-13 17:51:43.786630+00:00 image/png sketch.png 2021-12-13 17:49:37.806878+00:00 Mean ground velocities data 10222 https://api.rohub.org/api/resources/2ca3451c-643c-40de-b793-0280cd331831/download/ 2021-12-13 17:49:41.744694+00:00 2021-12-13 17:51:41.042882+00:00 application/vnd.openxmlformats-officedocument.spreadsheetml.sheet List_of_images.xlsx 2021-12-13 17:49:41.744694+00:00 460884 https://api.rohub.org/api/resources/3e9f5ea7-ec5b-4f90-b40e-8d7a6335855b/download/ 2021-12-13 17:49:49.252182+00:00 2021-12-13 17:51:42.921270+00:00 image/png connection_graph.png 2021-12-13 17:49:49.252182+00:00 23598522 https://api.rohub.org/api/resources/6931dcee-ff02-47a4-bb3c-ac38444d73b3/download/ 2021-12-13 17:49:28.816730+00:00 2021-12-13 17:51:40.107321+00:00 image/tiff Changbaishan_ALOS2_asc_poly1.tif 2021-12-13 17:49:28.816730+00:00 https://www.frontiersin.org/articles/10.3389/feart.2021.741287/abstract 2021-12-13 17:49:53.455227+00:00 2021-12-13 17:51:39.306605+00:00 https://www.frontiersin.org/articles/10.3389/feart.2021.741287/abstract 2021-12-13 17:49:53.455227+00:00 List of the ALOS-2 images used in the processing. Paper published in Frontiers Earth Science with data and modelling link to paper 4891 https://api.rohub.org/api/resources/cfa05a53-9836-4c05-8bd5-b05a3a1ffe03/download/ 2021-12-13 17:49:45.522927+00:00 2021-12-13 17:51:41.997249+00:00 application/rtf readme.rtf 2021-12-13 17:49:45.522927+00:00 Details on the data Details on the data Map of the mean ground velocities POLYGON ((127.82938662 41.702706825, 128.35894877 41.702706825, 128.35894877 42.1858125, 127.82938662 42.1858125, 127.82938662 41.702706825)) Applied sciences service-account-enrichment 61063 https://api.rohub.org/api/ros/b5b86f8e-5c07-4b43-9b21-6df3bb6ebe72/crate/download/ 2022-01-11 10:37:21.504328+00:00 2025-03-05 01:19:47.813154+00:00 2022-01-11 10:37:21.504328+00:00 Street Spectra is a citizen science project to map and characterize public lighting sources. Volunteers use a low cost diffraction grating on top of their smartphones’ camera to take pictures of the street lamps and their emission spectra. application/ld+json https://w3id.org/ro-id/b5b86f8e-5c07-4b43-9b21-6df3bb6ebe72 Street Spectra MANUAL cost diffraction grating digital emission spectrum image lamppost lighting smartphone spectrum volunteer earth sciences Photography Wireless technology citizen science cost diffraction grating emission spectrum lighting smartphone volunteer engineering citizen science project cost diffraction grating lighting source pictures of the street lamps street spectra Camera to take pictures of the street lamps and their emission spectra. Street Spectra is a citizen science project to map and characterize public lighting sources. Volunteers use a low cost diffraction grating on top of their smartphones? photography project, ACTION. "Street Spectra." ROHub. Jan 11 ,2022. https://w3id.org/ro-id/b5b86f8e-5c07-4b43-9b21-6df3bb6ebe72. Datasets Presentations Publications Software Documents https://five.epicollect.net/project/action-street-spectra 2022-01-11 10:51:00.637210+00:00 2022-01-11 10:51:00.637736+00:00 Application in Epicollect to collect data Data Collector in Epicollect5 2022-01-11 10:51:00.637210+00:00 https://doi.org/10.5281/zenodo.3885566 2022-01-11 10:47:28.165693+00:00 2022-01-11 10:47:28.166269+00:00 This document describes the different templates that are going to be developed in ACTION for helping pilots to export/use external platforms. Also, a new tool to create Data Management Plan documents based on a questionnaire will be described. Finally, a mini guide has been included to help users to create a CS project using the external platforms Epicollect and Zooniverse. D4.2 Lifecycle-aware citizen science templates 2022-01-11 10:47:28.165693+00:00 51542 https://api.rohub.org/api/resources/24952a29-d009-4c32-a16c-48ef780d8d5b/download/ 2022-01-11 10:38:11.122782+00:00 2022-01-11 10:38:11.124960+00:00 image/png ro-street.png 2022-01-11 10:38:11.122782+00:00 https://www.zooniverse.org/projects/actionprojecteu/street-spectra 2022-01-11 10:56:05.208335+00:00 2022-01-11 10:56:05.209024+00:00 Street Spectra - Zooniverse 2022-01-11 10:56:05.208335+00:00 https://doi.org/10.5281/zenodo.4041469 2022-01-11 10:45:36.637238+00:00 2022-01-11 10:45:36.637879+00:00 This lesson plan is to be used in the classroom of 12 and 13 years old students and aims to educate its users on the topic of light pollution. Aside from gaining awareness, the students will be introduced to the Street Spectra citizen science project through which they will learn how to analyze and classify sources of light pollution contributing to science as a citizen scientist. https://streetspectra.actionproject.eu/ These pages will discuss: artificial light at night in general, different types of light pollution, their negative effects as well as the most efficient way to install lighting sources in such a way that any negative impact is minimized. The Street Spectra project with its objectives as well as its relationship to citizen science are explained during the course. Theory is accompanied with suggested activities adapted to the level of the students. With this unit the authors intend to gather contents that can be implemented in the classroom, and which can serve as a guide so that both students and teachers can participate in this citizen science project. In order for a citizen science project to grow the input of researchers, disseminators and a wide range of volunteers are needed. The participation of the students and teachers will directly help the study of light pollution. Street Spectra - Teaching Materials 2022-01-11 10:45:36.637238+00:00 https://doi.org/10.5281/zenodo.3696492 2022-01-11 10:48:49.624858+00:00 2022-01-11 10:48:49.625481+00:00 This document explains all the steps to obtain the spectra of street lights, how to determine their nature, and also how to contribute with this information to the StreetSpectra citizen science project. The first sections are devoted to introduce the StreetSpectra project, and also the light pollution (LP) problem. We have also included some of the science basics (LP and simple physics of spectra). Tutorial: to identify the spectra of common street lamps 2022-01-11 10:48:49.624858+00:00 ACTION project Earth sciences service-account-enrichment 12545 https://api.rohub.org/api/ros/959fa202-b251-4fcd-8d5f-8ed83740fe43/crate/download/ 2022-01-12 19:56:50.046268+00:00 2025-03-05 01:23:32.908133+00:00 2022-01-12 19:56:50.046268+00:00 Norway is the land of fjords, trolls and – electric cars. By actively promoting the purchase of electric cars, the Norwegian government is aiming at protecting the environment and not least improving air quality, especially in urban areas. Air quality is still a reason for concern in many European countries, including the Nordic countries. Not many people are aware of this fact, and this is where the Norwegian pilot of the ACTION project comes in. The pilot gives high school students in Oslo and the larger Oslo area the opportunity to design and carry out their own air quality projects, using an off-the-shelf air quality sensor platform. The aim is to create awareness about the sources of air pollution, make the students think of ways to reduce both emission and exposure and teach them scientific working methods. We use the Nova SDS011 sensor for measuring PM2.5 and PM10 that is transmitting data to an Arduino board. The data can be obtained through an SD card. application/ld+json https://w3id.org/ro-id/959fa202-b251-4fcd-8d5f-8ed83740fe43 STUDENTS, AIR POLLUTION AND DIY SENSING MANUAL Oslo PM10 air pollution air quality awareness electric car emission high school information opportunity pilot project sensor student environmental sciences Air pollution High schools Students Oslo air pollution air quality electric car high school sensor student geosciences action project air quality project high school student purchase of electric cars sensor platform By actively promoting the purchase of electric cars, the Norwegian government is aiming at protecting the environment and not least improving air quality, especially in urban areas. The aim is to create awareness about the sources of air pollution, make the students think of ways to reduce both emission and exposure and teach them scientific working methods. The pilot gives high school students in Oslo and the larger Oslo area the opportunity to design and carry out their own air quality projects, using an off-the-shelf air quality sensor platform. ecology Norway Oslo project, ACTION. "STUDENTS, AIR POLLUTION AND DIY SENSING." ROHub. Jan 12 ,2022. https://w3id.org/ro-id/959fa202-b251-4fcd-8d5f-8ed83740fe43. Presentations Publications Datasets Software https://doi.org/10.5281/zenodo.3730478 2022-01-12 20:54:02.708585+00:00 2022-01-12 20:54:02.709862+00:00 Forskningsprosjekt luftforurensning Forskningsprosjekt luftforurensning 2022-01-12 20:54:02.708585+00:00 https://doi.org/10.5281/zenodo.3737608 2022-01-12 20:52:27.138627+00:00 2022-01-12 20:52:27.139413+00:00 This poster has been created by students of the Ullern Upper Secondary School, located in Oslo, Norway. Systematiske målinger: Vi ønsker å finne ut om det akustiske miljøet har effekt på luftkvalitetens endringer 2022-01-12 20:52:27.138627+00:00 https://doi.org/10.5281/zenodo.3737759 2022-01-12 20:48:05.309120+00:00 2022-01-12 20:48:05.309858+00:00 Measurements taken by a DIY sensor designed by the project air:bit (http://airbit.uit.no/#english). Measurements were taken by students of the school Lambertseter VGS, located in the district of Nordstrand in Oslo, Norway. Lambertseter VGS 2022-01-12 20:48:05.309120+00:00 https://doi.org/10.5281/zenodo.3737635 2022-01-12 20:51:50.182916+00:00 2022-01-12 20:51:50.183388+00:00 This poster has been created by students of the Ullern Upper Secondary School, located in Oslo, Norway. Trafikkforurensing: Trafikkerte områder er mer utsatt for forurensing 2022-01-12 20:51:50.182916+00:00 https://doi.org/10.5281/zenodo.3956481 2022-01-12 20:50:39.286485+00:00 2022-01-12 20:50:39.287215+00:00 Firmware of an Arduino board integrated with  a Nova SDS011 sensor for measuring PM2.5 and PM10. The data can be obtained through an SD card. ARDUINO_UNO_WITH_NOVASDS011_Firmware 2022-01-12 20:50:39.286485+00:00 https://doi.org/10.5281/zenodo.3730457 2022-01-12 20:54:42.876507+00:00 2022-01-12 20:54:42.877542+00:00 This deliverable serves as a handbook for air quality projects in high schools. It contains information about the ACTION air quality pilot in high schools, tips and lessons learned as well as material that has been used and created within the high school projects. Tutorial for air quality projects in high schools 2022-01-12 20:54:42.876507+00:00 https://doi.org/10.5281/zenodo.3737799 2022-01-12 20:49:30.350970+00:00 2022-01-12 20:49:30.352122+00:00 Measurements taken by a DIY sensor (Sensor 2) designed by the project air:bit (http://airbit.uit.no/#english). Measurements were taken by students of the school Lambertseter VGS, located in the district of Nordstrand in Oslo, Norway. Lambertseter VGS 2022-01-12 20:49:30.350970+00:00 ACTION project Applied sciences service-account-enrichment 13797 https://api.rohub.org/api/ros/370d93ab-df01-46de-982e-0ef74b3acf8a/crate/download/ 2022-01-12 20:56:44.324225+00:00 2025-03-05 02:45:35.385678+00:00 2022-01-12 20:56:44.324225+00:00 The Noise Maps project focused on deploying a citizen science process in the neighborhoods of Sagrada Familia and the Raval (Barcelona) to address the challenge of noise pollution, a serious problem related to health problems (lack of sleep, psychological ailments, cardiovascular disease, risk of higher stroke) and negative social effects (weakness of social cohesion and coexistence, reduced quality of life, loss of cultural diversity). Noise pollution was an urgent problem in the pilot areas, with active community groups on the lookout for a solution to help improve their living conditions. application/ld+json https://w3id.org/ro-id/370d93ab-df01-46de-982e-0ef74b3acf8a NOISE MAPS MANUAL Sagrada Família ailment cardiovascular disease challenge coexistence community health problem noise pollution problem project quality of life scout earth sciences Church Environmental pollution Psychology Science and technology Social condition Noise Maps cardiovascular disease challenge health problem noise pollution problem quality of life geosciences Noise Maps project challenge of noise pollution problem in the pilot area psychological ailment urgent problem NOISE MAPS. The Noise Maps project focused on deploying a citizen science process in the neighborhoods of Sagrada Familia and the Raval (Barcelona) to address the challenge of noise pollution, a serious problem related to health problems (lack of sleep, psychological ailments, cardiovascular disease, risk of higher stroke) and negative social effects (weakness of social cohesion and coexistence, reduced quality of life, loss of cultural diversity) Noise pollution was an urgent problem in the pilot areas, with active community groups on the lookout for a solution to help improve their living conditions. medicine Barcelona project, ACTION. "NOISE MAPS." ROHub. Jan 12 ,2022. https://w3id.org/ro-id/370d93ab-df01-46de-982e-0ef74b3acf8a. data Audios Datasets raw data Software Additional_Information Presentations http://www.bitlab.cat/en/projectes/noise-maps/ 2022-01-12 21:10:54.457704+00:00 2022-01-12 21:10:54.458641+00:00 NoiseMaps website 2022-01-12 21:10:54.457704+00:00 https://www.instamaps.cat/visor.html?businessid=1975f976dff9d780c23a1db01eb37ec3 2022-01-12 21:10:30.483090+00:00 2022-01-12 21:10:30.483591+00:00 Platform of the Geographical Institute of Catalunya text/html Instmaps website 2022-01-12 21:10:30.483090+00:00 https://dashboards.dataportal.actionproject.eu/ 2022-01-12 21:09:07.283838+00:00 2022-01-12 21:09:07.284429+00:00 Dashboards created in Grafana to visualze data Noise Maps Dashboards 2022-01-12 21:09:07.283838+00:00 https://freesound.org/people/bitlab_coop/packs/30131/ 2022-01-12 21:04:23.581144+00:00 2022-01-12 21:04:23.581715+00:00 Collection of ambient urban ourdoors audios from Raval Raval May2020 2022-01-12 21:04:23.581144+00:00 https://doi.org/10.5281/zenodo.4059533 2022-01-12 21:05:06.768056+00:00 2022-01-12 21:05:06.769024+00:00 The Noise Maps project focused on deploying a citizen science process in the Barcelona neighborhoods of Sagrada Familia and the Raval to address the challenge of noise pollution. The sound data was generated between May and September 2020. Noise Maps ACTION pilot data 2020 2022-01-12 21:05:06.768056+00:00 https://github.com/pzinemanas/AudioMoth-Firmware-SPL 2022-01-12 21:01:13.650377+00:00 2022-01-12 21:01:13.650871+00:00 This repository contains an AudioMoth firmware adaptation to calculate the Sound Pressure Level (SPL). This is based on the 1.3.0 version of AudioMoth firmware (published on AudioMoth-Project and AudioMoth-Firmware-Basic). We include the SPL library (src/spl.c and inc/spl.h) that implement all the functions related to the SPL estimation. AudioMoth-Firmware-SPL 2022-01-12 21:01:13.650377+00:00 https://doi.org/10.5281/zenodo.4068095 2022-01-12 21:11:57.606752+00:00 2022-01-12 21:11:57.607269+00:00 This presentation will help ACTION pilots to create their own dashboards Data visualization with Grafana 2022-01-12 21:11:57.606752+00:00 https://ars.electronica.art/keplersgardens/en/sonic-heritage/ 2022-01-12 21:13:10.635968+00:00 2022-01-12 21:13:10.636470+00:00 Results were presented in the ArsElectronica  2020 congress ArsElectronica 2020 2022-01-12 21:13:10.635968+00:00 ACTION project Applied sciences service-account-enrichment 13653 https://api.rohub.org/api/ros/4776fc21-01a3-4806-b248-70a577cbc6b0/crate/download/ 2022-01-12 21:39:57.720721+00:00 2025-03-05 01:19:11.360337+00:00 2022-01-12 21:39:57.720721+00:00 The Sonic Kayak system is a low cost open hardware for gathering and mapping fine-scale marine environmental data, which has not been previously possible to obtain. Data is sonified through an onboard speaker allowing paddlers to seek out areas of interest and gain real time feedback of the data. At the beginning of the project, the system included underwater temperature sensors and a hydrophone for measuring underwater sound, each recording data every second with GPS, time and date. Working with ACTION, two new environmental sensors have been designed and integrated into the existing system (turbidity and air quality). New data have been gathered and citizens have been engaged in two online citizen science style surveys. In the first one people could try out 4 different data sonification approaches and see which was the most straightforward for understanding the underlying environmental data, and also give their preferences on which sounds they liked the best. In the second one, feedback on the pilot activities were gathered. application/ld+json https://w3id.org/ro-id/4776fc21-01a3-4806-b248-70a577cbc6b0 SONIC KAYAKS MANUAL canoeist citizen data feedback hydrophone information preference real time sensor sonification study temperature earth sciences Canoeing Kayaking data feedback hydrophone real time sensor sonification survey life sciences real time feedback recording data sonification approach style survey temperature sensor Data is sonified through an onboard speaker allowing paddlers to seek out areas of interest and gain real time feedback of the data. In the first one people could try out 4 different data sonification approaches and see which was the most straightforward for understanding the underlying environmental data, and also give their preferences on which sounds they liked the best. The Sonic Kayak system is a low cost open hardware for gathering and mapping fine-scale marine environmental data, which has not been previously possible to obtain. computer science scientific terms technical terminology project, ACTION. "SONIC KAYAKS." ROHub. Jan 12 ,2022. https://w3id.org/ro-id/4776fc21-01a3-4806-b248-70a577cbc6b0. Additional_Information Publications Software Video Datasets https://fo.am/blog/2020/08/17/sonic-kayak-update-new-sensors-sonifications-and-visualisations/ 2022-01-12 21:45:23.695160+00:00 2022-01-12 21:45:23.695860+00:00 This post is to let you know about the changes we've made and new things available within the project, and to call for your feedback and thoughts via the survey at the end. Sonic Kayak update - new sensors, sonifications, and visualisations 2022-01-12 21:45:23.695160+00:00 https://github.com/fo-am/sonic-kayaks 2022-01-12 21:41:03.488190+00:00 2022-01-12 21:41:03.488763+00:00 Originally based on the Sonic Bikes system, a Raspberry Pi based citizen science project where kayaks become musical & scientific instruments for investigating the marine world. Device Firmware 2022-01-12 21:41:03.488190+00:00 https://fo.am/blog/2020/06/30/sonic-kayak-environmental-data-sonification/ 2022-01-12 21:44:54.129696+00:00 2022-01-12 21:44:54.130248+00:00 Sonic Kayaks are rigged with sensors, both underwater (temperature, sound, and turbidity) and above water (air pollution). As the kayaker paddles around, the sensors pick up changes in the environment, and these are played to the kayaker in real time through an on-board speaker. Environmental Data Sonification 2022-01-12 21:44:54.129696+00:00 https://doi.org/10.5281/zenodo.4041588 2022-01-12 21:43:21.850780+00:00 2022-01-12 21:43:21.851256+00:00 These data sets are the result of five trips using Sonic Kayaks to collect data as part of the ACTION Project. The sampling was carried out in the Penryn river, around Falmouth docks and the Helford estuary. A variety of sensors were used: Sonic Kayaks geolocated air pollution, water turbidity, temperature and hydrophone analysis 2022-01-12 21:43:21.850780+00:00 https://fo.am/blog/2020/05/05/sonic-kayak-progress-new-pollution-sensors-for-citizen-science/ 2022-01-12 21:49:05.158199+00:00 2022-01-12 21:49:05.158808+00:00 Post that describes the device Sonic Kayak progress – new pollution sensors for citizen science 2022-01-12 21:49:05.158199+00:00 https://www.flickr.com/photos/foam/albums/72157715979200366 2022-01-12 21:44:11.524385+00:00 2022-01-12 21:44:11.525013+00:00 Collection of maps based on the measurements taken by devices Observations taken by citizens represented on a Map 2022-01-12 21:44:11.524385+00:00 https://magpi.raspberrypi.com/issues/97/pdf 2022-01-12 21:42:35.214419+00:00 2022-01-12 21:42:35.215144+00:00 Magizine of Rasberry Pi projects. It includes an article about Sonic Kayacs The MagPi - Issue 97 2022-01-12 21:42:35.214419+00:00 https://www.youtube.com/watch?v=puLXKj1AVAk 2022-01-12 21:49:38.295745+00:00 2022-01-12 21:49:38.296142+00:00 Sonic Kayaks - citizen science in the marine environment for the ACTION project 2022-01-12 21:49:38.295745+00:00 ACTION project Applied sciences service-account-enrichment 8699 https://api.rohub.org/api/ros/b7601048-d964-4c6f-92ac-f6956817dd44/crate/download/ 2022-01-12 23:11:01.694528+00:00 2025-03-05 00:55:14.849586+00:00 2022-01-12 23:11:01.694528+00:00 The aim of the project was to to understand and map the use of pesticides and fertilizers in the context of home farming and gardening. Simultaneously, it aimed to disseminate information on the topic with the final aim of reducing the use of pesticides and fertilizers. application/ld+json https://w3id.org/ro-id/b7601048-d964-4c6f-92ac-f6956817dd44 IN MY BACKYARD MANUAL backyard context farming fertiliser horticulture information pesticide project purpose subject use earth sciences Agriculture Fertiliser aim farming fertilizer gardening pesticide project topic aeronautics aim of the project fertilizers in the context final aim home farming use of pesticide IN MY BACKYARD. Simultaneously, it aimed to disseminate information on the topic with the final aim of reducing the use of pesticides and fertilizers. The aim of the project was to to understand and map the use of pesticides and fertilizers in the context of home farming and gardening. agriculture project, ACTION. "IN MY BACKYARD." ROHub. Jan 12 ,2022. https://w3id.org/ro-id/b7601048-d964-4c6f-92ac-f6956817dd44. Publications Datasets Presentations https://doi.org/10.5281/zenodo.4081585 2022-01-12 23:13:53.593108+00:00 2022-01-12 23:13:53.593689+00:00 Description of project, process, take aways and impact. Project reflections and take aways 2022-01-12 23:13:53.593108+00:00 https://doi.org/10.5281/zenodo.4081597 2022-01-12 23:14:20.032977+00:00 2022-01-12 23:14:20.033714+00:00 Project Final Report Project Final Report 2022-01-12 23:14:20.032977+00:00 https://doi.org/10.5281/zenodo.4081778 2022-01-12 23:12:03.296651+00:00 2022-01-12 23:12:03.297278+00:00 In My Backyard: On-Site Survey Responses Raw Dataset On-Site Survey Responses Raw Dataset 2022-01-12 23:12:03.296651+00:00 https://doi.org/10.5281/zenodo.4081770 2022-01-12 23:12:48.624112+00:00 2022-01-12 23:12:48.624923+00:00 In My Backyard is a citizen science project promoted by Rio Neiva – Environmental NGO and its partner CEA – Municipal Centre for Environmental Education, both based in Esposende, Portugal. It was funded through the ACTION project. In My Backyard aimed to understand the use of harmful pesticides and fertilizers in home farming and gardening and uncovering sustainable alternatives practiced within domestic backyards. Data Analysis Report 2022-01-12 23:12:48.624112+00:00 https://doi.org/10.5281/zenodo.4081606 2022-01-12 23:13:27.546138+00:00 2022-01-12 23:13:27.546890+00:00 Project key insights - Presentation at EU Week of Regions and Cities, 8th October, Session Citizens safeguarding the environment - https://europa.eu/regions-and-cities/programme/sessions/1451_en Key Insights 2022-01-12 23:13:27.546138+00:00 ACTION project Applied sciences service-account-enrichment 8966 https://api.rohub.org/api/ros/7f2a62c1-21cb-42b1-875f-e7d2d19873c8/crate/download/ 2022-01-12 23:15:44.728087+00:00 2025-03-05 01:27:07.174680+00:00 2022-01-12 23:15:44.728087+00:00 The Po Valley in Northern Italy has one of the worst air qualities in Europe, with many of its cities regularly surpassing the threshold levels for PM concentrations considered safe for human health. Luckily, trees can play a role in tackling this problem: studies all over the world are demonstrating the ability of trees in capturing PM, but evidence is needed at the local level. application/ld+json https://w3id.org/ro-id/7f2a62c1-21cb-42b1-875f-e7d2d19873c8 WOW NATURE MANUAL Europe Northern Italy air quality city evidence hanger health prime minister problem safe study threshold level trees wow earth sciences Air pollution Arrest Executive (government) Government Ministers (government) Europe Po Valley air quality evidence study threshold level tree aeronautics Po Valley in Northern Italy ability of trees demonstrate the ability worst air qualities wow nature Luckily, trees can play a role in tackling this problem: studies all over the world are demonstrating the ability of trees in capturing PM, but evidence is needed at the local level. The Po Valley in Northern Italy has one of the worst air qualities in Europe, with many of its cities regularly surpassing the threshold levels for PM concentrations considered safe for human health. WOW NATURE. Europe Northern Italy project, ACTION. "WOW NATURE." ROHub. Jan 12 ,2022. https://w3id.org/ro-id/7f2a62c1-21cb-42b1-875f-e7d2d19873c8. Publications Presentations Datasets https://doi.org/10.5281/zenodo.5236660 2022-01-12 23:19:02.899248+00:00 2022-01-12 23:19:02.899697+00:00 Air pollution Device Measurements [\"pm1\",\"pm2p5\",\"pm4\",\"pm10\",\"humidity\"] WOW Nature - Bosco del ponte del Quarelo 2022-01-12 23:19:02.899248+00:00 https://zenodo.org/record/5236644 2022-01-12 23:16:42.817433+00:00 2022-01-12 23:16:42.818218+00:00 Air pollution Device Measurements [\"pm1\",\"pm2p5\",\"pm4\",\"pm10\",\"humidity\"] WOW Nature - Bosco di Prasaccon 2022-01-12 23:16:42.817433+00:00 https://doi.org/10.5281/zenodo.5842495 2022-01-12 23:19:37.582385+00:00 2022-01-12 23:19:37.583025+00:00 Final presentation of Wow Nature Wow Nature - Final Presentation 2022-01-12 23:19:37.582385+00:00 https://doi.org/10.5281/zenodo.5842501 2022-01-12 23:20:29.569248+00:00 2022-01-12 23:20:29.569658+00:00 This report summarizes the aims, design, implementation, and results of the WOWNATURE project, a project developed in the context of the first ACTION open call, i.e., a call for citizen science projects related to pollution funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824603. The project aimed to measure the air pollution mitigation capacity of urban and peri-urban forests by using innovative sensors and by engaging citizens throughout the process (i.e., experiment design, safekeeping of sensors, and dissemination of results) with the support of the WOWnature web-based platform, thus strengthening the argument in their favour as an effective policy to tackle air pollution. WOW Nature - Final Report 2022-01-12 23:20:29.569248+00:00 https://doi.org/10.5281/zenodo.5236621 2022-01-12 23:17:49.255133+00:00 2022-01-12 23:17:49.255593+00:00 Air pollution Device Measurements [\"pm1\",\"pm2p5\",\"pm4\",\"pm10\",\"humidity\"] Wow Nature - Bosco Limite 2022-01-12 23:17:49.255133+00:00 ACTION project Earth sciences christian.bignami@ingv.it Christian Bignami 0000-0002-8632-9979 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia soil 9.454545454545455 5.2 The Sentinel-1 SAR data have been processed by using the LiCSBAS method implemented by COMET 4.408817635270542 4.4 Etna Volcano 22.118380062305295 14.2 comet 5.454545454545454 3.0 phase of Etna Volcano 12.760736196319018 10.4 boom 19.09090909090909 10.5 geosciences 100.0 0.5355959534645081 This Research Object reports the results of a fast InSAR multi-temporal analysis to map ground deformation related to the post-eruption phase of Etna Volcano, after the December 2018 event. 72.14428857715431 72.0 ground deformation 35.95092024539877 29.3 eruption phase 19.631901840490798 16.0 Sentinel-1 InSAR ground velocity of Etna Volcano, after the big eruption of December 2018. 23.44689378757515 23.4 after the Dec-2018 POLYGON ((14.7 37.95, 15.3 37.95, 15.3 37.44, 14.7 37.44, 14.7 37.95)) 24368e97-b7e8-47a0-a677-7610777dc6cc POLYGON ((14.7 37.95, 15.3 37.95, 15.3 37.44, 14.7 37.44, 14.7 37.95)) POLYGON ((14.7 37.95, 15.3 37.95, 15.3 37.44, 14.7 37.44, 14.7 37.95)) 14.7 37.95, 15.3 37.95, 15.3 37.44, 14.7 37.44, 14.7 37.95 service-account-enrichment . https://w3id.org/ro-id/1c9bfc94-dbb9-475e-af50-601bff9f6c0c 49515117 https://api.rohub.org/api/ros/8b715b0d-b5bb-4d6a-9228-704ec87652f2/crate/download/ 2022-02-16 16:10:01.055517+00:00 2025-03-05 01:21:29.885983+00:00 2022-02-16 16:10:01.055517+00:00 This Research Object reports the results of a fast InSAR multi-temporal analysis to map ground deformation related to the post-eruption phase of Etna Volcano, after the December 2018 event. The Sentinel-1 SAR data have been processed by using the LiCSBAS method implemented by COMET application/ld+json https://w3id.org/ro-id/8b715b0d-b5bb-4d6a-9228-704ec87652f2 Ground Motion Ground Velocity InSAR SAR Sentinel-1 Sentinel-1 InSAR ground velocity of Etna Volcano, after the big eruption of December 2018 MANUAL https://w3id.org/ro-id/8b715b0d-b5bb-4d6a-9228-704ec87652f2/6453fc74-be94-4832-9757-d228b557ea6d https://w3id.org/ro-id/13597655-8c57-4280-9765-76e5e9a6278e https://w3id.org/ro-id/48cef009-12f2-452f-89b6-fc05d6f2938d https://w3id.org/ro-id/54566b31-3489-43c4-abcd-53f59eaefa9c https://w3id.org/ro-id/9a6cbb90-8725-4377-994f-2b8367fccb6b https://w3id.org/ro-id/b73b8141-bc82-4ad9-abbd-79c89a88c558 https://w3id.org/ro-id/eae3c482-5579-418f-b98d-20d693f845b5 https://w3id.org/ro-id/f101ae40-b251-42fb-9a50-515f91e970ce https://w3id.org/ro-id/f37fcac5-5fb4-4d37-941c-9cdec9e6c892 https://w3id.org/ro-id/f3b79827-3acf-4530-8fe2-9c81b345d563 https://w3id.org/ro-id/9bd87173-eb18-4afe-9c70-dd33d7b67127 https://w3id.org/ro-id/cfbdf5cf-2eef-4f65-abeb-76c16db92cc7 https://w3id.org/ro-id/db7665de-1070-46f0-8d4f-f037027cb28a https://w3id.org/ro-id/dff9b071-8fd3-477f-9875-00c787161fae https://w3id.org/ro-id/3e532cd3-916b-42c1-8583-ab7774e19db5 https://w3id.org/ro-id/b1ed85de-043f-4561-84b1-fddaea4f8aea https://w3id.org/ro-id/bae57bdb-f352-4983-a4ce-611db59e115d https://w3id.org/ro-id/d4528387-10e5-406f-8f95-368e0c813c7e https://w3id.org/ro-id/f26805af-fc16-4d47-8453-1c507f01c903 https://w3id.org/ro-id/f5873a88-4af3-408d-9cf1-49bd5e638a1c https://w3id.org/ro-id/5e1e9100-2c79-48d1-93c9-7a821a7b7b1e https://w3id.org/ro-id/e1abba21-4272-4eb6-abd1-dc51a57939c3 https://w3id.org/ro-id/49c29a0b-0d21-4f05-afa0-3261f9b56842 https://w3id.org/ro-id/63ace803-4197-48f3-8bec-44fddd903a59 https://w3id.org/ro-id/725a9d35-d8bc-4420-9fce-5d58ef77981d https://w3id.org/ro-id/939164aa-8730-4b35-8e0b-5946cc1ccef8 https://w3id.org/ro-id/b1416fc5-5abd-48f5-a6e0-130423b0ac93 https://w3id.org/ro-id/248d2117-7bbf-4a80-8954-66a9d38348ad https://w3id.org/ro-id/624c51d5-e2e3-4eab-bb95-5f2cfa84f464 https://w3id.org/ro-id/771c087c-8823-4614-b47b-ddf602aa9bff https://w3id.org/ro-id/857591e6-7e6e-455a-8113-071f69804f05 https://w3id.org/ro-id/b5dd7f41-defe-4614-9121-7bb50e0ee2f0 Bignami, Christian, and INGV GeoSAR Laboratory. "Sentinel-1 InSAR ground velocity of Etna Volcano, after the big eruption of December 2018." ROHub. Feb 16 ,2022. https://w3id.org/ro-id/8b715b0d-b5bb-4d6a-9228-704ec87652f2. script metadata biblio data 213 https://api.rohub.org/api/resources/07e25d65-eb01-48d6-a874-502f4b7fbecb/download/ 2022-03-19 08:21:49.029862+00:00 2023-06-09 13:05:01.450514+00:00 application/vnd.google-earth.kml+xml Reference point in KML format 2022-03-19 08:21:49.029862+00:00 1413 https://api.rohub.org/api/resources/141f0775-4b87-439d-87d5-47c0c3cfae92/download/ 2022-03-19 08:21:40.300883+00:00 2023-06-09 13:04:10.928930+00:00 text/plain List of the used images 2022-03-19 08:21:40.300883+00:00 13162 https://api.rohub.org/api/resources/5df10037-1895-43db-84b4-f629af6982d3/download/ 2022-03-18 19:53:24.339423+00:00 2022-03-18 19:53:29.252273+00:00 Jupyter Notebook used to process SAR data based on LiCSBAS method 2022-03-18 19:53:24.339423+00:00 6702901 https://api.rohub.org/api/resources/7f36b3c5-de72-490d-bdd6-1f8b0208627a/download/ 2023-06-09 12:05:26.685797+00:00 2023-06-09 12:06:17.299846+00:00 application/pdf One Reference paper of LiCSBAS method 2023-06-09 12:05:26.685797+00:00 4049604 https://api.rohub.org/api/resources/81cecfa4-7222-4862-b53c-5ace30066ab8/download/ 2023-06-09 12:06:02.187826+00:00 2023-06-09 12:06:03.584840+00:00 application/pdf A second Reference paper of LiCSBAS method 2023-06-09 12:06:02.187826+00:00 388733 https://api.rohub.org/api/resources/99224e8f-d02c-41b7-868f-179a3f4838a3/download/ 2022-03-19 08:21:54.744273+00:00 2023-06-09 13:04:51.128359+00:00 image/png Final connection graph 2022-03-19 08:21:54.744273+00:00 154390 https://api.rohub.org/api/resources/9d318340-e188-4727-8f0c-c90287696f6e/download/ 2022-03-18 21:04:11.292887+00:00 2022-03-18 21:04:14.294836+00:00 image/tiff Final mean ground velocity map by LiCSBAS method in GEOTiff 2022-03-18 21:04:11.292887+00:00 39967814 https://api.rohub.org/api/resources/ab7bd32e-5ac9-426f-ac49-7f46990694f7/download/ 2022-03-18 19:48:02.704188+00:00 2022-03-18 19:48:10.780688+00:00 This file is a structured h5 file, containing all the results of the MT-InSAR processing application/x-tar LiCSBAS output 2022-03-18 19:48:02.704188+00:00 101757 https://api.rohub.org/api/resources/dcb3913c-0ae2-438a-879a-ccff1fd3752d/download/ 2022-03-18 19:52:27.521128+00:00 2023-06-09 13:04:42.382632+00:00 image/png Mean ground Velocity map from LiCSBAS processing 2022-03-18 19:52:27.521128+00:00 ground velocity 25.39877300613497 20.7 ground 10.545454545454545 5.8 earth sciences 100.0 0.5819281339645386 big eruption 6.257668711656441 5.1 deformation 15.887850467289717 10.2 of Dec-2018 result 7.818181818181818 4.3 Research Object 19.937694704049843 12.8 atmospheric sciences 100.0 0.5819281339645386 SAR interferometry 11.370716510903426 7.3 Sports facilities Lifestyle and leisure/Leisure/Leisure venue/Sports facilities Sport venue Sport/Sport venue earth resources and remote sensing 100.0 0.5355959534645081 velocity 14.0 7.7 case 7.636363636363637 4.2 velocity 13.551401869158877 8.7 deformation 16.545454545454547 9.1 phase 9.454545454545455 5.2 eruption 17.133956386292834 11.0 labgeosar@ingv.it INGV GeoSAR Laboratory Earth sciences published v1 monthly map of PM10 Copernicus Atmosphere Monitoring Service Data Cube Ro country map Ro monthly map map of PM10 federica.foglini@ismar.cnr.it Federica Foglini PCSS example5@hotmail.com Pepito Baston 0000-0002-8316-3195 UNO-Recoletos npepito@hotmail.com Nieves Pepito 0000-0003-3784-6651 office@man.poznan.pl 025cj6e44 Poznan Supercomputing and Networking Center neworg3@example.org abcd56789 Example Org 3 17ac6881-a240-4b44-974c-a83463aca07a MULTIPOLYGON (((9.4858320000001 42.615273, 9.49472 42.603607, 9.4827770000001 42.613052, 9.47778 42.617218, 9.465277 42.630829, 9.457777 42.643326, 9.4858320000001 42.615273)), ((9.446665 42.67889, 9.4480550000001 42.64944, 9.452221 42.630272, 9.473888 42.582222, 9.47805 42.576111, 9.50555 42.563889, 9.509998 42.563606, 9.51139 42.56721, 9.511665 42.571663, 9.509443 42.578049, 9.503054 42.59166, 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1.598333 50.37055, 1.603851 50.36879, 1.562778 50.39611, 1.560278 50.399162, 1.558055 50.4061, 1.577222 50.528053, 1.564167 50.68471, 1.564444 50.705826, 1.5986110000001 50.809166, 1.625 50.877777, 1.733333 50.942497, 1.7458330000001 50.948051, 1.768889 50.95583, 1.792778 50.962776, 1.9433330000001 50.995277, 2.23528 51.03805, 2.3594440000001 51.054443, 2.38472 51.051941, 2.407222 51.054993, 2.42305 51.058052, 2.492222 51.07611, 2.5166660000001 51.082771, 2.5416670000001 51.09111) 38.0 38.0 POINT (38.0 38.0) a384dfb8-5a8b-4ded-86fd-3ac17ecab1d6 POINT (38.0 38.0) service-account-enrichment False https://w3id.org/ro-id/88374f34-bdb3-4449-97b3-8e0a8483aa66 2022-02-17 21:13:07.580080+00:00 mailto:rpalma@man.poznan.pl 103398 https://api.rohub.org/api/ros/4e7a0712-e600-4645-a375-5a9b0d4ef122/crate/download/ 2022-02-17 14:58:39.070868+00:00 2024-03-05 12:17:26.373675+00:00 2022-02-17 14:58:39.070868+00:00 This Research Object demonstrate how to compute monthly map of PM10 over your country - modified application/ld+json https://w3id.org/ro-id/4e7a0712-e600-4645-a375-5a9b0d4ef122 17th Feb - Copernicus Atmosphere Monitoring Service Data Cube Research Object - snapshot Copernicus Atmosphere Monitoring Service Data Cube RO Feb 17th - published v1 MANUAL https://w3id.org/ro-id/4e7a0712-e600-4645-a375-5a9b0d4ef122/0675dd94-c052-4526-9e7f-3274e2a20d63 https://w3id.org/ro-id/4e7a0712-e600-4645-a375-5a9b0d4ef122/a14e28c2-9990-45f1-a7f1-194103406268 https://w3id.org/ro-id/4e7a0712-e600-4645-a375-5a9b0d4ef122/f3ebe1ed-9c2d-4da4-8e05-55df51e8bcbb Foglini, Federica, Nieves Pepito, and Pepito Baston. "Copernicus Atmosphere Monitoring Service Data Cube RO Feb 17th - published v1." ROHub. Feb 17 ,2022. https://doi.org/10.24424/kh1w-th55. biblio data myfolder mysubfolder raw data metadata https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2022-02-17 15:22:30.059240+00:00 2023-05-16 17:11:30.443960+00:00 https://zenodo.org/record/5554786/files/RELIANCE-Datacube-featuring-EOSC_v0.2.ipynb 2022-02-17 15:22:30.059240+00:00 This dataset provides daily air quality analyses and forecasts for Europe. CAMS produces specific daily air quality analyses and forecasts for the European domain at significantly higher spatial resolution (0.1 degrees, approx. 10km) than is available from the global analyses and forecasts. The production is based on an ensemble of nine air quality forecasting systems across Europe. A median ensemble is calculated from individual outputs, since ensemble products yield on average better performance than the individual model products. The spread between the nine models are used to provide an estimate of the forecast uncertainty. The analysis combines model data with observations provided by the European Environment Agency (EEA) into a complete and consistent dataset using various data assimilation techniques depending upon the air-quality forecasting system used. In parallel, air quality forecasts are produced once a day for the next four days. Both the analysis and the forecast are available at hourly time steps at seven height levels. Note that only nitrogen monoxide, nitrogen dioxide, sulphur dioxide, ozone, PM2.5, PM10 and dust are regularly validated against in situ observations, and therefore forecasts of all other variables are unvalidated and should be considered experimental. EU_CAMS_SURFACE_PM10_G Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo Jupter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2022-02-17 15:22:03.118296+00:00 2022-02-17 21:13:02.711907+00:00 https://reliance-das.adamplatform.eu/wcs?service=WCS&Request=GetCoverage&CoverageID=EU_CAMS_SURFACE_PM10_G&subset=unix(2018-09-01,2018-09-01)&format=image/tiff 2022-02-17 15:22:03.118296+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2022-02-17 15:22:15.915421+00:00 2022-02-17 21:13:02.585683+00:00 https://reliance-das.adamplatform.eu/opensearch/search?datasetId=EU_CAMS_SURFACE_PM10_G&startDate=2018-09-01&endDate=2018-09-01 2022-02-17 15:22:15.915421+00:00 Daily PM10 concentration for 1st September 2018 over Europe Daily PM10 concentration This resource has this description Flow to compute monthly map - updated List of hourly PM10 concentration data for September 1st 2018 over Europe Index of daily PM10 concentration for September 1st 2018 73394 https://api.rohub.org/api/resources/a4a570d8-f83c-47e8-bf0f-50c2a66810b1/download/ 2022-02-17 15:19:04.098429+00:00 2022-02-17 21:13:02.115316+00:00 image/png flow-dcro.png 2022-02-17 15:19:04.098429+00:00 https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2022-02-17 15:22:47.629469+00:00 2022-02-17 21:13:02.616681+00:00 https://box.psnc.pl/f/d90a0e1e0d/?raw=1 2022-02-17 15:22:47.629469+00:00 Catch data records sample from 2019 Catch data from Norway https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2022-02-17 15:21:26.221676+00:00 2022-02-17 21:13:02.517346+00:00 https://reliance-das.adamplatform.eu/opensearch/datasets?datasetId=EU_CAMS_SURFACE_PM10_G 2022-02-17 15:21:26.221676+00:00 POINT (38.0 38.0) MULTIPOLYGON (((9.4858320000001 42.615273, 9.49472 42.603607, 9.4827770000001 42.613052, 9.47778 42.617218, 9.465277 42.630829, 9.457777 42.643326, 9.4858320000001 42.615273)), ((9.446665 42.67889, 9.4480550000001 42.64944, 9.452221 42.630272, 9.473888 42.582222, 9.47805 42.576111, 9.50555 42.563889, 9.509998 42.563606, 9.51139 42.56721, 9.511665 42.571663, 9.509443 42.578049, 9.503054 42.59166, 9.497221 42.60083, 9.50028 42.59861, 9.5202770000001 42.572495, 9.531666 42.54916, 9.5338880000001 42.541939, 9.562222 42.272774, 9.5599990000001 42.19221, 9.5555550000001 42.127777, 9.5533330000001 42.115555, 9.54583 42.102219, 9.4480550000001 41.999443, 9.42555 41.975, 9.41111 41.954163, 9.405554 41.934998, 9.397192 41.875931, 9.396666 41.862778, 9.398611 41.85083, 9.402498 41.840271, 9.404444 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51.054443, 2.38472 51.051941, 2.407222 51.054993, 2.42305 51.058052, 2.492222 51.07611, 2.5166660000001 51.082771, 2.5416670000001 51.09111))) POINT (-155.499 19.661) Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) 78c886f0-071a-4c18-b4dd-ebe86a23d74b POINT (15.0 37.75) service-account-enrichment 1850761 https://api.rohub.org/api/ros/114d6770-78b5-4f7a-a357-360cc8095bf1/crate/download/ 2022-03-10 00:49:43.815847+00:00 2025-03-05 00:51:30.903940+00:00 2022-03-10 00:49:43.815847+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/114d6770-78b5-4f7a-a357-360cc8095bf1 Etna Eruption 2021 02 19 Research Object MANUAL https://w3id.org/ro-id/114d6770-78b5-4f7a-a357-360cc8095bf1/a112a689-d0f4-44f9-9c8c-15425f4329ad Stelitano, Dario. "Etna Eruption 2021 02 19 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/114d6770-78b5-4f7a-a357-360cc8095bf1. raw data data metadata biblio https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 00:50:16.244407+00:00 2022-03-10 00:50:16.459624+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 00:50:16.244407+00:00 532684 https://api.rohub.org/api/resources/5de3508c-4dd6-41dc-bd95-1f40c90df054/download/ 2022-03-10 00:50:22.276715+00:00 2022-03-10 00:50:25.390021+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210219_0800 2022-03-10 00:50:22.276715+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 00:50:18.849951+00:00 2022-03-10 00:50:19.065264+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 00:50:18.849951+00:00 1788885 https://api.rohub.org/api/resources/65419b11-ffa1-49e5-88f9-7d6ec2de6f24/download/ 2022-03-10 00:50:03.945479+00:00 2022-03-10 00:50:07.182951+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210219_1000 2022-03-10 00:50:03.945479+00:00 https://youtu.be/MRZUVJRi2xI 2022-03-10 00:50:10.563424+00:00 2022-03-10 00:50:10.804040+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210219_1000 2022-03-10 00:50:10.563424+00:00 https://youtu.be/5bUT8Sih4mo 2022-03-10 00:50:13.121438+00:00 2022-03-10 00:50:13.338019+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210219_1000 2022-03-10 00:50:13.121438+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE POINT (15.0 37.75) 1f74d3d6-f6bd-4f4b-bfe9-e52cebccd7a6 POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) service-account-enrichment 1957096 https://api.rohub.org/api/ros/00635a9e-6a0b-4280-84a3-0a622bf27482/crate/download/ 2022-03-10 11:41:06.217407+00:00 2025-03-05 00:51:30.475196+00:00 2022-03-10 11:41:06.217407+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/00635a9e-6a0b-4280-84a3-0a622bf27482 Etna Eruption 2021 02 16 Research Object MANUAL https://w3id.org/ro-id/00635a9e-6a0b-4280-84a3-0a622bf27482/f7036a22-ab6d-47ab-956b-bfa1fbb138b3 Stelitano, Dario. "Etna Eruption 2021 02 16 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/00635a9e-6a0b-4280-84a3-0a622bf27482. biblio raw data data metadata https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 11:41:38.688525+00:00 2022-03-10 11:41:38.898711+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 11:41:38.688525+00:00 215657 https://api.rohub.org/api/resources/3bd13b28-46cd-4bd4-8ddb-475756c34707/download/ 2022-03-10 11:41:45.381170+00:00 2022-03-10 11:41:48.306873+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210216_1600 2022-03-10 11:41:45.381170+00:00 https://youtu.be/BiqGc6hBQAU 2022-03-10 11:41:36.168259+00:00 2022-03-10 11:41:36.436387+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210216_1800 2022-03-10 11:41:36.168259+00:00 1913984 https://api.rohub.org/api/resources/6780a15b-874e-4ce7-a543-1ef33e13ea5c/download/ 2022-03-10 11:41:26.839167+00:00 2022-03-10 11:41:29.713120+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210216_1800 2022-03-10 11:41:26.839167+00:00 https://youtu.be/5ReEp8UbRmU 2022-03-10 11:41:33.506223+00:00 2022-03-10 11:41:33.728852+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210216_1800 2022-03-10 11:41:33.506223+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 11:41:41.137273+00:00 2022-03-10 11:41:41.357790+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 11:41:41.137273+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE POINT (15.0 37.75) 13de5422-0db1-4a9d-99b9-f12a06e5931f POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) service-account-enrichment 1833419 https://api.rohub.org/api/ros/258c5e83-ce3b-4ea2-a845-23d0aebdae7d/crate/download/ 2022-03-10 12:01:08.866449+00:00 2025-03-05 00:51:30.689261+00:00 2022-03-10 12:01:08.866449+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/258c5e83-ce3b-4ea2-a845-23d0aebdae7d Etna Eruption 2021 02 17 Research Object MANUAL https://w3id.org/ro-id/258c5e83-ce3b-4ea2-a845-23d0aebdae7d/5384f20e-5fef-4062-ba36-8ae2d10b7312 Stelitano, Dario. "Etna Eruption 2021 02 17 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/258c5e83-ce3b-4ea2-a845-23d0aebdae7d. metadata biblio data raw data http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 12:02:51.163660+00:00 2022-03-10 12:02:51.420130+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 12:02:51.163660+00:00 https://youtu.be/t5YcOViEU_E 2022-03-10 12:02:43.977530+00:00 2022-03-10 12:02:44.222223+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210218_0100 2022-03-10 12:02:43.977530+00:00 https://youtu.be/-7lSBNfnToM 2022-03-10 12:02:41.047055+00:00 2022-03-10 12:02:41.271096+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210218_0100 2022-03-10 12:02:41.047055+00:00 1780706 https://api.rohub.org/api/resources/650a6881-3ef1-43af-89cd-3dcfce374983/download/ 2022-03-10 12:02:26.301770+00:00 2022-03-10 12:02:29.717878+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210217_2300 2022-03-10 12:02:26.301770+00:00 471319 https://api.rohub.org/api/resources/d64df5a0-9bca-44ff-9f9b-d4b023efdfc2/download/ 2022-03-10 12:03:50.586593+00:00 2022-03-10 12:03:53.727687+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210217_2300 2022-03-10 12:03:50.586593+00:00 https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 12:02:47.173805+00:00 2022-03-10 12:02:47.404197+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 12:02:47.173805+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE POINT (15.0 37.75) 44174c5e-4f9c-4192-b342-62a5013f8db0 POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) service-account-enrichment 1875608 https://api.rohub.org/api/ros/9b2a8c25-30c1-4dc2-9520-96d26cb29e72/crate/download/ 2022-03-10 12:07:01.432625+00:00 2025-03-05 00:51:31.555271+00:00 2022-03-10 12:07:01.432625+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/9b2a8c25-30c1-4dc2-9520-96d26cb29e72 Etna Eruption 2021 02 24 Research Object MANUAL https://w3id.org/ro-id/9b2a8c25-30c1-4dc2-9520-96d26cb29e72/2cf0de84-e9ff-4fa3-a6bf-f904113287e5 Stelitano, Dario. "Etna Eruption 2021 02 24 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/9b2a8c25-30c1-4dc2-9520-96d26cb29e72. biblio metadata data raw data https://youtu.be/Vae8zZzd1wM 2022-03-10 12:07:50.486721+00:00 2022-03-10 12:07:50.691137+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210224_2100 2022-03-10 12:07:50.486721+00:00 https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 12:07:57.317995+00:00 2022-03-10 12:07:57.722945+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 12:07:57.317995+00:00 1742146 https://api.rohub.org/api/resources/46729143-cc60-4b36-9a0b-0eab61986027/download/ 2022-03-10 12:07:43.761064+00:00 2022-03-10 12:07:46.899849+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210224_2100 2022-03-10 12:07:43.761064+00:00 1844188 https://api.rohub.org/api/resources/6881dbcc-88a0-4652-828d-513503fae5b8/download/ 2022-03-10 12:08:34.279360+00:00 2022-03-10 12:08:37.553317+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210224_1900 2022-03-10 12:08:34.279360+00:00 https://youtu.be/vMbhkmb6b7c 2022-03-10 12:07:53.340556+00:00 2022-03-10 12:07:53.539665+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210224_2100 2022-03-10 12:07:53.340556+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 12:08:00.675099+00:00 2022-03-10 12:08:00.875748+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 12:08:00.675099+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) 95da0fb9-53e0-49f6-b3dd-60986e962211 POINT (15.0 37.75) service-account-enrichment 2021983 https://api.rohub.org/api/ros/687e0266-fe8a-408c-9fb4-57c48640d700/crate/download/ 2022-03-10 13:32:31.782234+00:00 2025-03-05 00:51:31.122075+00:00 2022-03-10 13:32:31.782234+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/687e0266-fe8a-408c-9fb4-57c48640d700 Etna Eruption 2021 02 20 Research Object MANUAL https://w3id.org/ro-id/687e0266-fe8a-408c-9fb4-57c48640d700/ac0d9208-5ba5-4a8b-9bb7-d27c57cb18b4 Stelitano, Dario. "Etna Eruption 2021 02 20 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/687e0266-fe8a-408c-9fb4-57c48640d700. raw data data biblio metadata 2719750 https://api.rohub.org/api/resources/1ea25789-64f2-452d-bc6d-eff5d78c6865/download/ 2022-03-10 13:35:14.562546+00:00 2022-03-10 13:35:17.942422+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210220_2200 2022-03-10 13:35:14.562546+00:00 https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 13:35:05.988220+00:00 2022-03-10 13:35:06.241023+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 13:35:05.988220+00:00 https://youtu.be/tDdBgXmJt4M 2022-03-10 13:35:02.986303+00:00 2022-03-10 13:35:03.222781+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210221_0000 2022-03-10 13:35:02.986303+00:00 https://youtu.be/VWs20raLgRc 2022-03-10 13:34:59.852231+00:00 2022-03-10 13:35:00.059491+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210221_0000 2022-03-10 13:34:59.852231+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 13:35:08.482633+00:00 2022-03-10 13:35:08.709097+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 13:35:08.482633+00:00 1861342 https://api.rohub.org/api/resources/97ef253b-58f6-4d4a-910e-1d460a0b0f72/download/ 2022-03-10 13:34:52.428826+00:00 2022-03-10 13:34:55.449453+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210220_2300 2022-03-10 13:34:52.428826+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE POINT (15.0 37.75) 62b7c249-053f-4258-9f5e-cb85fcd0be34 POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) service-account-enrichment 1921725 https://api.rohub.org/api/ros/5922be96-b69d-429c-ab13-5852cdcd6d09/crate/download/ 2022-03-10 13:48:33.957435+00:00 2025-03-05 00:51:31.341425+00:00 2022-03-10 13:48:33.957435+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/5922be96-b69d-429c-ab13-5852cdcd6d09 Etna Eruption 2021 02 22 Research Object MANUAL https://w3id.org/ro-id/5922be96-b69d-429c-ab13-5852cdcd6d09/5844aec6-f61c-413c-b212-f4c4921a9757 Stelitano, Dario. "Etna Eruption 2021 02 22 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/5922be96-b69d-429c-ab13-5852cdcd6d09. raw data biblio metadata data https://youtu.be/CGhxdxCx0Lc 2022-03-10 13:49:06.861725+00:00 2022-03-10 13:49:07.114032+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210222_2300 2022-03-10 13:49:06.861725+00:00 3077583 https://api.rohub.org/api/resources/a3ee93ea-7075-48db-a19c-8b0ce156254e/download/ 2022-03-10 13:50:19.792902+00:00 2022-03-10 13:50:23.335281+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210222_2100 2022-03-10 13:50:19.792902+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 13:49:15.216661+00:00 2022-03-10 13:49:15.528144+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 13:49:15.216661+00:00 https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 13:49:12.377848+00:00 2022-03-10 13:49:12.663978+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 13:49:12.377848+00:00 1785546 https://api.rohub.org/api/resources/f8d3c693-b90e-4e3e-9369-7b13bf7c6d1c/download/ 2022-03-10 13:48:59.684382+00:00 2022-03-10 13:49:02.630764+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210222_2200 2022-03-10 13:48:59.684382+00:00 https://youtu.be/IdcjWZluTTI 2022-03-10 13:49:09.507134+00:00 2022-03-10 13:49:09.814444+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210222_2300 2022-03-10 13:49:09.507134+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE POINT (15.0 37.75) 9a215572-9f9f-4fca-89bb-8107ad97b063 POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) service-account-enrichment 1819506 https://api.rohub.org/api/ros/7b712a64-9f59-4e6b-a209-b36b88feeee7/crate/download/ 2022-03-10 15:09:15.176399+00:00 2025-03-05 00:51:31.769094+00:00 2022-03-10 15:09:15.176399+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/7b712a64-9f59-4e6b-a209-b36b88feeee7 Etna Eruption 2021 02 28 Research Object MANUAL https://w3id.org/ro-id/7b712a64-9f59-4e6b-a209-b36b88feeee7/bb0be0c2-64c8-4445-8e84-0bd91545bdc0 Stelitano, Dario. "Etna Eruption 2021 02 28 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/7b712a64-9f59-4e6b-a209-b36b88feeee7. raw data biblio metadata data https://youtu.be/d0zuReUfZMg 2022-03-10 15:10:20.426283+00:00 2022-03-10 15:10:20.645938+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210228_0800 2022-03-10 15:10:20.426283+00:00 https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 15:10:25.484604+00:00 2022-03-10 15:10:25.724746+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 15:10:25.484604+00:00 1739362 https://api.rohub.org/api/resources/36389c6d-5695-43e5-9410-aae2643e9701/download/ 2022-03-10 15:10:12.486663+00:00 2022-03-10 15:10:16.018742+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210228_0700 2022-03-10 15:10:12.486663+00:00 https://youtu.be/ypZ9Pou2LvY 2022-03-10 15:10:22.988881+00:00 2022-03-10 15:10:23.219447+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210228_0800 2022-03-10 15:10:22.988881+00:00 816177 https://api.rohub.org/api/resources/d6824cd3-1eb7-4a89-9a33-0a1497c427c2/download/ 2022-03-10 15:10:45.399136+00:00 2022-03-10 15:10:48.413538+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210228_0600 2022-03-10 15:10:45.399136+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 15:10:28.326455+00:00 2022-03-10 15:10:28.559970+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 15:10:28.326455+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) 3db1f448-809f-4516-8d85-a0617967bde3 POINT (15.0 37.75) service-account-enrichment 2034024 https://api.rohub.org/api/ros/1d9c7bde-4991-4da3-a73f-7f0e2e7d551b/crate/download/ 2022-03-10 15:33:29.483179+00:00 2025-03-05 00:51:31.980275+00:00 2022-03-10 15:33:29.483179+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/1d9c7bde-4991-4da3-a73f-7f0e2e7d551b Etna Eruption 2021 03 02 Research Object MANUAL https://w3id.org/ro-id/1d9c7bde-4991-4da3-a73f-7f0e2e7d551b/80e9d1ee-1cf4-4f18-ba10-3ac60e1a0dcd Stelitano, Dario. "Etna Eruption 2021 03 02 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/1d9c7bde-4991-4da3-a73f-7f0e2e7d551b. raw data data biblio metadata 1344981 https://api.rohub.org/api/resources/6feffb93-325b-4ea0-8ee8-680ed5fd32aa/download/ 2022-03-10 15:34:13.741615+00:00 2022-03-10 15:34:16.835851+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210302_1100 2022-03-10 15:34:13.741615+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 15:34:08.798076+00:00 2022-03-10 15:34:09.028387+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 15:34:08.798076+00:00 1934541 https://api.rohub.org/api/resources/a20c4d43-7be5-4af4-8497-46e724c6bc13/download/ 2022-03-10 15:33:52.992948+00:00 2022-03-10 15:33:56.054384+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210302_1200 2022-03-10 15:33:52.992948+00:00 https://youtu.be/Jkt2_mpgQRI 2022-03-10 15:34:00.337224+00:00 2022-03-10 15:34:00.556596+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210302_1300 2022-03-10 15:34:00.337224+00:00 https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 15:34:05.847511+00:00 2022-03-10 15:34:06.069957+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 15:34:05.847511+00:00 https://youtu.be/e8LDeJ_-IYM 2022-03-10 15:34:03.174398+00:00 2022-03-10 15:34:03.378438+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210302_1300 2022-03-10 15:34:03.174398+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE service-account-enrichment 1752221 https://api.rohub.org/api/ros/f695db70-62da-434b-a366-5f175494894e/crate/download/ 2022-03-10 15:41:19.270763+00:00 2025-03-05 00:51:32.201032+00:00 2022-03-10 15:41:19.270763+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/f695db70-62da-434b-a366-5f175494894e Etna Eruption 2021 03 04 Research Object MANUAL Stelitano, Dario. "Etna Eruption 2021 03 04 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/f695db70-62da-434b-a366-5f175494894e. metadata data raw data biblio 1741629 https://api.rohub.org/api/resources/2d84d2af-4a9f-4e3b-9522-7ed56c606f6b/download/ 2022-03-10 15:42:08.467725+00:00 2022-03-10 15:42:11.489521+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210304_0700 2022-03-10 15:42:08.467725+00:00 https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 15:42:21.352340+00:00 2022-03-10 15:42:21.550970+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 15:42:21.352340+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 15:42:24.337846+00:00 2022-03-10 15:42:24.526196+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 15:42:24.337846+00:00 https://youtu.be/blUCdl15HM4 2022-03-10 15:42:18.121380+00:00 2022-03-10 15:42:18.350521+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210304_0800 2022-03-10 15:42:18.121380+00:00 https://youtu.be/Jkt2_mpgQRI 2022-03-10 15:42:15.327095+00:00 2022-03-10 15:42:15.509398+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210304_0800 2022-03-10 15:42:15.327095+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE POINT (15.0 37.75) 4b4b4e98-b179-4a20-9d1a-81a93750c620 POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) service-account-enrichment 1728901 https://api.rohub.org/api/ros/90170231-63d3-49ed-b136-4f06c562ab35/crate/download/ 2022-03-10 15:52:27.726412+00:00 2025-03-05 00:51:32.420984+00:00 2022-03-10 15:52:27.726412+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/90170231-63d3-49ed-b136-4f06c562ab35 Etna Eruption 2021 03 07 Research Object MANUAL https://w3id.org/ro-id/90170231-63d3-49ed-b136-4f06c562ab35/f5419588-0987-4c62-a2cf-23f25a891745 Stelitano, Dario. "Etna Eruption 2021 03 07 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/90170231-63d3-49ed-b136-4f06c562ab35. metadata raw data data biblio https://youtu.be/st-PxspAtv0 2022-03-10 15:52:56.121253+00:00 2022-03-10 15:52:56.337231+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210307_0700 2022-03-10 15:52:56.121253+00:00 https://youtu.be/1HBw30dCsQU 2022-03-10 15:52:59.047954+00:00 2022-03-10 15:52:59.264964+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210307_0700 2022-03-10 15:52:59.047954+00:00 https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 15:53:01.678269+00:00 2022-03-10 15:53:01.903560+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 15:53:01.678269+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 15:53:04.976085+00:00 2022-03-10 15:53:05.150242+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 15:53:04.976085+00:00 1596932 https://api.rohub.org/api/resources/e6e7f136-894e-4378-a101-3ae76db6d729/download/ 2022-03-10 15:52:48.979802+00:00 2022-03-10 15:52:52.039964+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210307_0600 2022-03-10 15:52:48.979802+00:00 2278065 https://api.rohub.org/api/resources/f68827fd-d246-4143-80bc-5e2a90c62581/download/ 2022-03-10 15:53:12.873946+00:00 2022-03-10 15:53:15.945906+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210307_0500 2022-03-10 15:53:12.873946+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission height calculation SEVIRI box volcanic column column research World Meteorological Organization height World Meteorological Organization Trapani Etna Etna eruption Etna aim volcanology calculation EUMETSAT sounding Trapani 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE POINT (15.0 37.75) 1eba86a7-8bd5-405f-83f8-872bb06e6436 POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) service-account-enrichment 1986300 https://api.rohub.org/api/ros/9dda85b5-db3b-4167-8afb-034615cc16c8/crate/download/ 2022-03-10 16:18:25.419673+00:00 2025-03-05 00:51:32.629921+00:00 2022-03-10 16:18:25.419673+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/9dda85b5-db3b-4167-8afb-034615cc16c8 Etna Eruption 2021 03 09 Research Object MANUAL https://w3id.org/ro-id/9dda85b5-db3b-4167-8afb-034615cc16c8/eed3bad3-c43b-4f54-b391-b745e5da654d Stelitano, Dario. "Etna Eruption 2021 03 09 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/9dda85b5-db3b-4167-8afb-034615cc16c8. data biblio metadata raw data 1674681 https://api.rohub.org/api/resources/555862ce-f0a6-42f5-9dd0-9f3143a1caec/download/ 2022-03-10 16:18:46.047715+00:00 2022-03-10 16:18:49.582095+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210309_2300 2022-03-10 16:18:46.047715+00:00 https://youtu.be/AMRKswnAi7Q 2022-03-10 16:18:58.374760+00:00 2022-03-10 16:18:58.618087+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210310_0000 2022-03-10 16:18:58.374760+00:00 https://youtu.be/caFW5gzfVhI 2022-03-10 16:18:55.108176+00:00 2022-03-10 16:18:55.339265+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210310_0000 2022-03-10 16:18:55.108176+00:00 https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 16:19:01.415958+00:00 2022-03-10 16:19:01.639454+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 16:19:01.415958+00:00 13399939 https://api.rohub.org/api/resources/f7cd6f5a-8c54-440b-86d1-b92a513a8c39/download/ 2022-03-10 16:19:26.308248+00:00 2022-03-10 16:19:30.660126+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210309_2200 2022-03-10 16:19:26.308248+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 16:19:04.290216+00:00 2022-03-10 16:19:04.525751+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 16:19:04.290216+00:00 Dario Stelitano Earth sciences 10.13039/501100000781 European Commission 00qps9a02 Istituto Nazionale di Geofisica e Vulcanologia 101017502 RELIANCE Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. 65.93186372745491 65.8 Etna eruption 29.656607700312172 28.5 Etna Eruption 2021 03 24 Research Object. 14.228456913827655 14.2 Trapani https://www.wikidata.org/wiki/Q13664 Natural disasters Disaster, accident and emergency incident/Disaster/Natural disasters Etna https://www.wikidata.org/wiki/Q16990 Radiosounding provided by WMO in Trapani station. 19.839679358717436 19.8 Trapani 11.755233494363928 7.3 system 4.99194847020934 3.1 Mountains Environment/Natural resources/Land resources/Mountains calculation 15.780998389694043 9.8 Etna 21.90016103059581 13.6 geology 100.0 0.9904175400733948 Weather Weather Column Top Height 12.709497206703912 9.1 World Meteorological Organization 16.480446927374302 11.8 earth sciences 100.0 0.9904175400733948 Column Top Height calculation 11.446409989594171 11.0 box around Etna 4.578563995837669 4.4 sounding 14.331723027375201 8.9 Etna 18.854748603351958 13.5 EUMETSAT 15.502793296089386 11.1 space sciences 100.0 0.5544100999832153 research object 11.966701352757543 11.5 SEVIRI 10.75418994413408 7.7 space sciences (general) 100.0 0.5544100999832153 volcanology 100.0 7.4 calculation 13.268156424581006 9.5 SEVIRI box 42.35171696149844 40.7 POINT (15.0 37.75) 5d51dbbd-e4c2-46a7-a739-400925445bd8 POINT (15.0 37.75) 15.0 37.75 POINT (15.0 37.75) service-account-enrichment 1968912 https://api.rohub.org/api/ros/ae86fae3-f7a9-4582-9582-d3e5cf27881e/crate/download/ 2022-03-10 16:38:38.600063+00:00 2025-03-05 00:51:33.059059+00:00 2022-03-10 16:38:38.600063+00:00 Volcanic Column Top Height calculation using Dark Pixel method in a 19x19 EUMETSAT/SEVIRI box around Etna volcano. Radiosounding provided by WMO in Trapani station. application/ld+json https://w3id.org/ro-id/ae86fae3-f7a9-4582-9582-d3e5cf27881e Etna Eruption 2021 03 24 Research Object MANUAL https://w3id.org/ro-id/ae86fae3-f7a9-4582-9582-d3e5cf27881e/fb66cf2c-3ca7-4a97-b60c-65726271178b https://w3id.org/ro-id/a9736593-7c13-4a2b-b777-0b5504053f27 https://w3id.org/ro-id/ed7f50a9-cfcd-4940-b04d-d6f3cfc03dff https://w3id.org/ro-id/06cf592a-e81f-4e4a-9d98-61a09f319020 https://w3id.org/ro-id/1d8d44ae-9669-4616-8297-951627ddfa3b https://w3id.org/ro-id/24f87165-d038-49ed-ad6c-e296a320f7d4 https://w3id.org/ro-id/2aa17299-d447-4430-b414-c871412073ee https://w3id.org/ro-id/379da2bc-6db3-47c9-8e0f-40687f593787 https://w3id.org/ro-id/3cd84c6d-efe8-4fec-8b72-fc4034f83538 https://w3id.org/ro-id/732c5667-081d-471e-b979-f4ff6bcfb0b5 https://w3id.org/ro-id/d41373b4-ea29-4305-b3a7-fbb4269c856f https://w3id.org/ro-id/d8358bc4-4724-4263-bdb0-28b7aea66be0 https://w3id.org/ro-id/e54df1fe-bbf4-48d2-9ab5-5d71e5dc9da0 https://w3id.org/ro-id/47f82b88-216e-4647-a275-0dc1ecebad46 https://w3id.org/ro-id/58822377-23cf-4379-ae7a-7f8009bdbc8f https://w3id.org/ro-id/0b92119f-dde0-42a7-b739-8b325443cbfb https://w3id.org/ro-id/37287334-8d4b-41d5-b693-ac173095f2e1 https://w3id.org/ro-id/4e1c922d-c835-45b2-8f60-e6ec8d418beb https://w3id.org/ro-id/aff716b8-bbd7-4e6e-add9-07f87def6f7b https://w3id.org/ro-id/51359fcb-1453-4462-b031-9d8cd1502134 https://w3id.org/ro-id/53b2f5e0-2af6-4d0e-b2d5-4f09d0428269 https://w3id.org/ro-id/7c1ed93d-0aff-4908-9015-b2a28c282e44 https://w3id.org/ro-id/7d916713-3981-4067-8435-a5606218daf5 https://w3id.org/ro-id/952c7fba-8ba2-4bc9-b81f-80fd0bc62874 https://w3id.org/ro-id/ae05a6d9-da60-4f0f-bd8d-a768b072a290 https://w3id.org/ro-id/e208f01c-adaf-41af-83f6-b58dce58fec2 https://w3id.org/ro-id/87ba6515-1def-47be-99ba-60dd1ac67de8 https://w3id.org/ro-id/95898c5e-442d-4f8e-808b-c849597e0da7 https://w3id.org/ro-id/045c1529-667c-4b9e-8edd-32da2b93d405 https://w3id.org/ro-id/6c26254d-121b-42e8-bbf5-c04af6ae4850 https://w3id.org/ro-id/6ee9f3ce-5a1c-4a12-ba39-c052981a8dee https://w3id.org/ro-id/93a250ce-e1bf-42a9-ac45-b268575d2f9a https://w3id.org/ro-id/ae505dac-25bc-46b6-a211-9aa2575c13fe https://w3id.org/ro-id/02d19845-bfa8-4201-9341-3abede5f5675 https://w3id.org/ro-id/04f36e24-dc5d-49fd-9062-39546e677c44 https://w3id.org/ro-id/1d954682-0ef4-4a89-b9b2-fc050437fd21 https://w3id.org/ro-id/b39e208d-fc9c-4ca4-80e1-75d68a829ede Stelitano, Dario. "Etna Eruption 2021 03 24 Research Object." ROHub. Mar 10 ,2022. https://w3id.org/ro-id/ae86fae3-f7a9-4582-9582-d3e5cf27881e. data metadata biblio raw data 8146124 https://api.rohub.org/api/resources/02e0da2d-470d-4fdf-9727-a4b2b746dd17/download/ 2022-03-10 16:39:28.841611+00:00 2023-06-05 14:19:47.335090+00:00 text/html (interactive html) Volcanic Column Top Height using Dark Pixel Etna 20210324_0000 2022-03-10 16:39:28.841611+00:00 https://youtu.be/8gyQjXzLKB0 2022-03-10 16:39:06.078555+00:00 2022-03-10 16:39:06.293621+00:00 EUMETSAT/Meteosat RGB Ash composite video - Central Mediterranean Sea 20210324_0200 2022-03-10 16:39:06.078555+00:00 https://www.mdpi.com/2076-3263/8/4/140/htm 2022-03-10 16:39:12.254646+00:00 2022-03-10 16:39:12.469857+00:00 Dark Pixel procedure description. Chapter 3.3 2022-03-10 16:39:12.254646+00:00 http://editoria.rm.ingv.it/miscellanea/2020/miscellanea57/?page=114 2022-03-10 16:39:14.803356+00:00 2022-03-10 16:39:15.041898+00:00 Multimission Acquisition SysTem (MAST) description 2022-03-10 16:39:14.803356+00:00 1702779 https://api.rohub.org/api/resources/3b80da8f-373e-4de2-8c12-30594b699609/download/ 2022-03-10 16:38:58.411536+00:00 2022-03-10 16:39:01.548185+00:00 image/png EUMETSAT/Meteosat RGB Ash composite - Central Mediterranean Sea 20210324_0100 2022-03-10 16:38:58.411536+00:00 https://youtu.be/QncRb0ZOv0E 2022-03-10 16:39:08.838121+00:00 2022-03-10 16:39:09.080271+00:00 EUMETSAT/Meteosat Brightness Temperature Difference 11-12um video - Central Mediterranean Sea 20210324_0200 2022-03-10 16:39:08.838121+00:00 Volcanic eruption Disaster, accident and emergency incident/Disaster/Natural disasters/Volcanic eruption Mar-24-2021 volcano 6.9243156199677935 4.3 World Meteorological Organization 18.357487922705314 11.4 sounding 12.430167597765363 8.9 research 5.958132045088567 3.7 World Meteorological Organization https://www.wikidata.org/wiki/Q170424 Dario Stelitano Applied sciences Decatur The Illinois Basin Illinois Archer Daniels Midland mechanical data subsurface data Decatur Project Dataset Illinois Illinois Basin United States of America carbon dioxide data injection Archer Daniels Midland dataset Decatur Project Dataset The Illinois Basin Decatur Illinois report United States of America assessment injection at the Archer Daniels Midland Illinois Basin -88.89 39.87 POINT (-88.89 39.87) e459c565-3c19-460e-b703-75af8237a82c POINT (-88.89 39.87) service-account-enrichment 6642 https://api.rohub.org/api/ros/0e64ec05-65dc-4cd1-b652-1c7bf3be0639/crate/download/ 2022-03-22 00:38:18.628199+00:00 2025-03-05 00:53:53.667089+00:00 2022-03-22 00:38:18.628199+00:00 The Illinois Basin - Decatur Project (IBDP) dataset is a reference dataset containing subsurface data, monitoring data, geomodels, geomechanical data, and reports related to assessment and CO2 injection at the Archer Daniels Midland site in Decatur, Illinois, United States. application/ld+json https://w3id.org/ro-id/0e64ec05-65dc-4cd1-b652-1c7bf3be0639 Illinois Basin - Decatur Project Dataset MANUAL https://w3id.org/ro-id/0e64ec05-65dc-4cd1-b652-1c7bf3be0639/75f05324-9f7b-4622-9b10-c4142930e532 Illinois State Geological Survey (Illinois State Geological Survey). "Illinois Basin - Decatur Project Dataset." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/0e64ec05-65dc-4cd1-b652-1c7bf3be0639. POINT (-88.89 39.87) data biblio metadata raw data Illinois State Geological Survey (2022).Illinois Basin - Decatur Project Dataset [Data set]. Norstore. https://doi.org/10.11582/2022.00017 Illinois State Geological Survey (Illinois State Geological Survey) Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2022.00017 2022-03-09 00:00:00 2022-03-22 00:38:32.699107+00:00 The Illinois Basin - Decatur Project (IBDP) dataset is a reference dataset containing subsurface data, monitoring data, geomodels, geomechanical data, and reports related to assessment and CO2 injection at the Archer Daniels Midland site in Decatur, Illinois, United States. Illinois Basin - Decatur Project Dataset 2022-03-09 00:00:00 Illinois State Geological Survey (Illinois State Geological Survey) Illinois.State.Geological.Survey@rohub.com Illinois State Geological Survey (Illinois State Geological Survey) Geo H. Environmental research Life sciences Physical sciences Earth sciences sandstone 19.490254872563717 13.0 Science and technology Science and technology Hades apparatus 15.771812080536913 4.7 deformation 16.34182908545727 10.9 synchrotron 11.094452773613193 7.4 reservoir 7.3085846867749416 6.3 core sample 8.095952023988005 5.4 geophysics 100.0 0.6389099359512329 image 9.628770301624131 8.3 service-account-enrichment 7892 https://api.rohub.org/api/ros/41a50d36-8102-4f0c-a227-3fc44ae00a71/crate/download/ 2022-03-22 00:38:34.979065+00:00 2025-03-05 00:45:32.544737+00:00 2022-03-22 00:38:34.979065+00:00 In-situ X-ray tomography images of the deformation of a core sample of Groningen sandstone (Hades apparatus, beamline ID19, ESRF) application/ld+json https://w3id.org/ro-id/41a50d36-8102-4f0c-a227-3fc44ae00a71 4D synchrotron X-ray imaging of grain scale deformation mechanisms in a seismogenic gas reservoir sandstone during axial compaction MANUAL https://w3id.org/ro-id/f7333542-cfef-4a27-bfb2-c210b53b88b8 https://w3id.org/ro-id/8be0da68-0374-41d6-bc69-fd02b445d89c https://w3id.org/ro-id/2470d20e-b941-4257-8074-1dc69fc89180 https://w3id.org/ro-id/3c686357-c966-43a4-88e3-0a6b2fe6fe7b https://w3id.org/ro-id/66882826-aacd-44f0-b3fb-cb0daef582ea https://w3id.org/ro-id/7224d420-58e9-4d57-bd0c-915bdbaaba95 https://w3id.org/ro-id/882ad179-6f50-4b91-afd6-bb950cb700c0 https://w3id.org/ro-id/982d6bc0-24b0-418f-bf08-69b0bc4a963a https://w3id.org/ro-id/98809bba-63b0-4b80-8059-edd5cbb9000f https://w3id.org/ro-id/a8874812-e332-4236-a389-db2f7d35421f https://w3id.org/ro-id/e22ee2a0-7e6c-453c-aaee-f48c5f0653d8 https://w3id.org/ro-id/f6b78c91-930e-4380-a254-a6bd62b9ba38 https://w3id.org/ro-id/ffcb3f9f-781a-4eee-8cb7-4f8507d4cf67 https://w3id.org/ro-id/44fa2f04-f417-4356-bd8f-c160ef10981e https://w3id.org/ro-id/dbdc745e-aa7f-476b-980d-420cbb230d8a https://w3id.org/ro-id/0d524bd8-b347-4a5e-b0a8-f4dbeace0aff https://w3id.org/ro-id/7d58605c-b081-4b96-8770-b7cf400c7388 https://w3id.org/ro-id/d40de7fd-c426-4c11-9018-83c788192c59 https://w3id.org/ro-id/fa77f78e-fc12-45f0-8be4-de9545c2c893 https://w3id.org/ro-id/06647fc1-5df8-4592-b4a4-dd63c45d1e00 https://w3id.org/ro-id/1a53393e-e47b-467c-acb0-44c8c45e0a91 https://w3id.org/ro-id/1e495c9d-6fdb-43b9-8962-7306bf69e6ff https://w3id.org/ro-id/28e00251-f8a2-4589-8732-fef6a9d67ad3 https://w3id.org/ro-id/6a8a7e5e-6ff8-49da-85f8-4ec1edaae6b5 https://w3id.org/ro-id/86596d1c-e4bb-4fba-95e6-2c19a2657126 https://w3id.org/ro-id/ebd41fb7-29ba-4525-aac1-35b95d919a5e https://w3id.org/ro-id/38cb87ad-c379-407b-9240-934061ab2ec5 https://w3id.org/ro-id/87b442e6-935e-4262-a9a7-e09eabf8cfb6 https://w3id.org/ro-id/0f6e1d80-8bc3-4d1d-a700-c3bb186e8a28 https://w3id.org/ro-id/515472c2-8f88-42b0-8497-99a54f00eac9 https://w3id.org/ro-id/51b25536-7fe9-42f1-bda6-cb44ebe42ec7 https://w3id.org/ro-id/71890ef5-b2d8-4243-ba31-c13d21e8e8c8 https://w3id.org/ro-id/96bbbf2b-dfb4-4aa6-adf2-8340575e46d3 https://w3id.org/ro-id/49099124-4ecb-4d63-9516-6c14b3787521 https://w3id.org/ro-id/561d75de-a583-441c-bb7b-fbcb20e23c27 Francois Renard. "4D synchrotron X-ray imaging of grain scale deformation mechanisms in a seismogenic gas reservoir sandstone during axial compaction." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/41a50d36-8102-4f0c-a227-3fc44ae00a71. data raw data biblio metadata Renard, F. (2022).4D synchrotron X-ray imaging of grain scale deformation mechanisms in a seismogenic gas reservoir sandstone during axial compaction [Data set]. Norstore. https://doi.org/10.11582/2022.00016 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2022.00016 2022-03-07 00:00:00 2022-03-22 00:38:56.175879+00:00 In-situ X-ray tomography images of the deformation of a core sample of Groningen sandstone (Hades apparatus, beamline ID19, ESRF) 4D synchrotron X-ray imaging of grain scale deformation mechanisms in a seismogenic gas reservoir sandstone during axial compaction 2022-03-07 00:00:00 Francois Renard earth sciences 100.0 0.6915496587753296 In-situ X-ray tomography images of the deformation of a core sample of Groningen sandstone (Hades apparatus, beamline ID19, ESRF) 51.75175175175175 51.7 X-ray tomography image 29.865771812080535 8.9 seismogenic gas reservoir sandstone 10.738255033557047 3.2 4D synchrotron X-ray imaging of grain scale deformation mechanisms in a seismogenic gas reservoir sandstone during axial compaction. 48.248248248248245 48.2 deformation 12.645011600928074 10.9 image 11.994002998500749 8.0 grain scale deformation mechanism 32.88590604026846 9.8 apparatus 4.060324825986079 3.5 Genetics Science and technology/Natural science/Biology/Genetics imaging 23.38830584707646 15.6 geosciences 100.0 0.6389099359512329 core sample 6.0324825986078885 5.2 Groningen https://www.wikidata.org/wiki/Q749 deformation of a core sample of Groningen sandstone 10.738255033557047 3.2 natural gas 5.220417633410673 4.5 imaging 18.329466357308583 15.8 x-ray 9.628770301624131 8.3 Oil and gas - upstream activities Economy, business and finance/Economic sector/Energy and resource/Oil and gas - upstream activities geology 100.0 0.6915496587753296 synchrotron 8.584686774941995 7.4 reservoir 9.5952023988006 6.4 Groningen 3.596287703016241 3.1 geology 100.0 16.7 Medical procedure-test Health/Health treatment/Medical procedure-test sandstone 14.96519721577726 12.9 francois.renard@rohub.com Francois Renard Geo H. Environmental research Neurobiology Life sciences Physical sciences calcium photon http analysis dataset mouse two-photon calcium imaging imaging move mouse calcium imaging computer code information analysis code service-account-enrichment 10761 https://api.rohub.org/api/ros/0c774ee2-aef9-4f41-bc8f-15c244f99ec1/crate/download/ 2022-03-22 00:38:57.172485+00:00 2025-03-05 01:27:08.516180+00:00 2022-03-22 00:38:57.172485+00:00 This dataset contains data presented in the paper "Large-scale two-photon calcium imaging in freely moving mice" Weijian Zong,Horst A. Obenhaus, Emilie R. Skytøen, Hanna Eneqvist, Nienke L. de Jong, Marina R. Jorge, May-Britt Moser, Edvard I. Moser (2022). It is complementary to the analysis code stored at LINK: http://github.com/kavli-ntnu/MINI2P_toolbox application/ld+json https://w3id.org/ro-id/0c774ee2-aef9-4f41-bc8f-15c244f99ec1 Zong 2022 MANUAL Weijian Zong, Horst A. Obenhaus, Emilie Skytøen, Hanna Eneqvist, Nienke de Jong, Marina Jorge, May-Britt Moser, and Edvard Moser. "Zong 2022." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/0c774ee2-aef9-4f41-bc8f-15c244f99ec1. metadata raw data data biblio Zong, W., Obenhaus, H., Skytøen, E., Eneqvist, H., de Jong, N., Jorge, M., Moser, M., Moser, E. (2022).Zong 2022 [Data set]. Norstore. https://doi.org/10.11582/2022.00008 Edvard Ingjald Moser Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2022.00008 2022-02-10 00:00:00 2022-03-22 00:39:38.959576+00:00 This dataset contains data presented in the paper "Large-scale two-photon calcium imaging in freely moving mice" Weijian Zong,Horst A. Obenhaus, Emilie R. Skytøen, Hanna Eneqvist, Nienke L. de Jong, Marina R. Jorge, May-Britt Moser, Edvard I. Moser (2022). It is complementary to the analysis code stored at <a href="http://github.com/kavli-ntnu/MINI2P_toolbox" class="linkified" target="_blank">LINK</a> Zong 2022 2022-02-10 00:00:00 Edvard Ingjald Moser https://doi.org/10.1101/2021.09.20.461015 2022-03-22 00:39:36.559662+00:00 2022-03-22 00:39:36.674275+00:00 https://doi.org/10.1101/2021.09.20.461015 2022-03-22 00:39:36.559662+00:00 HorstA.Obenhaus@rohub.com Horst A. Obenhaus Weijian@hotmail.com Weijian Zong edvard.moser@rohub.com Edvard Moser emilie.skytoen@rohub.com Emilie Skytøen Geo H. hanna.eneqvist@rohub.com Hanna Eneqvist marina.jorge@rohub.com Marina Jorge may-britt.moser@rohub.com May-Britt Moser nienke.de.jong@rohub.com Nienke de Jong Applied sciences service-account-enrichment 7960 https://api.rohub.org/api/ros/a64cc611-d619-492b-9ceb-8bfa66f392d0/crate/download/ 2022-03-22 00:39:39.965760+00:00 2025-03-05 12:49:07.220293+00:00 2022-03-22 00:39:39.965760+00:00 This Excel spreadsheet contains data on the Nutrient optimised beef enhances blood levels of vitamin D and Selenium amount young women. application/ld+json https://w3id.org/ro-id/a64cc611-d619-492b-9ceb-8bfa66f392d0 Nutrient optimised beef enhances blood levels of vitamin D and Selenium amount young women MANUAL Excel beef data lineage miss quantity spreadsheet vitamin D earth sciences Food and drink Food Excel beef blood data spreadsheet vitamin D young woman life sciences Excel spreadsheet blood levels of vitamin D contain data optimised beef selenium amount young women Nutrient optimised beef enhances blood levels of vitamin D and Selenium amount young women. This Excel spreadsheet contains data on the Nutrient optimised beef enhances blood levels of vitamin D and Selenium amount young women. office productivity software Anna Haug. "Nutrient optimised beef enhances blood levels of vitamin D and Selenium amount young women." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/a64cc611-d619-492b-9ceb-8bfa66f392d0. data raw data metadata biblio Haug, A. (2022).Nutrient optimised beef enhances blood levels of vitamin D and Selenium amount young women [Data set]. Norstore. https://doi.org/10.11582/2022.00007 Bjørg Egelandsdal Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2022.00007 2022-02-08 00:00:00 2022-03-22 00:39:51.183359+00:00 This Excel spreadsheet contains data on the Nutrient optimised beef enhances blood levels of vitamin D and Selenium amount young women. Nutrient optimised beef enhances blood levels of vitamin D and Selenium amount young women 2022-02-08 00:00:00 Bjørg Egelandsdal anna.haug@rohub.com Anna Haug Geo H. Environmental research Neurobiology Life sciences Physical sciences service-account-enrichment 11738 https://api.rohub.org/api/ros/55007a51-6a9a-45a9-841d-bbf0d589abf7/crate/download/ 2022-03-22 00:39:52.337240+00:00 2025-03-05 12:49:07.354571+00:00 2022-03-22 00:39:52.337240+00:00 This dataset contains data presented in the paper "Functional network topography of the medial entorhinal cortex" by Horst A. Obenhaus, Weijian Zong, R. Irene Jacobsen, Tobias Rose, Flavio Donato, Liangyi Chen, Heping Cheng, Tobias Bonhoeffer, May-Britt Moser, Edvard I. Moser (2022) We refer to the readme file uploaded with this data for descriptions on how to use the data. LINK: http://github.com/kavli-ntnu/mini2p_topography application/ld+json https://w3id.org/ro-id/55007a51-6a9a-45a9-841d-bbf0d589abf7 Obenhaus2022 MANUAL README file communications network cortices data dataset information paper topography earth sciences Animal Geography IT-computer sciences Horst A. Obenhaus Weijian Zong data dataset network readme file topography geosciences contain data data for description entorhinal cortex network topography refer to the readme file LINK: http: github.com/kavli-ntnu/mini2p_topography This dataset contains data presented in the paper "Functional network topography of the medial entorhinal cortex" by Horst A. Obenhaus, Weijian Zong, R. Irene Jacobsen, Tobias Rose, Flavio Donato, Liangyi Chen, We refer to the readme file uploaded with this data for descriptions on how to use the data. 2022 computer science database information technology Horst A. Obenhaus, Weijian Zong, Ragnhild Irene Jacobsen, Tobias Rose, Flavio Donato, Liangyi Chen, Heping Cheng, Tobias Bonhoeffer, May-Britt Moser, and Edvard Ingjald Moser. "Obenhaus2022." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/55007a51-6a9a-45a9-841d-bbf0d589abf7. biblio data raw data metadata Obenhaus, H. A., Zong, W., Jacobsen, R. I., Rose, T., Donato, F., Chen, L., Cheng, H., Bonhoeffer, T., Moser, M., Moser, E. I. (2022).Obenhaus2022 [Data set]. Norstore. https://doi.org/10.11582/2022.00005 Edvard Ingjald Moser Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2022.00005 2022-01-27 00:00:00 2022-03-22 00:40:42.910252+00:00 This dataset contains data presented in the paper "Functional network topography of the medial entorhinal cortex" by Horst A. Obenhaus, Weijian Zong, R. Irene Jacobsen, Tobias Rose, Flavio Donato, Liangyi Chen, Heping Cheng, Tobias Bonhoeffer, May-Britt Moser, Edvard I. Moser (2022) We refer to the readme file uploaded with this data for descriptions on how to use the data. <a href="http://github.com/kavli-ntnu/mini2p_topography" class="linkified" target="_blank">LINK</a> Obenhaus2022 2022-01-27 00:00:00 Edvard Ingjald Moser Weijian@hotmail.com Weijian Zong edvard.ingjald.moser@rohub.com Edvard Ingjald Moser flavio.donato@rohub.com Flavio Donato Geo H. heping.cheng@rohub.com Heping Cheng horst.a.obenhaus@rohub.com Horst A. Obenhaus liangyi.chen@rohub.com Liangyi Chen may-britt.moser@rohub.com May-Britt Moser ragnhild.irene.jacobsen@rohub.com Ragnhild Irene Jacobsen tobias.bonhoeffer@rohub.com Tobias Bonhoeffer tobias.rose@rohub.com Tobias Rose Environmental research Neurobiology Life sciences Physical sciences recordings from 2-photon microscopy Begonia imaging library animal photon Alzheimer's data microscopy dataset raw data data library upload mouse transgenic mouse imaging pupil movement data recording datum conduct tg-ArcSwe Alzheimer's disease service-account-enrichment 8165 https://api.rohub.org/api/ros/590c074e-60c7-4096-bdb5-5d018b25538f/crate/download/ 2022-03-22 00:40:44.005873+00:00 2025-03-05 00:50:08.665153+00:00 2022-03-22 00:40:44.005873+00:00 (Note: Publication in review at time of upload) Datatypes: Recordings from 2-photon microscopy, behaviour and pupil movement data. HDF5 (see note on compatibility), CSV, MP4 and others. Subjects: tg-ArcSwe Alzheimer's disease model mice at 15-18 months. Animals awake during experiments. State: Derived and raw data. Data is prepared and processed with the Begonia imaging library. application/ld+json https://w3id.org/ro-id/590c074e-60c7-4096-bdb5-5d018b25538f Dataset for "Impaired astrocytic Ca2+ signalling in awake Alzheimer's disease transgenic mice" MANUAL GliaLab (GliaLab). "Dataset for "Impaired astrocytic Ca2+ signalling in awake Alzheimer's disease transgenic mice"." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/590c074e-60c7-4096-bdb5-5d018b25538f. data metadata biblio raw data GliaLab (2021).Dataset for "Impaired astrocytic Ca2+ signalling in awake Alzheimer's disease transgenic mice" [Data set]. Norstore. https://doi.org/10.11582/2021.00100 Rune Enger Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00100 2021-11-20 00:00:00 2022-03-22 00:40:55.789993+00:00 (Note: Publication in review at time of upload) Datatypes: Recordings from 2-photon microscopy, behaviour and pupil movement data. HDF5 (see note on compatibility), CSV, MP4 and others. Subjects: tg-ArcSwe Alzheimer's disease model mice at 15-18 months. Animals awake during experiments. State: Derived and raw data. Data is prepared and processed with the Begonia imaging library. Dataset for "Impaired astrocytic Ca2+ signalling in awake Alzheimer's disease transgenic mice" 2021-11-20 00:00:00 Rune Enger GliaLab@rohub.com GliaLab (GliaLab) Geo H. Environmental research Life sciences Physical sciences Earth sciences vette fault gouge data on laboratory Direct Shear Testing thesis document geology carbon dioxide http data geological fault dataset fault slip implication gouge thesis bet fault implication thesis storage slip potential CO2 storage service-account-enrichment 7440 https://api.rohub.org/api/ros/9cb2a7a6-8dca-4520-b7df-7e5234d2c194/crate/download/ 2022-03-22 00:40:56.716512+00:00 2025-03-05 00:50:42.658583+00:00 2022-03-22 00:40:56.716512+00:00 This dataset contains data on laboratory Direct Shear Testing performed in 2020-2021 on material analogous to the Vette fault gouge (Smeaheia), with applications for Carbon Storage. The resulting thesis can be found here: LINK: http://urn.nb.no/URN:NBN:no-89352 For more details please refer to the thesis document and README file contained in the dataset. application/ld+json https://w3id.org/ro-id/9cb2a7a6-8dca-4520-b7df-7e5234d2c194 Experimental study addressing fault slip Implications for derisking of the Smeaheia potential CO2 storage site MANUAL Diana Carolina Alves Da Silva. "Experimental study addressing fault slip Implications for derisking of the Smeaheia potential CO2 storage site." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/9cb2a7a6-8dca-4520-b7df-7e5234d2c194. raw data metadata biblio data Alves Da Silva, D. C. (2021).Experimental study addressing fault slip Implications for derisking of the Smeaheia potential CO2 storage site [Data set]. Norstore. https://doi.org/10.11582/2021.00093 Diana Carolina Alves Da Silva Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00093 2021-10-27 00:00:00 2022-03-22 00:41:08.944218+00:00 This dataset contains data on laboratory Direct Shear Testing performed in 2020-2021 on material analogous to the Vette fault gouge (Smeaheia), with applications for Carbon Storage. The resulting thesis can be found here: <a href="http://urn.nb.no/URN:NBN:no-89352" class="linkified" target="_blank">LINK</a> For more details please refer to the thesis document and README file contained in the dataset. Experimental study addressing fault slip Implications for derisking of the Smeaheia potential CO2 storage site 2021-10-27 00:00:00 Michael Heeremans diana.carolina.alves.da.silva@rohub.com Diana Carolina Alves Da Silva Geo H. Environmental research Life sciences Physical sciences Earth sciences profiles of the talus Norway talus LG Corporation Norway rockfall rockfall talus measurement Davegaarden measurements measurement talus measurements measurement measure profile Lærdal Gård service-account-enrichment 7281 https://api.rohub.org/api/ros/80092230-08cd-4164-97d3-74a747d7606e/crate/download/ 2022-03-22 00:41:10.367174+00:00 2025-03-05 01:24:09.917952+00:00 2022-03-22 00:41:10.367174+00:00 Measurements from four rockfall taluses in Lærdal and Aurland, Norway. Bo: Bø, DG: Davegaarden, LG: Lærdal Gård. Measurements were collected along profiles of the talus. application/ld+json https://w3id.org/ro-id/80092230-08cd-4164-97d3-74a747d7606e Talus measurements MANUAL Elise Morken. "Talus measurements." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/80092230-08cd-4164-97d3-74a747d7606e. raw data data metadata biblio Morken, E. (2021).Talus measurements [Data set]. Norstore. https://doi.org/10.11582/2021.00080 Elise Morken Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00080 2021-09-29 00:00:00 2022-03-22 00:41:19.737272+00:00 Measurements from four rockfall taluses in Lærdal and Aurland, Norway. Bo: Bø, DG: Davegaarden, LG: Lærdal Gård. Measurements were collected along profiles of the talus. Talus measurements 2021-09-29 00:00:00 Elise Morken elise.morken@rohub.com Elise Morken Geo H. Environmental research Life sciences Physical sciences service-account-enrichment 7713 https://api.rohub.org/api/ros/0d8bd106-97fd-43c2-86ed-1e8243f432bd/crate/download/ 2022-03-22 00:41:21.899171+00:00 2025-03-05 00:45:29.161091+00:00 2022-03-22 00:41:21.899171+00:00 original experiment data, documents, manuscript for the publication application/ld+json https://w3id.org/ro-id/0d8bd106-97fd-43c2-86ed-1e8243f432bd 2014_Tiwari_Fuglebakk_etal_BMC_Bioinfo MANUAL https://w3id.org/ro-id/1aa2c46d-be80-4298-a0a5-5bda68e7063f https://w3id.org/ro-id/628d0049-0560-4516-9822-4cec1e7350f7 https://w3id.org/ro-id/7cbf4a8a-c0e1-412e-b92c-d70be1c8064e https://w3id.org/ro-id/adf67e8e-8e1d-4ac7-b6bd-e734c9465e8b https://w3id.org/ro-id/cc052c5e-089d-488f-a641-810d8f7966be https://w3id.org/ro-id/533a140f-dde4-444e-91bf-b0399c83081f https://w3id.org/ro-id/f2351ab7-1d10-4135-8c66-1f36ba31a829 https://w3id.org/ro-id/d7a0608d-160c-4a78-bdc6-fa2caf6e6ded https://w3id.org/ro-id/0fdf9212-d8ca-4a37-a787-d9ff88d56e2d https://w3id.org/ro-id/1e0d4893-caed-4e69-af48-c4c980a4ec20 https://w3id.org/ro-id/970ec352-4b67-40ca-a5c9-0ee7cfdc2e53 https://w3id.org/ro-id/f240e3bc-3fe7-4b79-81ba-890997962d20 https://w3id.org/ro-id/f7d8e2be-55bb-4a2d-bd0a-311502b63056 https://w3id.org/ro-id/8abe483d-8e39-40be-825b-8da92cae89c4 https://w3id.org/ro-id/8d586b11-8917-4d6e-98b8-fb9eace53b77 https://w3id.org/ro-id/9c14bc16-297a-4135-a6cc-91570d71723f https://w3id.org/ro-id/ab7e274a-43d7-4b9f-84bb-bfefbaed0681 https://w3id.org/ro-id/c839f19e-55b7-4ecc-91c0-e57fbdb91d70 https://w3id.org/ro-id/3ad239ef-93bf-469d-bb67-c39e7d1941a3 Nathalie Reuter. "2014_Tiwari_Fuglebakk_etal_BMC_Bioinfo." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/0d8bd106-97fd-43c2-86ed-1e8243f432bd. metadata biblio raw data data https://doi.org/10.1186/s12859-014-0427-6 2022-03-22 00:41:32.578667+00:00 2022-03-22 00:41:32.697372+00:00 https://doi.org/10.1186/s12859-014-0427-6 2022-03-22 00:41:32.578667+00:00 Reuter, N. (2021).2014_Tiwari_Fuglebakk_etal_BMC_Bioinfo [Data set]. Norstore. https://doi.org/10.11582/2021.00074 Nathalie Reuter Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00074 2021-09-21 00:00:00 2022-03-22 00:41:35.599728+00:00 original experiment data, documents, manuscript for the publication 2014_Tiwari_Fuglebakk_etal_BMC_Bioinfo 2021-09-21 00:00:00 Nathalie Reuter experiment 14.844533600802407 14.8 manuscript 21.450151057401815 21.3 publication 18.956870611835505 18.9 2014_Tiwari_Fuglebakk_etal_BMC_Bioinfo. original experiment data, documents, manuscript for the publication 100.0 100.0 earth sciences 100.0 0.9590817093849182 datum 27.089627391742198 26.9 experiment 14.702920443101712 14.6 life sciences 100.0 0.7785815596580505 life sciences (general) 100.0 0.7785815596580505 document 16.75025075225677 16.7 experiment datum 77.27727727727728 77.2 manuscript for the publication 18.21821821821822 18.2 publication 19.738167170191343 19.6 original experiment datum 4.504504504504505 4.5 document 17.019133937562938 16.9 Book industry Economy, business and finance/Economic sector/Media/Book industry geology 100.0 0.9590817093849182 manuscript 21.063189568706118 21.0 datum 28.385155466399198 28.3 Geo H. nathalie.reuter@rohub.com Nathalie Reuter Environmental research Life sciences Physical sciences Earth sciences service-account-enrichment 7623 https://api.rohub.org/api/ros/c9365b2c-cc7a-48b2-bb8c-5189fefbff94/crate/download/ 2022-03-22 00:41:36.704625+00:00 2025-03-05 00:47:49.207732+00:00 2022-03-22 00:41:36.704625+00:00 Results of direct shear tests on samples of plaster and sandstone. application/ld+json https://w3id.org/ro-id/c9365b2c-cc7a-48b2-bb8c-5189fefbff94 Direct Shear Data MANUAL information plaster result sample sandstone shearing machine testing earth sciences Textile and clothing data plaster result sample sandstone shear test engineering direct shear data direct shear test samples of plaster and sandstone shear data shear test Direct Shear Data. Results of direct shear tests on samples of plaster and sandstone. construction industry Tord Alexander Buvik. "Direct Shear Data." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/c9365b2c-cc7a-48b2-bb8c-5189fefbff94. data metadata raw data biblio Buvik, T. A. (2021).Direct Shear Data [Data set]. Norstore. https://doi.org/10.11582/2021.00073 Tord Alexander Buvik Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00073 2021-09-16 00:00:00 2022-03-22 00:41:52.326175+00:00 Results of direct shear tests on samples of plaster and sandstone. Direct Shear Data 2021-09-16 00:00:00 Tord Alexander Buvik Geo H. tord.alexander.buvik@rohub.com Tord Alexander Buvik Environmental research Life sciences Physical sciences Medical science images from confocal microscopy ultrasound technique ultrasound image medicine radiology ultrasound image imaging microscopy system bubble pulse in vivo image PLOS technique for imaging thick service-account-enrichment 7882 https://api.rohub.org/api/ros/8fafb8df-d1d5-467b-b8f7-6e36b3de25d0/crate/download/ 2022-03-22 00:41:53.590185+00:00 2025-03-05 00:46:17.038419+00:00 2022-03-22 00:41:53.590185+00:00 Images from confocal microscopy and ultrasound images which is used in the paper "A multi-pulse ultrasound technique for imaging of thick-shelled microbubbles demonstrated in vitro and in vivo" which is to be submitted to PLOS One. application/ld+json https://w3id.org/ro-id/8fafb8df-d1d5-467b-b8f7-6e36b3de25d0 A multi-pulse ultrasound technique for imaging of thick-shelled microbubbles demonstrated in vitro and in vivo MANUAL Sigrid Berg. "A multi-pulse ultrasound technique for imaging of thick-shelled microbubbles demonstrated in vitro and in vivo." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/8fafb8df-d1d5-467b-b8f7-6e36b3de25d0. raw data metadata biblio data Berg, S. (2021).A multi-pulse ultrasound technique for imaging of thick-shelled microbubbles demonstrated in vitro and in vivo [Data set]. Norstore. https://doi.org/10.11582/2021.00072 Sigrid Berg Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00072 2021-09-06 00:00:00 2022-03-22 00:42:05.636673+00:00 Images from confocal microscopy and ultrasound images which is used in the paper "A multi-pulse ultrasound technique for imaging of thick-shelled microbubbles demonstrated in vitro and in vivo" which is to be submitted to PLOS One. A multi-pulse ultrasound technique for imaging of thick-shelled microbubbles demonstrated in vitro and in vivo 2021-09-06 00:00:00 Sigrid Berg Geo H. sigrid.berg@rohub.com Sigrid Berg Environmental research Life sciences Physical sciences information technology magnetic disturbance evaluation transfer learning accompanying publication data image preprint persona dataset processed file version of the article method valuation learning model explanation solution magnetic disturbance peer publication service-account-enrichment 7623 https://api.rohub.org/api/ros/e3dfa3c8-4303-4bfb-af43-5eed9d51bdab/crate/download/ 2022-03-22 00:42:06.855630+00:00 2025-03-05 02:46:56.033478+00:00 2022-03-22 00:42:06.855630+00:00 We show that transfer learning can be easily applied to all sky images for the purpose of classifying images, filtering images and predicting magnetic disturbance from auroral images. In the accompanying publication we describe our methods and show the results that we obtained. Version 1 of the dataset corresponds to the preprint, Version 2 to the peer reviewed version of the article. This dataset contains the processed files that can be used to replicate our results. Instructions how to apply the data and on the accompanying code can be found here: LINK: http://tid.uio.no/TAME/ application/ld+json https://w3id.org/ro-id/e3dfa3c8-4303-4bfb-af43-5eed9d51bdab Transfer Learning Aurora Image Classification and Magnetic Disturbance Evaluation (TAME) MANUAL Pascal Sado. "Transfer Learning Aurora Image Classification and Magnetic Disturbance Evaluation (TAME)." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/e3dfa3c8-4303-4bfb-af43-5eed9d51bdab. raw data data metadata biblio https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00071 2022-03-22 00:42:15.866064+00:00 2022-03-22 00:42:21.085814+00:00 We show that transfer learning can be easily applied to all sky images for the purpose of classifying images, filtering images and predicting magnetic disturbance from auroral images. In the accompanying publication we describe our methods and show the results that we obtained. Version 1 of the dataset corresponds to the preprint, Version 2 to the peer reviewed version of the article. This dataset contains the processed files that can be used to replicate our results. Instructions how to apply the data and on the accompanying code can be found here: <a href="http://tid.uio.no/TAME/" class="linkified" target="_blank">LINK</a> Transfer Learning Aurora Image Classification and Magnetic Disturbance Evaluation (TAME) 2022-03-22 00:42:15.866064+00:00 https://doi.org/10.1029/2021JA029683 2022-03-22 00:42:18.373699+00:00 2022-03-22 00:42:18.491506+00:00 https://doi.org/10.1029/2021JA029683 2022-03-22 00:42:18.373699+00:00 Geo H. pascal.sado@rohub.com Pascal Sado Environmental research Life sciences Physical sciences plasma density electron frequency rocket data plasma file article editorial dataset electron density tailspin launch density density dataset consist referenced article rocket spin frequency service-account-enrichment 7927 https://api.rohub.org/api/ros/647beba0-6d23-4fad-a0a3-3087817e7407/crate/download/ 2022-03-22 00:42:23.106410+00:00 2025-03-05 00:53:51.453498+00:00 2022-03-22 00:42:23.106410+00:00 This dataset consists of a single ASCII formatted file containing the electron densities derived from the multi-Needle Langmuir Probe (m-NLP) measurements on board the ICI-3 rocket. More information about how the densities were calculated can be found in the referenced article. The first column contains the time after launch in units of s, the second column contains the plasma density in m^{-3}. It should be noted that the data was filtered with a notch filter in order to remove the rocket spin frequency and its first 3 harmonics. application/ld+json https://w3id.org/ro-id/647beba0-6d23-4fad-a0a3-3087817e7407 ICI-3 electron density (spin filtered) MANUAL Lasse Clausen. "ICI-3 electron density (spin filtered)." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/647beba0-6d23-4fad-a0a3-3087817e7407. biblio raw data data metadata Clausen, L. (2021).ICI-3 electron density (spin filtered) [Data set]. Norstore. https://doi.org/10.11582/2021.00060 Lasse Clausen Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00060 2021-07-02 00:00:00 2022-03-22 00:42:36.018313+00:00 This dataset consists of a single ASCII formatted file containing the electron densities derived from the multi-Needle Langmuir Probe (m-NLP) measurements on board the ICI-3 rocket. More information about how the densities were calculated can be found in the referenced article. The first column contains the time after launch in units of s, the second column contains the plasma density in m^{-3}. It should be noted that the data was filtered with a notch filter in order to remove the rocket spin frequency and its first 3 harmonics. ICI-3 electron density (spin filtered) 2021-07-02 00:00:00 Lasse Clausen https://doi.org/10.1002/2016JA022999 2022-03-22 00:42:33.088884+00:00 2022-03-22 00:42:33.191876+00:00 https://doi.org/10.1002/2016JA022999 2022-03-22 00:42:33.088884+00:00 Geo H. lasse.clausen@rohub.com Lasse Clausen Environmental research Life sciences Physical sciences plasma density refereced article electron frequency rocket data plasma file article editorial dataset electron density tailspin launch density density dataset consist rocket spin frequency service-account-enrichment 7932 https://api.rohub.org/api/ros/4bdaf37c-16e6-412d-899e-d651e7981e60/crate/download/ 2022-03-22 00:42:37.442231+00:00 2025-03-05 00:53:51.220248+00:00 2022-03-22 00:42:37.442231+00:00 This dataset consists of a single ASCII formatted file containing the electron densities derived from the multi-Needle Langmuir Probe (m-NLP) measurements on board the ICI-2 rocket. More information about how the densities were calculated can be found in the refereced article. The first column contains the time after launch in units of s, the second column contains the plasma density in m^{-3}. It should be noted that the data was filtered with a notch filter in order to remove the rocket spin frequency and its first 3 harmonics. application/ld+json https://w3id.org/ro-id/4bdaf37c-16e6-412d-899e-d651e7981e60 ICI-2 electron density (spin filtered) MANUAL Lasse Clausen. "ICI-2 electron density (spin filtered)." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/4bdaf37c-16e6-412d-899e-d651e7981e60. biblio raw data metadata data https://doi.org/10.1029/2012GL051407 2022-03-22 00:42:48.082310+00:00 2022-03-22 00:42:48.192043+00:00 https://doi.org/10.1029/2012GL051407 2022-03-22 00:42:48.082310+00:00 Clausen, L. (2021).ICI-2 electron density (spin filtered) [Data set]. Norstore. https://doi.org/10.11582/2021.00059 Lasse Clausen Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00059 2021-07-02 00:00:00 2022-03-22 00:42:52.544077+00:00 This dataset consists of a single ASCII formatted file containing the electron densities derived from the multi-Needle Langmuir Probe (m-NLP) measurements on board the ICI-2 rocket. More information about how the densities were calculated can be found in the refereced article. The first column contains the time after launch in units of s, the second column contains the plasma density in m^{-3}. It should be noted that the data was filtered with a notch filter in order to remove the rocket spin frequency and its first 3 harmonics. ICI-2 electron density (spin filtered) 2021-07-02 00:00:00 Lasse Clausen Geo H. lasse.clausen@rohub.com Lasse Clausen Environmental research Life sciences Physical sciences information technology magnetic disturbance evaluation transfer learning accompanying publication data image preprint persona dataset processed file version of the article method valuation learning model explanation solution magnetic disturbance peer publication service-account-enrichment 9210 https://api.rohub.org/api/ros/2cc7cda2-a3db-4646-ad31-2580a4a45f85/crate/download/ 2022-03-22 00:42:53.625315+00:00 2025-03-05 02:46:56.257392+00:00 2022-03-22 00:42:53.625315+00:00 We show that transfer learning can be easily applied to all sky images for the purpose of classifying images, filtering images and predicting magnetic disturbance from auroral images. In the accompanying publication we describe our methods and show the results that we obtained. Version 1 of the dataset corresponds to the preprint, Version 2 to the peer reviewed version of the article. This dataset contains the processed files that can be used to replicate our results. Instructions how to apply the data and on the accompanying code can be found here: LINK: http://tid.uio.no/TAME/ application/ld+json https://w3id.org/ro-id/2cc7cda2-a3db-4646-ad31-2580a4a45f85 Transfer Learning Aurora Image Classification and Magnetic Disturbance Evaluation (TAME) MANUAL Pascal Sado. "Transfer Learning Aurora Image Classification and Magnetic Disturbance Evaluation (TAME)." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/2cc7cda2-a3db-4646-ad31-2580a4a45f85. raw data biblio metadata data Sado, P. (2021).Transfer Learning Aurora Image Classification and Magnetic Disturbance Evaluation (TAME) [Data set]. Norstore. https://doi.org/10.11582/2021.00071 Pascal Sado Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00057 2021-06-16 00:00:00 2022-03-22 00:43:05.148572+00:00 We show that transfer learning can be easily applied to all sky images for the purpose of classifying images, filtering images and predicting magnetic disturbance from auroral images. In the accompanying publication we describe our methods and show the results that we obtained. Version 1 of the dataset corresponds to the preprint, Version 2 to the peer reviewed version of the article. This dataset contains the processed files that can be used to replicate our results. Instructions how to apply the data and on the accompanying code can be found here: <a href="http://tid.uio.no/TAME/" class="linkified" target="_blank">LINK</a> Transfer Learning Aurora Image Classification and Magnetic Disturbance Evaluation (TAME) 2021-06-16 00:00:00 Pascal Sado Geo H. pascal.sado@rohub.com Pascal Sado Environmental research Life sciences Physical sciences Earth sciences Pinatubo forcing Mt Pinatubo eruption meteorology NorESM output agriculture mean field simulation ensemble experiment field computer modelling eruption uncertainty dataset output proxy end product forcing climate prediction analogy ensemble service-account-enrichment 8135 https://api.rohub.org/api/ros/657fb2f6-a440-4887-81e3-7613f4af8517/crate/download/ 2022-03-22 00:43:06.401309+00:00 2025-03-05 12:49:05.212928+00:00 2022-03-22 00:43:06.401309+00:00 This dataset contains post-processed output from a study with the Norwegian Earth System Model (NorESM) that uses proxy-based stochastic volcanic forcing to assess the effects of volcanic uncertainty on probabilistic 21st century climate projections (Bethke et al. 2017). This particular dataset contains output from a supporting experiment that comprises two historical 60-member simulation ensembles with and without 1991-Mt Pinatubo forcing and temporal coverage 1990-2005. The output contains a range of standard monthly mean fields and selected daily mean fields for addressing monsoon related aspects. application/ld+json https://w3id.org/ro-id/657fb2f6-a440-4887-81e3-7613f4af8517 NorESM output from simulations with and without Mt Pinatubo eruption MANUAL Ingo Bethke. "NorESM output from simulations with and without Mt Pinatubo eruption." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/657fb2f6-a440-4887-81e3-7613f4af8517. biblio data raw data metadata https://doi.org/10.1038/nclimate3394 2022-03-22 00:43:16.261976+00:00 2022-03-22 00:43:16.370207+00:00 https://doi.org/10.1038/nclimate3394 2022-03-22 00:43:16.261976+00:00 Bethke, I. (2021).NorESM output from simulations with and without Mt Pinatubo eruption [Data set]. Norstore. https://doi.org/10.11582/2021.00051 Ingo Bethke Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00051 2021-05-28 00:00:00 2022-03-22 00:43:19.392575+00:00 This dataset contains post-processed output from a study with the Norwegian Earth System Model (NorESM) that uses proxy-based stochastic volcanic forcing to assess the effects of volcanic uncertainty on probabilistic 21st century climate projections (Bethke et al. 2017). This particular dataset contains output from a supporting experiment that comprises two historical 60-member simulation ensembles with and without 1991-Mt Pinatubo forcing and temporal coverage 1990-2005. The output contains a range of standard monthly mean fields and selected daily mean fields for addressing monsoon related aspects. NorESM output from simulations with and without Mt Pinatubo eruption 2021-05-28 00:00:00 Ingo Bethke Geo H. ingo.bethke@rohub.com Ingo Bethke Environmental research Life sciences Physical sciences Biology Medical science receptor data specification file file antigen fact input/output dataset antigen specificity guideline receptor specificity input/output output file learning output file information immuneML use case 2 service-account-enrichment 8013 https://api.rohub.org/api/ros/dfece22d-4a22-4a58-81e6-b42fd4c66728/crate/download/ 2022-03-22 00:43:20.656579+00:00 2025-03-05 00:53:54.291837+00:00 2022-03-22 00:43:20.656579+00:00 This dataset contains the data, original specification files, GLIPH2 input/output files and complete results for immuneML use case 2: Extending immuneML with a deep learning component for predicting antigen specificity of paired receptor data. To use the dataset you should follow the guidelines in the README.txt file contained within the dataset. application/ld+json https://w3id.org/ro-id/dfece22d-4a22-4a58-81e6-b42fd4c66728 immuneML use case 2: Extending immuneML with a deep learning component for predicting antigen specificity of paired receptor data MANUAL Milena Pavlović. "immuneML use case 2: Extending immuneML with a deep learning component for predicting antigen specificity of paired receptor data." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/dfece22d-4a22-4a58-81e6-b42fd4c66728. metadata raw data data biblio Pavlović, M. (2021).immuneML use case 2: Extending immuneML with a deep learning component for predicting antigen specificity of paired receptor data [Data set]. Norstore. https://doi.org/10.11582/2021.00009 Lonneke Scheffer Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00009 2021-02-16 00:00:00 2022-03-22 00:43:31.859965+00:00 This dataset contains the data, original specification files, GLIPH2 input/output files and complete results for immuneML use case 2: Extending immuneML with a deep learning component for predicting antigen specificity of paired receptor data. To use the dataset you should follow the guidelines in the README.txt file contained within the dataset. immuneML use case 2: Extending immuneML with a deep learning component for predicting antigen specificity of paired receptor data 2021-02-16 00:00:00 Lonneke Scheffer Geo H. milena.pavlovic@rohub.com Milena Pavlović Environmental research Life sciences Physical sciences Biology Medical science replication of a published study specification file immuneML file dataset guideline dataset use the dataset README.txt file study reproduction immuneML use case 1 service-account-enrichment 7754 https://api.rohub.org/api/ros/2243f9c9-5c9d-4ad1-8219-a6daed0a7d4f/crate/download/ 2022-03-22 00:43:32.837367+00:00 2025-03-05 00:53:54.083290+00:00 2022-03-22 00:43:32.837367+00:00 This dataset contains the original specification files and complete results for immuneML use case 1: Replication of a published study inside immuneML. To use the dataset you should follow the guidelines in the README.txt file contained within the dataset. application/ld+json https://w3id.org/ro-id/2243f9c9-5c9d-4ad1-8219-a6daed0a7d4f immuneML use case 1: Replication of a published study inside immuneML. MANUAL Milena Pavlović. "immuneML use case 1: Replication of a published study inside immuneML.." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/2243f9c9-5c9d-4ad1-8219-a6daed0a7d4f. biblio raw data metadata data Pavlović, M. (2021).immuneML use case 1: Replication of a published study inside immuneML. [Data set]. Norstore. https://doi.org/10.11582/2021.00008 Lonneke Scheffer Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00008 2021-02-16 00:00:00 2022-03-22 00:43:48.054345+00:00 This dataset contains the original specification files and complete results for immuneML use case 1: Replication of a published study inside immuneML. To use the dataset you should follow the guidelines in the README.txt file contained within the dataset. immuneML use case 1: Replication of a published study inside immuneML. 2021-02-16 00:00:00 Lonneke Scheffer Geo H. milena.pavlovic@rohub.com Milena Pavlović Environmental research Life sciences Physical sciences Earth sciences tomography dataset X-ray tomography data x-ray granite sample voxel synchrotron imaging dataset resolution synchrotron X-ray tomography data datasets of a westerly granite sample information micrometers voxel size spatial service-account-enrichment 7825 https://api.rohub.org/api/ros/5c79fe26-7465-4493-875a-9bb44ddcf2ad/crate/download/ 2022-03-22 00:43:49.117619+00:00 2025-03-05 01:24:09.547783+00:00 2022-03-22 00:43:49.117619+00:00 Synchrotron X-ray tomography data of a Westerly granite acquired at two spatial resolutions on beamline ID19 at ESRF application/ld+json https://w3id.org/ro-id/5c79fe26-7465-4493-875a-9bb44ddcf2ad Synchrotron X-ray microtomography datasets of a Westerly granite sample acquired at two spatial resolutions (6.5 and 0.65 micrometers voxel size) MANUAL Francois Renard. "Synchrotron X-ray microtomography datasets of a Westerly granite sample acquired at two spatial resolutions (6.5 and 0.65 micrometers voxel size)." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/5c79fe26-7465-4493-875a-9bb44ddcf2ad. raw data metadata biblio data Renard, F. (2021).Synchrotron X-ray microtomography datasets of a Westerly granite sample acquired at two spatial resolutions (6.5 and 0.65 micrometers voxel size) [Data set]. Norstore. https://doi.org/10.11582/2021.00007 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00007 2021-02-15 00:00:00 2022-03-22 00:44:00.827454+00:00 Synchrotron X-ray tomography data of a Westerly granite acquired at two spatial resolutions on beamline ID19 at ESRF Synchrotron X-ray microtomography datasets of a Westerly granite sample acquired at two spatial resolutions (6.5 and 0.65 micrometers voxel size) 2021-02-15 00:00:00 Francois Renard francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences Earth sciences X-ray tomography data radiology x-ray granite data sample time series imaging time series of tomogram tomography data tomogram Dynamic X-ray tomography experiment experiment samples of Westerley Granite service-account-enrichment 7551 https://api.rohub.org/api/ros/1e9c8d62-dc10-4228-acbb-686d3f48058f/crate/download/ 2022-03-22 00:44:04.365360+00:00 2025-03-05 01:27:07.731759+00:00 2022-03-22 00:44:04.365360+00:00 Dynamic X-ray tomography experiments on three samples of Westerley Granite (WG01, WG02, WG04). Data correspond to time series of tomograms application/ld+json https://w3id.org/ro-id/1e9c8d62-dc10-4228-acbb-686d3f48058f X-ray tomography data of Westerley granite MANUAL Francois Renard. "X-ray tomography data of Westerley granite." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/1e9c8d62-dc10-4228-acbb-686d3f48058f. biblio data raw data metadata Renard, F. (2021).X-ray tomography data of Westerley granite [Data set]. Norstore. https://doi.org/10.11582/2021.00002 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00002 2021-01-13 00:00:00 2022-03-22 00:44:16.262608+00:00 Dynamic X-ray tomography experiments on three samples of Westerley Granite (WG01, WG02, WG04). Data correspond to time series of tomograms X-ray tomography data of Westerley granite 2021-01-13 00:00:00 Francois Renard francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences Earth sciences Anstrude limestone geology rock music sandstone limestone experiment time series physics imaging reservoir rock imaging archive rock samples of Adamswiller sandstone onset mineralogy strain localization locating rock physics experiment Bentheim sandstone service-account-enrichment 7443 https://api.rohub.org/api/ros/556f8bc4-2d71-4b30-bed4-4c2d2e48527f/crate/download/ 2022-03-22 00:44:17.587055+00:00 2025-03-05 01:24:09.161613+00:00 2022-03-22 00:44:17.587055+00:00 The archive contains time series of X-ray tomography rock physics experiments on 7 rock samples of Adamswiller sandstone (ADAM01), Bentheim sandstone (BEN1), Anstrude limestone (ANS2, ANS3, ANS4, ANS5, ANS6) application/ld+json https://w3id.org/ro-id/556f8bc4-2d71-4b30-bed4-4c2d2e48527f Synchrotron 4D X-ray imaging reveals strain localization at the onset of system-size failure of porous reservoir rocks MANUAL Francois Renard. "Synchrotron 4D X-ray imaging reveals strain localization at the onset of system-size failure of porous reservoir rocks." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/556f8bc4-2d71-4b30-bed4-4c2d2e48527f. biblio raw data data metadata Renard, F. (2020).Synchrotron 4D X-ray imaging reveals strain localization at the onset of system-size failure of porous reservoir rocks [Data set]. Norstore. https://doi.org/10.11582/2020.00058 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2020.00058 2020-11-18 00:00:00 2022-03-22 00:44:28.148566+00:00 The archive contains time series of X-ray tomography rock physics experiments on 7 rock samples of Adamswiller sandstone (ADAM01), Bentheim sandstone (BEN1), Anstrude limestone (ANS2, ANS3, ANS4, ANS5, ANS6) Synchrotron 4D X-ray imaging reveals strain localization at the onset of system-size failure of porous reservoir rocks 2020-11-18 00:00:00 Francois Renard francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences service-account-enrichment 7492 https://api.rohub.org/api/ros/2d1255b8-c744-4022-a2f6-fdaf88c6b011/crate/download/ 2022-03-22 00:44:29.447195+00:00 2025-03-05 00:56:02.954057+00:00 2022-03-22 00:44:29.447195+00:00 Summary statistics for multivariate association (MOSTest) of genetic variants and regional brain morphology application/ld+json https://w3id.org/ro-id/2d1255b8-c744-4022-a2f6-fdaf88c6b011 Making the MOSTest of imaging genetics MANUAL associating brain genetics imagination morphology statistic stochastic variable summary earth sciences Genetics brain genetics imaging morphology statistic summary variant life sciences MOSTest of imaging genetics brain morphology genetic variant imaging genetics summary statistic Making the MOSTest of imaging genetics. Summary statistics for multivariate association (MOSTest) of genetic variants and regional brain morphology statistics Oleksandr Frei. "Making the MOSTest of imaging genetics." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/2d1255b8-c744-4022-a2f6-fdaf88c6b011. raw data data biblio metadata Frei, O. (2020).Making the MOSTest of imaging genetics [Data set]. Norstore. https://doi.org/10.11582/2020.00031 Oleksandr Frei Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2020.00031 2020-05-29 00:00:00 2022-03-22 00:44:42.852674+00:00 Summary statistics for multivariate association (MOSTest) of genetic variants and regional brain morphology Making the MOSTest of imaging genetics 2020-05-29 00:00:00 Oleksandr Frei https://www.biorxiv.org/content/10.1101/767905v2 2022-03-22 00:44:39.712345+00:00 2022-03-22 00:44:39.824466+00:00 https://www.biorxiv.org/content/10.1101/767905v2 2022-03-22 00:44:39.712345+00:00 Geo H. oleksandr.frei@rohub.com Oleksandr Frei Environmental research Life sciences Physical sciences Earth sciences data of creep deformation X-ray imaging geology medicine radiology x-ray Carrara marble marble data sample experiment time series deformation voxel synchrotron imaging creep triaxial compression experiments time series compression tomography data faulting voxel size service-account-enrichment 7890 https://api.rohub.org/api/ros/6492da85-5bd1-4c56-82f4-03e8f8c90c69/crate/download/ 2022-03-22 00:44:43.924370+00:00 2025-03-05 00:50:03.633793+00:00 2022-03-22 00:44:43.924370+00:00 Time series of synchrotron X-ray microtomography data of creep deformation of two samples of Carrara marble. Voxel size: 6.5 micrometers application/ld+json https://w3id.org/ro-id/6492da85-5bd1-4c56-82f4-03e8f8c90c69 Creep burst coincident with faulting in marble observed in 4D synchrotron X-ray imaging triaxial compression experiments MANUAL Francois Renard. "Creep burst coincident with faulting in marble observed in 4D synchrotron X-ray imaging triaxial compression experiments." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/6492da85-5bd1-4c56-82f4-03e8f8c90c69. data raw data biblio metadata Renard, F. (2020).Creep burst coincident with faulting in marble observed in 4D synchrotron X-ray imaging triaxial compression experiments [Data set]. Norstore. https://doi.org/10.11582/2020.00022 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2020.00022 2020-04-07 00:00:00 2022-03-22 00:44:55.209043+00:00 Time series of synchrotron X-ray microtomography data of creep deformation of two samples of Carrara marble. Voxel size: 6.5 micrometers Creep burst coincident with faulting in marble observed in 4D synchrotron X-ray imaging triaxial compression experiments 2020-04-07 00:00:00 Francois Renard francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences Earth sciences sample of monzonite synchrotron imaging experiments time series geology medicine radiology error x-ray experiment synchrotron imaging monzonite weirdo damage tomography data saw saw-cut fault fault information sample competition imaging experiments time series service-account-enrichment 8160 https://api.rohub.org/api/ros/b8b9d3f9-ebfc-4c66-a6b6-0c89cdc2f8d2/crate/download/ 2022-03-22 00:44:56.443123+00:00 2025-03-05 00:47:01.088389+00:00 2022-03-22 00:44:56.443123+00:00 Time series of X-ray microtomography data acquired on beamlin ID19 at the ESRF. Four sample of monzonite rocks with a saw-cut fault. application/ld+json https://w3id.org/ro-id/b8b9d3f9-ebfc-4c66-a6b6-0c89cdc2f8d2 Competition between creep and damage on faults revealed in 4D synchrotron imaging experiments MANUAL Francois Renard. "Competition between creep and damage on faults revealed in 4D synchrotron imaging experiments." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/b8b9d3f9-ebfc-4c66-a6b6-0c89cdc2f8d2. biblio data raw data metadata Renard, F. (2020).Competition between creep and damage on faults revealed in 4D synchrotron imaging experiments [Data set]. Norstore. https://doi.org/10.11582/2020.00003 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2020.00003 2020-01-20 00:00:00 2022-03-22 00:45:10.279284+00:00 Time series of X-ray microtomography data acquired on beamlin ID19 at the ESRF. Four sample of monzonite rocks with a saw-cut fault. Competition between creep and damage on faults revealed in 4D synchrotron imaging experiments 2020-01-20 00:00:00 Francois Renard https://doi.org/10.1016/j.tecto.2020.228437. 2022-03-22 00:45:07.504181+00:00 2022-03-22 00:45:07.628514+00:00 https://doi.org/10.1016/j.tecto.2020.228437. 2022-03-22 00:45:07.504181+00:00 francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences Earth sciences physics experiment strain partitioning physics rock and roll rock x-ray data experiment physics disk partitioning imaging dataset mixology non-starter X-ray microtomography rock physics experiment Digital Volume Correlation data service-account-enrichment 7576 https://api.rohub.org/api/ros/642bed30-8205-4c7d-a0e7-cc808430b031/crate/download/ 2022-03-22 00:45:11.603831+00:00 2025-03-05 02:47:40.727346+00:00 2022-03-22 00:45:11.603831+00:00 The dataset contains Digital Volume Correlation data of rock physics experiments performed using X-ray microtomography. application/ld+json https://w3id.org/ro-id/642bed30-8205-4c7d-a0e7-cc808430b031 The mixology of precursory strain partitioning approaching brittle failure in rocks MANUAL Jess McBeck. "The mixology of precursory strain partitioning approaching brittle failure in rocks." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/642bed30-8205-4c7d-a0e7-cc808430b031. metadata biblio data raw data https://doi.org/10.1093/gji/ggaa121 2022-03-22 00:45:31.238021+00:00 2022-03-22 00:45:31.350511+00:00 https://doi.org/10.1093/gji/ggaa121 2022-03-22 00:45:31.238021+00:00 McBeck, J. (2020).The mixology of precursory strain partitioning approaching brittle failure in rocks [Data set]. Norstore. https://doi.org/10.11582/2020.00002 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2020.00002 2020-01-08 00:00:00 2022-03-22 00:45:36.140605+00:00 The dataset contains Digital Volume Correlation data of rock physics experiments performed using X-ray microtomography. The mixology of precursory strain partitioning approaching brittle failure in rocks 2020-01-08 00:00:00 Francois Renard Geo H. jess.mcbeck@rohub.com Jess McBeck Environmental research Life sciences Physical sciences nanoscale pore structure CXDI-WAXD analysis quartz-clay matrix geology measure pyrite rock formation shale dataset nanocrystal nanoscale imaging clay testing shale microparticles pore nanoscale imaging fragment mineralogy X-ray diffraction potential service-account-enrichment 8392 https://api.rohub.org/api/ros/dac2cd2c-712c-498a-a3ed-43ad9fab23e1/crate/download/ 2022-03-22 00:45:37.418119+00:00 2025-03-05 01:06:34.665385+00:00 2022-03-22 00:45:37.418119+00:00 The dataset corresonds to the article that reports the use of coherent X-ray diffraction imaging (CXDI) to study the internal structure of microscopic shale fragments and wide-angle X-ray diffraction (WAXD) measurement was performed in tandem to study the minerology of the shale microparticles. It was possible to identify pyrite nanocrystals as inclusions in the quartz-clay matrix and the nanoscale pore structure. The combined CXDI-WAXD analysis enabled establishing a correlation between sample morphology and crystallite shape and size. The results highlight the potential of the combined CXDI-WAXD approach as an upcoming imaging modality for 3D nanoscale studies of shales and other geological formations via serial measurements of microscopic fragments, including cuttings from drillings. application/ld+json https://w3id.org/ro-id/dac2cd2c-712c-498a-a3ed-43ad9fab23e1 Nanoscale imaging of shale fragments with coherent X-ray diffraction MANUAL Basab Chattopadhyay. "Nanoscale imaging of shale fragments with coherent X-ray diffraction." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/dac2cd2c-712c-498a-a3ed-43ad9fab23e1. data metadata biblio raw data Chattopadhyay, B. (2019).Nanoscale imaging of shale fragments with coherent X-ray diffraction [Data set]. Norstore. https://doi.org/10.11582/2019.00044 Basab Chattopadhyay Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2019.00044 2019-12-06 00:00:00 2022-03-22 00:45:49.589127+00:00 The dataset corresonds to the article that reports the use of coherent X-ray diffraction imaging (CXDI) to study the internal structure of microscopic shale fragments and wide-angle X-ray diffraction (WAXD) measurement was performed in tandem to study the minerology of the shale microparticles. It was possible to identify pyrite nanocrystals as inclusions in the quartz-clay matrix and the nanoscale pore structure. The combined CXDI-WAXD analysis enabled establishing a correlation between sample morphology and crystallite shape and size. The results highlight the potential of the combined CXDI-WAXD approach as an upcoming imaging modality for 3D nanoscale studies of shales and other geological formations via serial measurements of microscopic fragments, including cuttings from drillings. Nanoscale imaging of shale fragments with coherent X-ray diffraction 2019-12-06 00:00:00 Basab Chattopadhyay basab.chattopadhyay@rohub.com Basab Chattopadhyay Geo H. Environmental research Life sciences Physical sciences Earth sciences Ne Java gas survey geochemistry interpretation A. Sciarra West Irian Java Indonesia Indonesia West Irian Java study information gas geochemistry result A. Zaputlyaeva fluid chemistry interpretation of the data service-account-enrichment 7429 https://api.rohub.org/api/ros/d2c4be1a-9fa4-454d-9963-993f763467aa/crate/download/ 2022-03-22 00:45:50.581037+00:00 2025-03-05 00:59:11.488692+00:00 2022-03-22 00:45:50.581037+00:00 The data represents the results of the gas survey, acquired in the north-east Java in 2017-2018. The interpretation of the data is provided in the "Mantle-derived fluids in the East Java sedimentary basin, Indonesia" by A. Zaputlyaeva, A. Mazzini, A. Caracausi, and A. Sciarra, published in JGR Solid Earth, 2019 application/ld+json https://w3id.org/ro-id/d2c4be1a-9fa4-454d-9963-993f763467aa Gas geochemistry results, NE Java, Indonesia MANUAL Alexandra Zaputlyaeva, and Centre for Earth Evolution and Dynamics, University of Oslo (CEED/UiO). "Gas geochemistry results, NE Java, Indonesia." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/d2c4be1a-9fa4-454d-9963-993f763467aa. biblio raw data data metadata https://doi.org/10.1029/2018JB017274 2022-03-22 00:46:06.750822+00:00 2022-03-22 00:46:06.879553+00:00 https://doi.org/10.1029/2018JB017274 2022-03-22 00:46:06.750822+00:00 https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2019.00025 2022-03-22 00:46:04.396700+00:00 2022-03-22 00:46:04.752445+00:00 The data represents the results of the gas survey, acquired in the north-east Java in 2017-2018. The interpretation of the data is provided in the "Mantle-derived fluids in the East Java sedimentary basin, Indonesia" by A. Zaputlyaeva, A. Mazzini, A. Caracausi, and A. Sciarra, published in JGR Solid Earth, 2019 Gas geochemistry results, NE Java, Indonesia 2022-03-22 00:46:04.396700+00:00 CEED.UiO@rohub.com Centre for Earth Evolution and Dynamics, University of Oslo (CEED/UiO) alexandra.zaputlyaeva@rohub.com Alexandra Zaputlyaeva Geo H. Environmental research Life sciences Physical sciences information technology wave statistics laboratory data http data file fact directory treatise gossip Arabia files LabloggtilKarsten.xlsx Arabia master thesis statistics directory shoal Journal of Fluid Mechanics directory SJ service-account-enrichment 8842 https://api.rohub.org/api/ros/5228ef35-26a9-4d98-843a-0e8af35d3fc3/crate/download/ 2022-03-22 00:46:09.034092+00:00 2025-03-05 00:50:43.837894+00:00 2022-03-22 00:46:09.034092+00:00 This directory contains laboratory data used for the article: Trulsen, Raustøl, Jorde &amp; Rye (2019) "Extreme wave statistics of longcrested irregular waves over a shoal" Journal of Fluid Mechanics Data from the master thesis of Anne Raustøl is in directory AR. For details see the comments in the file Kommentar.odt and see the master thesis that can be downloaded from LINK: http://www.duo.uio.no/handle/10852/40405 Data from the master thesis of Stian Jorde is in directory SJ. For details see the comments in the files LabloggtilKarsten.xlsx and Lesmeg.docx and see the master thesis that can be downloaded from LINK: http://www.duo.uio.no/handle/10852/67561 All text written in the course of these two master theses is in Norwegian, no English translation has been made. application/ld+json https://w3id.org/ro-id/5228ef35-26a9-4d98-843a-0e8af35d3fc3 Extreme wave statistics of longcrested irregular waves over a shoal MANUAL Karsten Trulsen. "Extreme wave statistics of longcrested irregular waves over a shoal." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/5228ef35-26a9-4d98-843a-0e8af35d3fc3. biblio data metadata raw data http://folk.uio.no/karstent/JFM-19-RP-1252.R1_Proof_hi.pdf 2022-03-22 00:46:18.915143+00:00 2022-03-22 00:46:19.014468+00:00 application/pdf http://folk.uio.no/karstent/JFM-19-RP-1252.R1_Proof_hi.pdf 2022-03-22 00:46:18.915143+00:00 Trulsen, K. (2019).Extreme wave statistics of longcrested irregular waves over a shoal [Data set]. Norstore. https://doi.org/10.11582/2019.00023 Karsten Trulsen Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2019.00023 2019-10-11 00:00:00 2022-03-22 00:46:21.701376+00:00 This directory contains laboratory data used for the article: Trulsen, Raustøl, Jorde &amp; Rye (2019) "Extreme wave statistics of longcrested irregular waves over a shoal" Journal of Fluid Mechanics Data from the master thesis of Anne Raustøl is in directory AR. For details see the comments in the file Kommentar.odt and see the master thesis that can be downloaded from <a href="http://www.duo.uio.no/handle/10852/40405" class="linkified" target="_blank">LINK</a> Data from the master thesis of Stian Jorde is in directory SJ. For details see the comments in the files LabloggtilKarsten.xlsx and Lesmeg.docx and see the master thesis that can be downloaded from <a href="http://www.duo.uio.no/handle/10852/67561" class="linkified" target="_blank">LINK</a> All text written in the course of these two master theses is in Norwegian, no English translation has been made. Extreme wave statistics of longcrested irregular waves over a shoal 2019-10-11 00:00:00 Karsten Trulsen Geo H. karsten.trulsen@rohub.com Karsten Trulsen Environmental research Life sciences Physical sciences Earth sciences transport in porous rocks Series Switzerland Institut Laue Langevin neutron imaging of cadmium sorption Paul Scherrer Institute neutron tomography image neutron imaging cadmium neutron image imaging sorption tomography image Switzerland imaging Ill France transport rock France chemistry Ill service-account-enrichment 8204 https://api.rohub.org/api/ros/7a02a524-8fb8-42c1-911a-74aa8dc03c0c/crate/download/ 2022-03-22 00:46:22.684252+00:00 2025-03-05 01:06:35.596784+00:00 2022-03-22 00:46:22.684252+00:00 Series of 2D and 3D neutron tomography images acquired at the Paul Scherrer Institute (PSI, Switzerland) or at the Institut Laue Langevin (ILL, France). application/ld+json https://w3id.org/ro-id/7a02a524-8fb8-42c1-911a-74aa8dc03c0c Neutron imaging of cadmium sorption and transport in porous rocks MANUAL Francois Renard. "Neutron imaging of cadmium sorption and transport in porous rocks." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/7a02a524-8fb8-42c1-911a-74aa8dc03c0c. raw data data metadata biblio Renard, F. (2019).Neutron imaging of cadmium sorption and transport in porous rocks [Data set]. Norstore. https://doi.org/10.11582/2019.00021 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2019.00021 2019-09-25 00:00:00 2022-03-22 00:46:36.114428+00:00 Series of 2D and 3D neutron tomography images acquired at the Paul Scherrer Institute (PSI, Switzerland) or at the Institut Laue Langevin (ILL, France). Neutron imaging of cadmium sorption and transport in porous rocks 2019-09-25 00:00:00 Francois Renard https://doi.org/10.3389/feart.2019.00306. 2022-03-22 00:46:33.178531+00:00 2022-03-22 00:46:33.302120+00:00 https://doi.org/10.3389/feart.2019.00306. 2022-03-22 00:46:33.178531+00:00 francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences Earth sciences service-account-enrichment 8143 https://api.rohub.org/api/ros/ab90c409-80fc-4643-9f90-e90864ee488f/crate/download/ 2022-03-22 00:46:37.264152+00:00 2025-03-05 02:46:56.460627+00:00 2022-03-22 00:46:37.264152+00:00 Transmission Kikuchi Diffraction (TKD) maps for experiment s1221, published in Demurtas et al., 2019, Grain size sensitive creep during simulated seismic slip in nanogranular fault gouges: constraints from Transmission Kikuchi Diffraction (TKD), Journal of Geophysical Research: Solid Earth. Experimental conditions: - Slip rate = 1 m/s - Displacement = 0.4 m - Normal load = 17.5 MPa - Room-humidity conditions application/ld+json https://w3id.org/ro-id/ab90c409-80fc-4643-9f90-e90864ee488f Transmission Kikuchi Diffraction (TKD) data: calcite-dolomite mixtures MANUAL constraint experiment geological fault gouge map weirdo earth sciences Inorganic chemical Newspaper and magazine Newspaper Weather Demurtas Transmission Kikuchi Diffraction constraint fault gouge map s1221 geosciences Journal of Geophysical Research calcite-dolomite mixture constraints from Transmission Kikuchi Diffraction experiment s1221 fault gouge Transmission Kikuchi Diffraction (TKD) data: calcite-dolomite mixtures. Transmission Kikuchi Diffraction (TKD) maps for experiment s1221, published in Demurtas et al. 2019, Grain size sensitive creep during simulated seismic slip in nanogranular fault gouges: constraints from Transmission Kikuchi Diffraction (TKD) Journal of Geophysical Research: Solid Earth. geology Matteo Demurtas. "Transmission Kikuchi Diffraction (TKD) data: calcite-dolomite mixtures." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/ab90c409-80fc-4643-9f90-e90864ee488f. data raw data biblio metadata Demurtas, M. (2019).Transmission Kikuchi Diffraction (TKD) data: calcite-dolomite mixtures [Data set]. Norstore. https://doi.org/10.11582/2019.00016 Matteo Demurtas Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2019.00016 2019-08-26 00:00:00 2022-03-22 00:46:49.838333+00:00 Transmission Kikuchi Diffraction (TKD) maps for experiment s1221, published in Demurtas et al., 2019, Grain size sensitive creep during simulated seismic slip in nanogranular fault gouges: constraints from Transmission Kikuchi Diffraction (TKD), Journal of Geophysical Research: Solid Earth. Experimental conditions: - Slip rate = 1 m/s - Displacement = 0.4 m - Normal load = 17.5 MPa - Room-humidity conditions Transmission Kikuchi Diffraction (TKD) data: calcite-dolomite mixtures 2019-08-26 00:00:00 Matteo Demurtas Geo H. matteo.demurtas@rohub.com Matteo Demurtas Environmental research Life sciences Physical sciences Earth sciences images of a sample geology medicine radiology limestone x-ray Series image synchrotron imaging sample tomography image hade apparatus crush synchrotron X-ray imaging porous limestone Series porous limestone compaction localization locating service-account-enrichment 8263 https://api.rohub.org/api/ros/9ceb232e-a8ae-4ecf-a960-a8406e85121f/crate/download/ 2022-03-22 00:46:51.385725+00:00 2025-03-05 01:24:09.360800+00:00 2022-03-22 00:46:51.385725+00:00 Series of time-lapse 3D X-ray microtomography images of a sample of Leitha limestone deformed in the traxial apparatus HADES at the beamline ID19, ESRF. application/ld+json https://w3id.org/ro-id/9ceb232e-a8ae-4ecf-a960-a8406e85121f Synchrotron X-ray imaging in 4D: Multiscale failure and compaction localization in triaxially compressed porous limestone MANUAL Francois Renard. "Synchrotron X-ray imaging in 4D: Multiscale failure and compaction localization in triaxially compressed porous limestone." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/9ceb232e-a8ae-4ecf-a960-a8406e85121f. biblio metadata data raw data https://doi.org/10.1016/j.epsl.2019.115831. 2022-03-22 00:47:02.078286+00:00 2022-03-22 00:47:02.189240+00:00 https://doi.org/10.1016/j.epsl.2019.115831. 2022-03-22 00:47:02.078286+00:00 Renard, F. (2019).Synchrotron X-ray imaging in 4D: Multiscale failure and compaction localization in triaxially compressed porous limestone [Data set]. Norstore. https://doi.org/10.11582/2019.00015 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2019.00015 None 2022-03-22 00:47:04.774399+00:00 Series of time-lapse 3D X-ray microtomography images of a sample of Leitha limestone deformed in the traxial apparatus HADES at the beamline ID19, ESRF. Synchrotron X-ray imaging in 4D: Multiscale failure and compaction localization in triaxially compressed porous limestone None Francois Renard francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences Earth sciences fluids in the East Java Journal of geophysical research. Biogeosciences NE Java gas survey geochemistry interpretation West Irian Java Indonesia Indonesia West Irian Java study manuscript information gas geochemistry result north east fluid chemistry interpretation of the data service-account-enrichment 8227 https://api.rohub.org/api/ros/3215a150-9891-40ef-bf67-420abb5734b0/crate/download/ 2022-03-22 00:47:06.177829+00:00 2025-03-05 00:59:11.269094+00:00 2022-03-22 00:47:06.177829+00:00 The data represents the results of the gas survey, acquired in the north-east Java in 2017-2018. The interpretation of the data is provided in the "Mantle-derived fluids in the East Java sedimentary basin, Indonesia" by A. Zaputlyaeva, A. Mazzini, A. Caracausi, and A. Sciarra. The manuscript is currently under review in the Journal of Geophysical Research: Solid Earth. application/ld+json https://w3id.org/ro-id/3215a150-9891-40ef-bf67-420abb5734b0 Gas geochemistry results, NE Java, Indonesia MANUAL Alexandra Zaputlyaeva, and Centre for Earth Evolution and Dynamics, University of Oslo (CEED/UiO). "Gas geochemistry results, NE Java, Indonesia." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/3215a150-9891-40ef-bf67-420abb5734b0. data raw data metadata biblio Zaputlyaeva, A., Centre for Earth Evolution and Dynamics, University of Oslo (2019).Gas geochemistry results, NE Java, Indonesia [Data set]. Norstore. https://doi.org/10.11582/2019.00025 Alexandra Zaputlyaeva Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2019.00009 2019-04-04 00:00:00 2022-03-22 00:47:21.134296+00:00 The data represents the results of the gas survey, acquired in the north-east Java in 2017-2018. The interpretation of the data is provided in the "Mantle-derived fluids in the East Java sedimentary basin, Indonesia" by A. Zaputlyaeva, A. Mazzini, A. Caracausi, and A. Sciarra. The manuscript is currently under review in the Journal of Geophysical Research: Solid Earth. Gas geochemistry results, NE Java, Indonesia 2019-04-04 00:00:00 Alexandra Zaputlyaeva CEED.UiO@rohub.com Centre for Earth Evolution and Dynamics, University of Oslo (CEED/UiO) alexandra.zaputlyaeva@rohub.com Alexandra Zaputlyaeva Geo H. Environmental research Life sciences Physical sciences Earth sciences modelling system physics electrotechnics ocean sea ice snow depth output thickness output ocean-sea ice modeling system equipment concentration snow depth sea ice thickness sea ice concentration service-account-enrichment 8345 https://api.rohub.org/api/ros/954ac2c8-45eb-4567-a84a-7745f0809dbc/crate/download/ 2022-03-22 00:47:24.149220+00:00 2025-03-05 00:56:56.900514+00:00 2022-03-22 00:47:24.149220+00:00 This is model output used for the analysis in the following paper: Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean-sea ice modelling system, The Cryosphere, 2018, Fritzner et. al. application/ld+json https://w3id.org/ro-id/954ac2c8-45eb-4567-a84a-7745f0809dbc Model output, Article: Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean-sea ice modeling system MANUAL Sindre Fritzner. "Model output, Article: Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean-sea ice modeling system." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/954ac2c8-45eb-4567-a84a-7745f0809dbc. data metadata biblio raw data https://www.the-cryosphere-discuss.net/tc-2018-171/tc-2018-171.pdf 2022-03-22 00:47:36.208011+00:00 2022-03-22 00:47:36.322304+00:00 application/pdf https://www.the-cryosphere-discuss.net/tc-2018-171/tc-2018-171.pdf 2022-03-22 00:47:36.208011+00:00 Fritzner, S. (2019).Model output, Article: Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean-sea ice modeling system [Data set]. Norstore. https://doi.org/10.11582/2019.00005 Sindre Markus Fritzner Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2019.00005 2019-02-06 00:00:00 2022-03-22 00:47:39.206542+00:00 This is model output used for the analysis in the following paper: Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean-sea ice modelling system, The Cryosphere, 2018, Fritzner et. al. Model output, Article: Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean-sea ice modeling system 2019-02-06 00:00:00 Sindre Markus Fritzner Geo H. sindre.fritzner@rohub.com Sindre Fritzner Environmental research Life sciences Physical sciences Earth sciences hades rig physics geology Carrara marble data dynamics time series volume imaging sample precursor tomography datum dynamics of microscale precursor samples M8 hade times series of TIF 3D volume fail rig datum service-account-enrichment 7845 https://api.rohub.org/api/ros/271509e6-7194-4b4e-9ccf-9bbec2bba5af/crate/download/ 2022-03-22 00:47:40.189086+00:00 2025-03-05 00:47:52.546898+00:00 2022-03-22 00:47:40.189086+00:00 X-ray microtomography data of samples M8 and M8-2: times series of TIF 3D volumes during deformation. Data acquired using the HADES rig, beamline ID19, European Synchrotron Radiation Facility. application/ld+json https://w3id.org/ro-id/271509e6-7194-4b4e-9ccf-9bbec2bba5af Dynamics of microscale precursors establish brittle compressive failure in Carrara marble as a critical phenomenon MANUAL Francois Renard. "Dynamics of microscale precursors establish brittle compressive failure in Carrara marble as a critical phenomenon." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/271509e6-7194-4b4e-9ccf-9bbec2bba5af. metadata biblio data raw data Renard, F. (2019).Dynamics of microscale precursors establish brittle compressive failure in Carrara marble as a critical phenomenon [Data set]. Norstore. https://doi.org/10.11582/2019.00001 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2019.00001 None 2022-03-22 00:47:56.565519+00:00 X-ray microtomography data of samples M8 and M8-2: times series of TIF 3D volumes during deformation. Data acquired using the HADES rig, beamline ID19, European Synchrotron Radiation Facility. Dynamics of microscale precursors establish brittle compressive failure in Carrara marble as a critical phenomenon None Francois Renard https://doi.org/10.1029/2019JB017381. 2022-03-22 00:47:53.910815+00:00 2022-03-22 00:47:54.015156+00:00 https://doi.org/10.1029/2019JB017381. 2022-03-22 00:47:53.910815+00:00 francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences Earth sciences Mixed-mode strain localization hydration reaction medicine x-ray chemical reaction magnesium oxide imaging tomography datum strain serpentine datum series strain localization hydration locating series of tif image service-account-enrichment 7996 https://api.rohub.org/api/ros/d9ee3dc8-e998-41e8-8065-ddc995192148/crate/download/ 2022-03-22 00:47:57.561209+00:00 2025-03-05 00:56:53.364916+00:00 2022-03-22 00:47:57.561209+00:00 X-ray dynamic microtomography data (series of tif images) of serpentine with periclase application/ld+json https://w3id.org/ro-id/d9ee3dc8-e998-41e8-8065-ddc995192148 Mixed-mode strain localization generated by hydration reaction at crustal conditions MANUAL Francois Renard. "Mixed-mode strain localization generated by hydration reaction at crustal conditions." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/d9ee3dc8-e998-41e8-8065-ddc995192148. data metadata biblio raw data https://doi.org/10.1029/2018JB017008. 2022-03-22 00:48:07.306463+00:00 2022-03-22 00:48:07.415160+00:00 https://doi.org/10.1029/2018JB017008. 2022-03-22 00:48:07.306463+00:00 Renard, F. (2018).Mixed-mode strain localization generated by hydration reaction at crustal conditions [Data set]. Norstore. https://doi.org/10.11582/2018.00037 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00037 None 2022-03-22 00:48:10.024010+00:00 X-ray dynamic microtomography data (series of tif images) of serpentine with periclase Mixed-mode strain localization generated by hydration reaction at crustal conditions None Francois Renard francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences Earth sciences shear strain localization samples of basalt physics medicine mountain x-ray basalt imaging shear tomography datum Etna shear strain localization in Mt. Etna Etna datum sample locating microtomography datum service-account-enrichment 7494 https://api.rohub.org/api/ros/44a84f82-3f87-4080-ae85-511d3cf48ef5/crate/download/ 2022-03-22 00:48:11.313858+00:00 2025-03-05 01:27:55.097356+00:00 2022-03-22 00:48:11.313858+00:00 X-ray microtomography data of 2 samples of basalt from Mount Etna. application/ld+json https://w3id.org/ro-id/44a84f82-3f87-4080-ae85-511d3cf48ef5 Volumetric and shear strain localization in Mt. Etna basalt MANUAL Francois Renard. "Volumetric and shear strain localization in Mt. Etna basalt." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/44a84f82-3f87-4080-ae85-511d3cf48ef5. biblio data metadata raw data Renard, F. (2018).Volumetric and shear strain localization in Mt. Etna basalt [Data set]. Norstore. https://doi.org/10.11582/2018.00036 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00036 2018-11-13 00:00:00 2022-03-22 00:48:23.850111+00:00 X-ray microtomography data of 2 samples of basalt from Mount Etna. Volumetric and shear strain localization in Mt. Etna basalt 2018-11-13 00:00:00 Francois Renard https://doi.org/10.1029/2018GL081299. 2022-03-22 00:48:21.317230+00:00 2022-03-22 00:48:21.417819+00:00 https://doi.org/10.1029/2018GL081299. 2022-03-22 00:48:21.317230+00:00 francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences service-account-enrichment 8627 https://api.rohub.org/api/ros/a752e046-0330-490c-852b-1d4e6c9d353c/crate/download/ 2022-03-22 00:48:25.026115+00:00 2025-03-05 02:49:06.490009+00:00 2022-03-22 00:48:25.026115+00:00 V3V dataset from open channel experiments at the upstream side of alternative (fish-friendly) trash-rack. The actual trash-rack type is referred to Rack II according to the defined configurations in Szabo-Meszaros et al. 2018. application/ld+json https://w3id.org/ro-id/a752e046-0330-490c-852b-1d4e6c9d353c V3V measurement from experimental hydraulics MANUAL alternative dataset experiment fish fluid mechanics measure rack rubbish two type earth sciences Food IT-computer sciences Science and technology V3V dataset experiment hydraulics rack trash type engineering channel experiment measurement from experimental hydraulics rack II trash-rack type upstream side of alternative The actual trash-rack type is referred to Rack II according to the defined configurations in Szabo-Meszaros et al. 2018. V3V dataset from open channel experiments at the upstream side of alternative (fish-friendly) trash-rack. V3V measurement from experimental hydraulics. Christy Ushanth Navaratnam, and Marcell Szabo-Meszaros. "V3V measurement from experimental hydraulics." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/a752e046-0330-490c-852b-1d4e6c9d353c. raw data biblio data metadata https://doi.org/10.1016/j.ecoleng.2017.12.032 2022-03-22 00:48:41.344981+00:00 2022-03-22 00:48:41.452551+00:00 https://doi.org/10.1016/j.ecoleng.2017.12.032 2022-03-22 00:48:41.344981+00:00 Navaratnam, C. U., Szabo-Meszaros, M. (2018).V3V measurement from experimental hydraulics [Data set]. Norstore. https://doi.org/10.11582/2018.00030 Norwegian University of Science and Technology Department of Civil and Environmental Engineering (NTNU - IBM) Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00030 2018-10-11 00:00:00 2022-03-22 00:48:43.913778+00:00 V3V dataset from open channel experiments at the upstream side of alternative (fish-friendly) trash-rack. The actual trash-rack type is referred to Rack II according to the defined configurations in Szabo-Meszaros et al. 2018. V3V measurement from experimental hydraulics 2018-10-11 00:00:00 Knut Alfredsen christy.ushanth.navaratnam@rohub.com Christy Ushanth Navaratnam Geo H. marcell.szabo-meszaros@rohub.com Marcell Szabo-Meszaros Environmental research Neurobiology Life sciences Physical sciences GUI data visualize the data data user interface graphical user interface Fiji paper data within the Fiji software session sessions of the paper Fiji Fiji software service-account-enrichment 7716 https://api.rohub.org/api/ros/09ee2433-635e-4317-9b3d-27655503452a/crate/download/ 2022-03-22 00:48:45.359168+00:00 2025-03-05 00:57:47.549843+00:00 2022-03-22 00:48:45.359168+00:00 Data from 4 sessions of the paper titled "Efficient cortical coding of 3D posture in freely behaving rats" as well as a user interface for visualizing the data within the Fiji software. application/ld+json https://w3id.org/ro-id/09ee2433-635e-4317-9b3d-27655503452a Efficient cortical coding of 3D posture in freely behaving rats - data and GUI MANUAL Bartul Mimica. "Efficient cortical coding of 3D posture in freely behaving rats - data and GUI." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/09ee2433-635e-4317-9b3d-27655503452a. raw data metadata data biblio Mimica, B. (2018).Efficient cortical coding of 3D posture in freely behaving rats - data and GUI [Data set]. Norstore. https://doi.org/10.11582/2018.00028 Jonathan Whitlock Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00028 2018-09-13 00:00:00 2022-03-22 00:48:56.209038+00:00 Data from 4 sessions of the paper titled "Efficient cortical coding of 3D posture in freely behaving rats" as well as a user interface for visualizing the data within the Fiji software. Efficient cortical coding of 3D posture in freely behaving rats - data and GUI 2018-09-13 00:00:00 Jonathan Whitlock bartul.mimica@rohub.com Bartul Mimica Geo H. Environmental research Neurobiology Life sciences Physical sciences service-account-enrichment 7404 https://api.rohub.org/api/ros/31f383a0-7547-43c0-a80a-86a2feb88eb6/crate/download/ 2022-03-22 00:48:57.198715+00:00 2025-03-05 00:50:07.977678+00:00 2022-03-22 00:48:57.198715+00:00 This is the data archive for our 2018 paper in elife application/ld+json https://w3id.org/ro-id/31f383a0-7547-43c0-a80a-86a2feb88eb6 Data from Rowland et al 2018 MANUAL data library information earth sciences Library and museum data archive data life sciences paper in elife Data from Rowland et al 2018. This is the data archive for our 2018 paper in elife 2018 David Rowland. "Data from Rowland et al 2018." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/31f383a0-7547-43c0-a80a-86a2feb88eb6. metadata biblio raw data data Rowland, D. (2018).Data from Rowland et al 2018 [Data set]. Norstore. https://doi.org/10.11582/2018.00025 David Clayton Rowland Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00025 2018-08-22 00:00:00 2022-03-22 00:49:07.656208+00:00 This is the data archive for our 2018 paper in elife Data from Rowland et al 2018 2018-08-22 00:00:00 David Clayton Rowland david.rowland@rohub.com David Rowland Geo H. Environmental research Life sciences Physical sciences Earth sciences sample monzonite 5 faulting X-ray tomography data geology x-ray data synchrotron radiation imaging monzonite processes hade faulting data of the deformation rig in-situ imaging crystalline rock deformation sample monzonite rock sample volumetric service-account-enrichment 7733 https://api.rohub.org/api/ros/044861d7-b47d-4d4f-b5bd-4431dc6e2050/crate/download/ 2022-03-22 00:49:08.870899+00:00 2025-03-05 01:27:54.858145+00:00 2022-03-22 00:49:08.870899+00:00 X-ray tomography data of the deformation of a monzonite rock sample (sample Monzonite 5). In-situ imaging of the sample inside the HADES rig at the European Synchrotron Radiation Facility application/ld+json https://w3id.org/ro-id/044861d7-b47d-4d4f-b5bd-4431dc6e2050 Volumetric and shear processes in crystalline rock during the approach to faulting MANUAL Francois Renard, and University of Oslo (UiO). "Volumetric and shear processes in crystalline rock during the approach to faulting." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/044861d7-b47d-4d4f-b5bd-4431dc6e2050. data metadata raw data biblio Renard, F., University of Oslo (2018).Volumetric and shear processes in crystalline rock during the approach to faulting [Data set]. Norstore. https://doi.org/10.11582/2018.00023 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00023 2018-08-20 00:00:00 2022-03-22 00:49:23.282128+00:00 X-ray tomography data of the deformation of a monzonite rock sample (sample Monzonite 5). In-situ imaging of the sample inside the HADES rig at the European Synchrotron Radiation Facility Volumetric and shear processes in crystalline rock during the approach to faulting 2018-08-20 00:00:00 Francois Renard UiO@rohub.com University of Oslo (UiO) francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences Earth sciences Dynamic in situ three-dimensional imaging and digital volume correlation analysis quantify strain localization and fracture coalescence in sandstone. 52.50501002004008 52.4 information 8.77016129032258 8.7 data 7.258064516129032 7.2 coalescence 15.514592933947775 10.1 fracture 15.668202764976957 10.2 statistics 20.103092783505158 3.9 three-dimensional imaging 8.812260536398467 6.9 Data are times series of 3D tomograms (stacks of tif images) 12.82565130260521 12.8 radiology 30.927835051546396 6.0 geology 13.402061855670103 2.6 life sciences 100.0 0.6553213596343994 sandstone 3.629032258064516 3.6 locating 7.762096774193548 7.7 Microtomography data of 3 samples of Fontainebleau deformed into the HADES rig at the European Synchrotron Radiation Facility (beamline ID19) 34.66933867735471 34.6 imaging 13.911290322580644 13.8 rig 4.133064516129031 4.1 tomogram 3.9314516129032255 3.9 life sciences (general) 100.0 0.6553213596343994 strain 13.978494623655916 9.1 Fontainebleau 4.032258064516129 4.0 strain 8.669354838709678 8.6 imaging 14.132104454685098 9.2 correlational analysis 7.258064516129032 7.2 earth sciences 100.0 0.8457534313201904 tomography data 20.945083014048528 16.4 Injury Health/Diseases and conditions/Injury fracture coalescence 29.374201787994892 23.0 hade 4.133064516129031 4.1 geology 100.0 0.8457534313201904 data 15.053763440860218 9.8 strain localization 28.863346104725416 22.6 volume correlation analysis 12.005108556832695 9.4 localization 13.0568356374808 8.5 Fontainebleau https://www.wikidata.org/wiki/Q182872 fracture 9.576612903225806 9.5 time series 7.661290322580645 7.6 correlation analysis 12.596006144393241 8.2 Health Health coalescence 9.274193548387096 9.2 medicine 35.56701030927835 6.9 Medical procedure-test Health/Health treatment/Medical procedure-test service-account-enrichment 8332 https://api.rohub.org/api/ros/37db5a42-5a5d-420e-9422-c85007514eba/crate/download/ 2022-03-22 00:49:24.633058+00:00 2025-10-04 18:10:20.333647+00:00 2022-03-22 00:49:24.633058+00:00 Microtomography data of 3 samples of Fontainebleau deformed into the HADES rig at the European Synchrotron Radiation Facility (beamline ID19). Data are times series of 3D tomograms (stacks of tif images). application/ld+json https://w3id.org/ro-id/37db5a42-5a5d-420e-9422-c85007514eba Dynamic in situ three-dimensional imaging and digital volume correlation analysis quantify strain localization and fracture coalescence in sandstone MANUAL University of Oslo (UiO), and Francois Renard. "Dynamic in situ three-dimensional imaging and digital volume correlation analysis quantify strain localization and fracture coalescence in sandstone." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/37db5a42-5a5d-420e-9422-c85007514eba. biblio raw data data metadata University of Oslo, Renard, F. (2018).Dynamic in situ three-dimensional imaging and digital volume correlation analysis quantify strain localization and fracture coalescence in sandstone [Data set]. Norstore. https://doi.org/10.11582/2018.00022 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00022 2018-08-20 00:00:00 2022-03-22 00:49:41.106458+00:00 Microtomography data of 3 samples of Fontainebleau deformed into the HADES rig at the European Synchrotron Radiation Facility (beamline ID19). Data are times series of 3D tomograms (stacks of tif images). Dynamic in situ three-dimensional imaging and digital volume correlation analysis quantify strain localization and fracture coalescence in sandstone 2018-08-20 00:00:00 Francois Renard https://doi.org/10.1007/s00024-018-2003-x. 2022-03-22 00:49:38.276683+00:00 2022-03-22 00:49:38.377764+00:00 https://doi.org/10.1007/s00024-018-2003-x. 2022-03-22 00:49:38.276683+00:00 UiO@rohub.com University of Oslo (UiO) francois.renard@rohub.com Francois Renard Geo H. Environmental research Life sciences Physical sciences Earth sciences effects of confinement medicine data magnesium oxide periclase data sample detention response service-account-enrichment 7838 https://api.rohub.org/api/ros/18918bfc-fae6-43a4-a18d-b71de2500a44/crate/download/ 2022-03-22 00:49:42.348457+00:00 2025-03-05 00:57:46.608901+00:00 2022-03-22 00:49:42.348457+00:00 Data of 4 samples: PERI01, PERI04, PERI06 and PERI08 application/ld+json https://w3id.org/ro-id/18918bfc-fae6-43a4-a18d-b71de2500a44 Effects of confinement on reaction-induced fracturing during hydration of periclase MANUAL Francois Renard. "Effects of confinement on reaction-induced fracturing during hydration of periclase." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/18918bfc-fae6-43a4-a18d-b71de2500a44. metadata data raw data biblio https://agupubs.onlinelibrary.wiley.com/journal/15252027 2022-03-22 00:49:54.595899+00:00 2022-03-22 00:49:54.693328+00:00 https://agupubs.onlinelibrary.wiley.com/journal/15252027 2022-03-22 00:49:54.595899+00:00 Renard, F. (2018).Effects of confinement on reaction-induced fracturing during hydration of periclase [Data set]. Norstore. https://doi.org/10.11582/2018.00016 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00016 2018-06-26 00:00:00 2022-03-22 00:49:58.212302+00:00 Data of 4 samples: PERI01, PERI04, PERI06 and PERI08 Effects of confinement on reaction-induced fracturing during hydration of periclase 2018-06-26 00:00:00 Francois Renard francois.renard@rohub.com Francois Renard Geo H. Environmental research Neurobiology Life sciences Physical sciences version of the dataset grid scale al 2008 cell data Hippocampus publication grid network dataset entorhinal cortex cortices position data model growth service-account-enrichment 6886 https://api.rohub.org/api/ros/8b778ba8-2e09-48d9-a7ff-3d9354b70656/crate/download/ 2022-03-22 00:49:59.623588+00:00 2025-03-05 00:59:16.283740+00:00 2022-03-22 00:49:59.623588+00:00 This is a refined version of the dataset. It contains spike-data, position data and also raw position data. This data was used in the publication: Brun, V., 2008, "Progressive increase in grid scale from dorsal to ventral medial entorhinal cortex", Hippocampus, 18, 1200–1212. application/ld+json https://w3id.org/ro-id/8b778ba8-2e09-48d9-a7ff-3d9354b70656 Grid cell data Brun et al 2008 MANUAL Centre for the Biology of Memory (CBM), and Vegard Brun. "Grid cell data Brun et al 2008." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/8b778ba8-2e09-48d9-a7ff-3d9354b70656. raw data biblio metadata data https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00015 2022-03-22 00:50:11.648228+00:00 2022-03-22 00:50:16.550297+00:00 This is a refined version of the dataset. It contains spike-data, position data and also raw position data. This data was used in the publication: Brun, V., 2008, "Progressive increase in grid scale from dorsal to ventral medial entorhinal cortex", Hippocampus, 18, 1200–1212. Grid cell data Brun et al 2008 2022-03-22 00:50:11.648228+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1002/hipo.20504 2022-03-22 00:50:13.736944+00:00 2022-03-22 00:50:13.839338+00:00 https://onlinelibrary.wiley.com/doi/abs/10.1002/hipo.20504 2022-03-22 00:50:13.736944+00:00 CBM@rohub.com Centre for the Biology of Memory (CBM) Geo H. vegard.brun@rohub.com Vegard Brun Mathematics Information science separable statistics linear cryptanalysis supplemental material for the paper cryptanalysis domain material for the paper statistics material supplemental material service-account-enrichment 7203 https://api.rohub.org/api/ros/04741546-5c3e-481c-b0f2-34db66f336af/crate/download/ 2022-03-22 00:50:17.771843+00:00 2025-03-05 01:21:30.100114+00:00 2022-03-22 00:50:17.771843+00:00 Supplemental Material for the paper "Separable Statistics and Multidimensional Linear Cryptanalysis". application/ld+json https://w3id.org/ro-id/04741546-5c3e-481c-b0f2-34db66f336af Separable Statistics and Multidimensional Linear Cryptanalysis - Supplemental Material MANUAL Stian Fauskanger, and Igor Semaev. "Separable Statistics and Multidimensional Linear Cryptanalysis - Supplemental Material." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/04741546-5c3e-481c-b0f2-34db66f336af. data biblio metadata raw data Fauskanger, S., Semaev, I. (2018).Separable Statistics and Multidimensional Linear Cryptanalysis - Supplemental Material [Data set]. Norstore. https://doi.org/10.11582/2018.00013 Stian Fauskanger Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00013 2018-05-17 00:00:00 2022-03-22 00:50:35.189223+00:00 Supplemental Material for the paper "Separable Statistics and Multidimensional Linear Cryptanalysis". Separable Statistics and Multidimensional Linear Cryptanalysis - Supplemental Material 2018-05-17 00:00:00 Stian Fauskanger https://eprint.iacr.org/2017/994 2022-03-22 00:50:32.270166+00:00 2022-03-22 00:50:32.396439+00:00 https://eprint.iacr.org/2017/994 2022-03-22 00:50:32.270166+00:00 Geo H. igor.semaev@rohub.com Igor Semaev stian.fauskanger@rohub.com Stian Fauskanger Environmental research Life sciences Physical sciences Earth sciences samples GRS01 Green River geology medicine x-ray data archive shale imaging sample anisotropic shale Green River tomography data onset of strain localization onset deformation sample correlation shale sample service-account-enrichment 7370 https://api.rohub.org/api/ros/2cee7168-1254-46dc-80cd-e3910724e61e/crate/download/ 2022-03-22 00:50:36.320205+00:00 2025-03-05 00:55:19.587631+00:00 2022-03-22 00:50:36.320205+00:00 The archive contains the dynamic X-ray tomography data of two Green River shale samples undergoing deformation. Samples GRS01 and GRS02 application/ld+json https://w3id.org/ro-id/2cee7168-1254-46dc-80cd-e3910724e61e Investigating the onset of strain localization within anisotropic shale using digital volume correlation of time-resolved X-ray microtomography images MANUAL Francois Renard, and Jessica McBeck. "Investigating the onset of strain localization within anisotropic shale using digital volume correlation of time-resolved X-ray microtomography images." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/2cee7168-1254-46dc-80cd-e3910724e61e. data raw data biblio metadata https://doi.org/10.1029/2018JB015676. 2022-03-22 00:50:51.137828+00:00 2022-03-22 00:50:51.236563+00:00 https://doi.org/10.1029/2018JB015676. 2022-03-22 00:50:51.137828+00:00 Renard, F., McBeck, J. (2018).Investigating the onset of strain localization within anisotropic shale using digital volume correlation of time-resolved X-ray microtomography images [Data set]. Norstore. https://doi.org/10.11582/2018.00005 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00005 2018-02-20 00:00:00 2022-03-22 00:50:53.797555+00:00 The archive contains the dynamic X-ray tomography data of two Green River shale samples undergoing deformation. Samples GRS01 and GRS02 Investigating the onset of strain localization within anisotropic shale using digital volume correlation of time-resolved X-ray microtomography images 2018-02-20 00:00:00 Francois Renard francois.renard@rohub.com Francois Renard Geo H. jessica.mcbeck@rohub.com Jessica McBeck Environmental research Neurobiology Life sciences Physical sciences cells from hippocampus cells for path integration anatomy cell hippocampus rat path integration et al 2018 path integration path et al service-account-enrichment 7473 https://api.rohub.org/api/ros/adc3405d-90ee-4c83-9704-8aaabdee5802/crate/download/ 2022-03-22 00:51:07.079263+00:00 2025-03-05 00:48:36.145390+00:00 2022-03-22 00:51:07.079263+00:00 Cells from hippocampus with path integration-dependent firing in young rats application/ld+json https://w3id.org/ro-id/adc3405d-90ee-4c83-9704-8aaabdee5802 Cells for path integration in young rats (Bjerknes et al 2018) MANUAL Tale Bjerknes. "Cells for path integration in young rats (Bjerknes et al 2018)." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/adc3405d-90ee-4c83-9704-8aaabdee5802. data metadata raw data biblio Bjerknes, T. (2018).Cells for path integration in young rats (Bjerknes et al 2018) [Data set]. Norstore. https://doi.org/10.11582/2018.00003 Edvard Ingjald Moser Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2018.00003 2018-01-17 00:00:00 2022-03-22 00:51:18.488669+00:00 Cells from hippocampus with path integration-dependent firing in young rats Cells for path integration in young rats (Bjerknes et al 2018) 2018-01-17 00:00:00 Edvard Ingjald Moser Geo H. tale.bjerknes@rohub.com Tale Bjerknes Environmental research Life sciences Physical sciences Earth sciences evolution of damage monzonite rock X-ray tomography data geology development rock x-ray data system imaging fail monzonite archive size crystalline rock damage sample system size failure failure in a crystalline rock service-account-enrichment 8038 https://api.rohub.org/api/ros/3a7aa719-ccfc-4cfc-89d2-c9d9c31e7737/crate/download/ 2022-03-22 00:51:19.763139+00:00 2025-03-05 00:50:03.869659+00:00 2022-03-22 00:51:19.763139+00:00 The archive contains the X-ray tomography data of two samples of monzonite rock during deformation. application/ld+json https://w3id.org/ro-id/3a7aa719-ccfc-4cfc-89d2-c9d9c31e7737 Critical evolution of damage towards system size failure in a crystalline rock MANUAL Francois Renard. "Critical evolution of damage towards system size failure in a crystalline rock." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/3a7aa719-ccfc-4cfc-89d2-c9d9c31e7737. raw data biblio metadata data https://doi.org/10.1002/2017JB014964 2022-03-22 00:51:30.283596+00:00 2022-03-22 00:51:30.382361+00:00 https://doi.org/10.1002/2017JB014964 2022-03-22 00:51:30.283596+00:00 Renard, F. (2017).Critical evolution of damage towards system size failure in a crystalline rock [Data set]. Norstore. https://doi.org/10.11582/2017.00025 Francois Renard Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2017.00025 2017-11-12 00:00:00 2022-03-22 00:51:32.656753+00:00 The archive contains the X-ray tomography data of two samples of monzonite rock during deformation. Critical evolution of damage towards system size failure in a crystalline rock 2017-11-12 00:00:00 Francois Renard francois.renard@rohub.com Francois Renard Geo H. Environmental research Neurobiology Life sciences Physical sciences Wernle et al cell data publication grid network use in the publication et al grid grid map format map merged environment integration environment service-account-enrichment 7411 https://api.rohub.org/api/ros/520b717a-664c-41ef-9afe-8d98fb25c4aa/crate/download/ 2022-03-22 00:51:34.042480+00:00 2025-03-05 00:59:18.161447+00:00 2022-03-22 00:51:34.042480+00:00 Data and analysis used in the publication: Wernle, T. et al., 2017, "Integration of grid maps in merged environments" (NN-A60549A). format: Matlab. application/ld+json https://w3id.org/ro-id/520b717a-664c-41ef-9afe-8d98fb25c4aa Grid cell data Wernle et al 2017 MANUAL Tanja Wernle, and Kavli Institute for Systems Neuroscience. "Grid cell data Wernle et al 2017." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/520b717a-664c-41ef-9afe-8d98fb25c4aa. metadata raw data biblio data https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2017.00023 2022-03-22 00:51:48.500032+00:00 2022-03-22 00:51:53.630316+00:00 Data and analysis used in the publication: Wernle, T. et al., 2017, "Integration of grid maps in merged environments" (NN-A60549A). format: Matlab. Grid cell data Wernle et al 2017 2022-03-22 00:51:48.500032+00:00 https://www.nature.com/articles/s41593-017-0036-6 2022-03-22 00:51:50.821986+00:00 2022-03-22 00:51:50.934370+00:00 https://www.nature.com/articles/s41593-017-0036-6 2022-03-22 00:51:50.821986+00:00 Geo H. kavli.institute.for.systems.neuroscience@rohub.com Kavli Institute for Systems Neuroscience tanja.wernle@rohub.com Tanja Wernle Environmental research Neurobiology Life sciences Physical sciences service-account-enrichment 9382 https://api.rohub.org/api/ros/bfab61ab-8d3a-4c8a-956a-0d05839af73b/crate/download/ 2022-03-22 00:52:01.044504+00:00 2025-03-05 00:59:17.928916+00:00 2022-03-22 00:52:01.044504+00:00 Data and analysis used in the publication: Wernle, T. et al., 2017, "Integration of grid maps in merged environments" (NN-A60549A). format: Matlab. application/ld+json https://w3id.org/ro-id/bfab61ab-8d3a-4c8a-956a-0d05839af73b Grid cell data Wernle et al 2017 MANUAL cell data environment format grid information integration long ton publication earth sciences IT-computer sciences analysis data environment format grid integration publication geosciences al 2017 et al 2017 grid map merged environment use in the publication Data and analysis used in the publication: Wernle, T. et al. 2017, "Integration of grid maps in merged environments" (NN-A60549A) format: Matlab. Grid cell data Wernle et al 2017. anatomy computer science Tanja Wernle, and Kavli Institute for Systems Neuroscience. "Grid cell data Wernle et al 2017." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/bfab61ab-8d3a-4c8a-956a-0d05839af73b. data metadata biblio raw data Wernle, T., Kavli Institute for Systems Neuroscience (2017).Grid cell data Wernle et al 2017 [Data set]. Norstore. https://doi.org/10.11582/2017.00023 Edvard Ingjald Moser Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2017.00021 2017-10-30 00:00:00 2022-03-22 00:52:21.717362+00:00 Data and analysis used in the publication: Wernle, T. et al., 2017, "Integration of grid maps in merged environments" (NN-A60549A). format: Matlab. Grid cell data Wernle et al 2017 2017-10-30 00:00:00 Edvard Ingjald Moser https://doi.org/10.1038/s41593-017-0036-6 2022-03-22 00:52:18.899877+00:00 2022-03-22 00:52:18.996862+00:00 https://doi.org/10.1038/s41593-017-0036-6 2022-03-22 00:52:18.899877+00:00 Geo H. kavli.institute.for.systems.neuroscience@rohub.com Kavli Institute for Systems Neuroscience tanja.wernle@rohub.com Tanja Wernle Environmental research Neurobiology Life sciences Physical sciences phase precession dataset doi data plant cell dataset grid network et al grid cell data information precedence phase entorhinal grid cell service-account-enrichment 7038 https://api.rohub.org/api/ros/cd45de5c-5cd2-4dc1-a0ab-54f4990a22a5/crate/download/ 2022-03-22 00:52:22.800226+00:00 2025-03-05 00:59:17.260814+00:00 2022-03-22 00:52:22.800226+00:00 Spike-time data for grid cells. Data was used in the publication: Hafting, T. et al, 2008, "Hippocampus-independent phase precession in entorhinal grid cells", Nature, 453, 1248-1252 (doi:10.1038/nature06957) This dataset is an older version of the published dataset doi: 10.11582/2014.00004 with data put online before Norstore Research Archive was available. application/ld+json https://w3id.org/ro-id/cd45de5c-5cd2-4dc1-a0ab-54f4990a22a5 Grid cell data; Hafting et al 2008 MANUAL Torkel Hafting, and Centre for the Biology of Memory (CBM). "Grid cell data; Hafting et al 2008." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/cd45de5c-5cd2-4dc1-a0ab-54f4990a22a5. metadata biblio raw data data https://www.nature.com/nature/journal/v453/n7199/full/nature06957.html 2022-03-22 00:52:37.677801+00:00 2022-03-22 00:52:37.800529+00:00 text/html https://www.nature.com/nature/journal/v453/n7199/full/nature06957.html 2022-03-22 00:52:37.677801+00:00 https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2017.00020 2022-03-22 00:52:35.528433+00:00 2022-03-22 00:52:40.460055+00:00 Spike-time data for grid cells. Data was used in the publication: Hafting, T. et al, 2008, "Hippocampus-independent phase precession in entorhinal grid cells", Nature, 453, 1248-1252 (doi:10.1038/nature06957) This dataset is an older version of the published dataset doi: 10.11582/2014.00004 with data put online before Norstore Research Archive was available. Grid cell data; Hafting et al 2008 2022-03-22 00:52:35.528433+00:00 CBM@rohub.com Centre for the Biology of Memory (CBM) Geo H. torkel.hafting@rohub.com Torkel Hafting Environmental research Neurobiology Life sciences Physical sciences grid scale scale from dorsal dataset doi cell data dataset grid network et al warning information Brun et al service-account-enrichment 7677 https://api.rohub.org/api/ros/e6f26cbc-a400-4bfc-87d2-cd94c3a404b8/crate/download/ 2022-03-22 00:52:41.640806+00:00 2025-03-05 00:59:15.807463+00:00 2022-03-22 00:52:41.640806+00:00 WARNING THIS DATASET HAS SOME ISSUES. Spike-time data for grid cells. Data used in the publication: Brun, V., 2008, "Progressive increase in grid scale from dorsal to ventral medial entorhinal cortex", Hippocampus, 18, 1200–1212. This dataset is an older version of the published dataset doi: 10.11582/2014.00002 with data put online before Norstore Research Archive was available. application/ld+json https://w3id.org/ro-id/e6f26cbc-a400-4bfc-87d2-cd94c3a404b8 Grid cell data Brun et al 2008 MANUAL Centre for the Biology of Memory (CBM), and Vegard Brun. "Grid cell data Brun et al 2008." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/e6f26cbc-a400-4bfc-87d2-cd94c3a404b8. biblio data metadata raw data http://onlinelibrary.wiley.com/doi/10.1002/hipo.20504/abstract 2022-03-22 00:52:55.251932+00:00 2022-03-22 00:52:55.368450+00:00 http://onlinelibrary.wiley.com/doi/10.1002/hipo.20504/abstract 2022-03-22 00:52:55.251932+00:00 https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2017.00018 2022-03-22 00:52:52.597056+00:00 2022-03-22 00:53:01.619885+00:00 WARNING THIS DATASET HAS SOME ISSUES. Spike-time data for grid cells. Data used in the publication: Brun, V., 2008, "Progressive increase in grid scale from dorsal to ventral medial entorhinal cortex", Hippocampus, 18, 1200–1212. This dataset is an older version of the published dataset doi: 10.11582/2014.00002 with data put online before Norstore Research Archive was available. Grid cell data Brun et al 2008 2022-03-22 00:52:52.597056+00:00 CBM@rohub.com Centre for the Biology of Memory (CBM) Geo H. vegard.brun@rohub.com Vegard Brun Environmental research Neurobiology Life sciences Physical sciences conjunctive representation dataset doi scientific discipline conjunctive data plant cell dataset grid network velocity in Entorhinal Cortex et al data for grid cell information service-account-enrichment 7031 https://api.rohub.org/api/ros/80d4357d-91a4-435c-a92d-b1c04afe4c0f/crate/download/ 2022-03-22 00:53:02.694198+00:00 2025-03-05 00:59:17.481084+00:00 2022-03-22 00:53:02.694198+00:00 Spike-time data for grid cells. Data used in the publidation: Sargolini, F. et al, 2006, "Conjunctive Representation of Position, Direction, and Velocity in Entorhinal Cortex", Science 312 (5774), 758-612 (doi:10.1126/science.1125572) This dataset is an older version of the published dataset doi: 10.11582/2014.00003 with data put online before Norstore Research Archive was available. application/ld+json https://w3id.org/ro-id/80d4357d-91a4-435c-a92d-b1c04afe4c0f Grid cell data Sargolini et al 2006 MANUAL Fransesca Sargolini, and Centre for the Biology of Memory (CBM). "Grid cell data Sargolini et al 2006." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/80d4357d-91a4-435c-a92d-b1c04afe4c0f. metadata data biblio raw data http://science.sciencemag.org/content/312/5774/758 2022-03-22 00:53:17.431019+00:00 2022-03-22 00:53:17.534207+00:00 http://science.sciencemag.org/content/312/5774/758 2022-03-22 00:53:17.431019+00:00 https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2017.00019 2022-03-22 00:53:14.972694+00:00 2022-03-22 00:53:20.005996+00:00 Spike-time data for grid cells. Data used in the publidation: Sargolini, F. et al, 2006, "Conjunctive Representation of Position, Direction, and Velocity in Entorhinal Cortex", Science 312 (5774), 758-612 (doi:10.1126/science.1125572) This dataset is an older version of the published dataset doi: 10.11582/2014.00003 with data put online before Norstore Research Archive was available. Grid cell data Sargolini et al 2006 2022-03-22 00:53:14.972694+00:00 CBM@rohub.com Centre for the Biology of Memory (CBM) fransesca.sargolini@rohub.com Fransesca Sargolini Geo H. Environmental research Neurobiology Life sciences Physical sciences dataset doi data publication plant cell dataset microstructure grid network et al entorhinal cortex cortices data for grid cell information microstructure of a spatial map spatial service-account-enrichment 7674 https://api.rohub.org/api/ros/cbe0dfee-32f4-4ccc-9ea0-e4611abfe72a/crate/download/ 2022-03-22 00:53:20.970356+00:00 2025-03-05 00:59:16.512187+00:00 2022-03-22 00:53:20.970356+00:00 Spike-time data for grid cells. The data was used in the publication: Hafting, T. et al, 2005, "Microstructure of a spatial map in the entorhinal cortex", 436, 801-806 (doi:10.1038/nature03721). This dataset is an older version of the published dataset doi:10.11582/2014.00001 with data put online before Norstore Research Archive was available. application/ld+json https://w3id.org/ro-id/cbe0dfee-32f4-4ccc-9ea0-e4611abfe72a Grid cell data Hafting et al 2005 MANUAL Torkel Hafting, and Centre for the Biology of Memory (CBM). "Grid cell data Hafting et al 2005." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/cbe0dfee-32f4-4ccc-9ea0-e4611abfe72a. data raw data metadata biblio https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2017.00017 2022-03-22 00:53:32.283095+00:00 2022-03-22 00:53:37.194021+00:00 Spike-time data for grid cells. The data was used in the publication: Hafting, T. et al, 2005, "Microstructure of a spatial map in the entorhinal cortex", 436, 801-806 (doi:10.1038/nature03721). This dataset is an older version of the published dataset doi:10.11582/2014.00001 with data put online before Norstore Research Archive was available. Grid cell data Hafting et al 2005 2022-03-22 00:53:32.283095+00:00 http://www.nature.com/nature/journal/v436/n7052/full/nature03721.html 2022-03-22 00:53:34.390597+00:00 2022-03-22 00:53:34.483565+00:00 text/html http://www.nature.com/nature/journal/v436/n7052/full/nature03721.html 2022-03-22 00:53:34.390597+00:00 CBM@rohub.com Centre for the Biology of Memory (CBM) Geo H. torkel.hafting@rohub.com Torkel Hafting Environmental research Life sciences Physical sciences Earth sciences service-account-enrichment 8905 https://api.rohub.org/api/ros/afc95f4d-ef46-47bf-a284-89e1bd53495b/crate/download/ 2022-03-22 00:53:38.169196+00:00 2025-03-05 12:49:07.914643+00:00 2022-03-22 00:53:38.169196+00:00 This dataset is collective static information outputted by the TOPAZ4 reanalysis in 1991-2013. They include the assimilated observations and the concerned optimization information using the EnKF. Also they are ones of the basic reference datasets for the paper of “Quality assessment of the TOPAZ4 reanalysis in the Arctic over the period 1991–2013” accepted by Ocean Science in January 2017. The file ensemble-static-TOPAZ4-part0.tar.gz contains files before 20000 (Julian day relative to 1/1/1950) and ensemble-static-TOPAZ4-part1.tar.gz contains files after 20000. application/ld+json https://w3id.org/ro-id/afc95f4d-ef46-47bf-a284-89e1bd53495b Observations and ensemble statics of the TOPAZ4 reanalysis of 1991-2013 MANUAL Arctic Zone data dataset file information optimisation re-analysis earth sciences IT-computer sciences EnKF Ocean Science TOPAZ4 dataset information optimization reanalysis geosciences ensemble statics of the TOPAZ4 reanalysis optimization information quality assessment of the TOPAZ4 reanalysis reference dataset static information Observations and ensemble statics of the TOPAZ4 reanalysis of 1991-2013. Quality assessment of the TOPAZ4 reanalysis in the Arctic over the period 1991? This dataset is collective static information outputted by the TOPAZ4 reanalysis in 1991-2013. 2013 in 1991-2013 in Jan-2017 of 1991-2013 over the period 1991 to Jan-1-1950 computer science database Arctic Zone Jiping Xie. "Observations and ensemble statics of the TOPAZ4 reanalysis of 1991-2013." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/afc95f4d-ef46-47bf-a284-89e1bd53495b. biblio data raw data metadata Xie, J. (2017).Observations and ensemble statics of the TOPAZ4 reanalysis of 1991-2013 [Data set]. Norstore. https://doi.org/10.11582/2017.00001 Jiping Xie Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2017.00001 2017-02-10 00:00:00 2022-03-22 00:53:50.382451+00:00 This dataset is collective static information outputted by the TOPAZ4 reanalysis in 1991-2013. They include the assimilated observations and the concerned optimization information using the EnKF. Also they are ones of the basic reference datasets for the paper of “Quality assessment of the TOPAZ4 reanalysis in the Arctic over the period 1991–2013” accepted by Ocean Science in January 2017. The file ensemble-static-TOPAZ4-part0.tar.gz contains files before 20000 (Julian day relative to 1/1/1950) and ensemble-static-TOPAZ4-part1.tar.gz contains files after 20000. Observations and ensemble statics of the TOPAZ4 reanalysis of 1991-2013 2017-02-10 00:00:00 Jiping Xie http://www.ocean-sci-discuss.net/os-2016-38/os-2016-38.pdf 2022-03-22 00:53:47.890303+00:00 2022-03-22 00:53:48.002348+00:00 application/pdf http://www.ocean-sci-discuss.net/os-2016-38/os-2016-38.pdf 2022-03-22 00:53:47.890303+00:00 Geo H. jiping.xie@rohub.com Jiping Xie Environmental research Life sciences Physical sciences Genetics genomic sequence data sequence data genome extinct bird species mitochondrial genome mitochondrial information sequence complete mitochondrial genome service-account-enrichment 7460 https://api.rohub.org/api/ros/ee01f9e4-3ad0-4577-b626-5c9103eebe3c/crate/download/ 2022-03-22 00:53:51.362614+00:00 2025-03-05 00:47:01.514306+00:00 2022-03-22 00:53:51.362614+00:00 Whole genomic sequence data from 11 extinct bird species application/ld+json https://w3id.org/ro-id/ee01f9e4-3ad0-4577-b626-5c9103eebe3c Complete mitochondrial genomes of eleven extinct or possibly extinct bird species MANUAL Jarl Andreas Anmarkrud. "Complete mitochondrial genomes of eleven extinct or possibly extinct bird species." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/ee01f9e4-3ad0-4577-b626-5c9103eebe3c. data raw data biblio metadata Anmarkrud, J. A. (2016).Complete mitochondrial genomes of eleven extinct or possibly extinct bird species [Data set]. Norstore. https://doi.org/10.11582/2016.00006 Jarl Andreas Anmarkrud Experiment https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2016.00006 2016-11-17 00:00:00 2022-03-22 00:54:02.996258+00:00 Whole genomic sequence data from 11 extinct bird species Complete mitochondrial genomes of eleven extinct or possibly extinct bird species 2016-11-17 00:00:00 Jarl Andreas Anmarkrud Geo H. jarl.andreas.anmarkrud@rohub.com Jarl Andreas Anmarkrud