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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. 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"https://w3id.org/ro-id/0d5a0619-14d5-4b45-b925-a9432684f76a/4b10ec21-8232-4aee-b23d-ee9f37dce383"; "Anne Foilloux, and Jean Iaquinta. \"Jupyter notebook demonstrating the usage of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services - snapshot.\" ROHub. Jan 18 ,2022. https://w3id.org/ro-id/0d5a0619-14d5-4b45-b925-a9432684f76a." . a , ; , , , ; "input" . a , ; , , , , ; "output" . a , ; ; "tool" . a , ; "biblio" . a , ; "Daily average of CAMS Particule matter < 10 μm [μg/m3] over Paris in September 2021"; "Timeseries of particule matter < 10 μm [μg/m3] over Paris in september 2021" . a , ; "This dataset is a data-Cube retrieved from the ADAM platform over France in September 2019"; "Data-Cube from ADAM platform over France in September 2019" . a , ; ; "https://datahub.egi.eu/share/117f0e2a8b5d6615974c6a941b093804ch8b23"; ; "2022-01-18 18:30:06.117346+00:00"; "2022-01-18 18:30:54.343006+00:00"; ; "https://datahub.egi.eu/share/117f0e2a8b5d6615974c6a941b093804ch8b23"; "2022-01-18 18:30:06.117346+00:00" . a , ; "This dataset is a data-Cube retrieved from the ADAM platform over France in September 2020"; "Data-Cube from ADAM platform over France in September 2020" . a , ; "Geojson file used for retrieving data from the ADAM platform over France"; "Geojson for France" . a , ; ; "https://datahub.egi.eu/share/0e87b0cdd21a4c147952d99ed302a957ch3802"; ; "2022-01-18 18:30:02.737890+00:00"; "2022-01-18 18:30:54.402658+00:00"; ; "https://datahub.egi.eu/share/0e87b0cdd21a4c147952d99ed302a957ch3802"; "2022-01-18 18:30:02.737890+00:00" . a , ; "Jupyter Notebook for discovering, accessing and processing RELIANCE data cube, and creating a Research Object with results, and finally publish it in Zenodo"; "Jupyter Notebook of CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services" . a , ; ; "https://datahub.egi.eu/share/f35b2956fc60a70f493e91278e08e3abchf56d"; ; "2022-01-18 18:30:26.410290+00:00"; "2022-01-18 18:30:54.498308+00:00"; ; "https://datahub.egi.eu/share/f35b2956fc60a70f493e91278e08e3abchf56d"; "2022-01-18 18:30:26.410290+00:00" . a , ; ; "https://datahub.egi.eu/share/e0e426bfbea07306695b82068898bdcachaa15"; ; "2022-01-18 18:30:31.670405+00:00"; "2022-01-18 18:30:54.569917+00:00"; ; "https://datahub.egi.eu/share/e0e426bfbea07306695b82068898bdcachaa15"; "2022-01-18 18:30:31.670405+00:00" . a , ; "Monthly average maps of CAMS Particule matter < 10 μm [μg/m3] over France in 2019, 2020 and 2021"; "Particule matter < 10 μm [μg/m3] over France for September 2019, 2020 and 2021" . a , ; "Monthly average maps of CAMS Particule matter < 10 μm [μg/m3] over France in 2019, 2020 and 2021"; "Particule matter < 10 μm [μg/m3] over France for September 2019, 2020 and 2021" . a , ; ; "https://datahub.egi.eu/share/a078eb09f1e3822c806bdc9cc530288bchf4c2"; ; "2022-01-18 18:30:29.465828+00:00"; "2022-01-18 18:30:54.623804+00:00"; ; "https://datahub.egi.eu/share/a078eb09f1e3822c806bdc9cc530288bchf4c2"; "2022-01-18 18:30:29.465828+00:00" . a , ; "netCDF data corresponding to daily average of CAMS Particule matter < 10 μm [μg/m3] over France for September 2019, September 2020 and September 2021"; "netCDF data for daily PM10 concentration over France in September 2019, 2020 and 2021" . a , ; ; "https://datahub.egi.eu/share/e5580c9233f571eacf7eb8ef71c0d7dcch294a"; ; "2022-01-18 18:30:23.256523+00:00"; "2022-01-18 18:30:54.532963+00:00"; ; "https://datahub.egi.eu/share/e5580c9233f571eacf7eb8ef71c0d7dcch294a"; "2022-01-18 18:30:23.256523+00:00" . a , ; ; "https://datahub.egi.eu/share/0ed7237e5dc09ba8ff353697fef6fc96ch04c1"; ; "2022-01-18 18:30:04.435676+00:00"; "2022-01-18 18:30:54.374174+00:00"; ; "https://datahub.egi.eu/share/0ed7237e5dc09ba8ff353697fef6fc96ch04c1"; "2022-01-18 18:30:04.435676+00:00" . a , ; ; "154837"^^xsd:integer; "https://api.rohub.org/api/resources/c13c349b-c738-4e88-82fa-c67b56f8f08d/download/"; ; "2022-01-18 18:28:39.211870+00:00"; "2022-01-18 18:30:55.438746+00:00"; "image/png"; ; "PM10_september_FR_2019-2021.png"; "2022-01-18 18:28:39.211870+00:00" . a , ; "Daily average maps of CAMS Particule matter < 10 μm [μg/m3] over France on September 15, 2021"; "Particule matter < 10 μm [μg/m3] over France on September 15, 2021" . a , ; ; "https://datahub.egi.eu/share/617299120e542500102b06860f1e6e15ch2f25"; ; "2022-01-18 18:30:19.396255+00:00"; "2022-01-18 18:30:55.512286+00:00"; ; "https://datahub.egi.eu/share/617299120e542500102b06860f1e6e15ch2f25"; "2022-01-18 18:30:19.396255+00:00" . a , ; "This dataset is a data-Cube retrieved from the ADAM platform over France in September 2021"; "Data-Cube from ADAM platform over France in September 2021" . a , ; ; "https://datahub.egi.eu/share/8368086b44835af9620d9f0eccf18d7bch39cc"; ; "2022-01-18 18:29:59.231939+00:00"; "2022-01-18 18:30:54.431313+00:00"; ; "https://datahub.egi.eu/share/8368086b44835af9620d9f0eccf18d7bch39cc"; "2022-01-18 18:29:59.231939+00:00" . a ; dct:conformsTo ; . a , ; "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, 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Feb 17 ,2022. https://doi.org/10.24424/kh1w-th55." . a , ; ; "biblio" . a , ; ; "data" . a , ; "myfolder" . a , ; "mysubfolder" . a , ; "raw data" . a , ; "metadata" . a , ; ; "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" . a , ; """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" . a , ; "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" . a , ; ; "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" . a , ; ; "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" . a , ; "Daily PM10 concentration for 1st September 2018 over Europe"; "Daily PM10 concentration" . a , ; "This resource has this description"; "Flow to compute monthly map - updated" . a , ; "List of hourly PM10 concentration data for September 1st 2018 over Europe"; "Index of daily PM10 concentration for September 1st 2018" . a , ; ; "73394"^^xsd:integer; "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" . a , ; 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"2022-03-11 10:09:34.280134+00:00"; "This Research Object aggregates all the resources needed for running Galaxy EODIE: i) Examples of input datasets needed for running EODIE on Galaxy; ii) Galaxy Workflow (.ga) and corresponding CWL abstract and diagram; iii) Link to a published Galaxy history."; "application/ld+json"; ; ; , , , ; "https://w3id.org/ro-id/7f907b0e-d08b-4d55-a272-7561564d8272"; "copernicus", "earth observation", "galaxy", "sentinel-2"; ; "EODIE Galaxy Tool Research Object showing its usage in Galaxy Europe", "Galaxy EODIE Tool Example - snapshot"; , ; "MANUAL"; "False"; "https://w3id.org/ro-id/7f907b0e-d08b-4d55-a272-7561564d8272/19e8c40b-3247-4262-beb1-023d73cd3ac0", "https://w3id.org/ro-id/7f907b0e-d08b-4d55-a272-7561564d8272/26eb3f89-d160-4b0c-a5d9-e1da72c0cb68", "https://w3id.org/ro-id/7f907b0e-d08b-4d55-a272-7561564d8272/38f18eb0-32db-4096-ab87-65d06506b13e", "https://w3id.org/ro-id/7f907b0e-d08b-4d55-a272-7561564d8272/b2f4e417-3edc-4c7d-92e4-add7e54622f0"; "https://w3id.org/ro-id/dcc8604a-ba39-41b7-a080-4970badab8f8"; 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"https://w3id.org/ro-id/3e04294e-c7f9-4a83-b199-7ab3281cbd82", "https://w3id.org/ro-id/89bf1a14-9db7-43a7-ac0e-cdb9cd285d2e"; "https://w3id.org/ro-id/094ade67-5f22-448c-a8b5-e43744373618", "https://w3id.org/ro-id/3f7e4bbd-214c-4984-9291-79265f603230", "https://w3id.org/ro-id/5e361137-82f7-44ad-a5b1-bf0262caf26c", "https://w3id.org/ro-id/e92d7fd8-ba2c-4b67-8b9b-f6e4896dc13b", "https://w3id.org/ro-id/e98705e7-5c22-4d36-9f48-40c5e62bd208"; "https://w3id.org/ro-id/9c67bd11-95f4-4308-ad6e-b2d7a8edb5f9", "https://w3id.org/ro-id/e2075c38-7a18-4b42-845d-00e4ead8c77d"; "Anne Foilloux, and Samantha Wittke. \"EODIE Galaxy Tool Research Object showing its usage in Galaxy Europe.\" ROHub. Mar 11 ,2022. https://doi.org/10.24424/4fpx-ks69." . a , ; "POLYGON ((24.18406744995054 61.18989752053165, 24.18674075775491 61.19037141598483, 24.18716156079448 61.18986424310414, 24.185956130552082 61.18912805997288, 24.18430110034565 61.188898431974906, 24.18406744995054 61.18989752053165))" . a , ; "POLYGON ((22.811822629936163 60.294519011902665, 24.91411237826359 60.294519011902665, 24.91411237826359 61.32117938698947, 22.811822629936163 61.32117938698947, 22.811822629936163 60.294519011902665))" . a , ; "POLYGON ((24.192215188374867 61.18501915071051, 24.19578893147163 61.186083237631095, 24.19715287272243 61.184061770037154, 24.19399282834134 61.18289474417407, 24.192215188374867 61.18501915071051))" . a , ; "POLYGON ((24.18964452411491 61.191826100745374, 24.196058374024226 61.192475014763325, 24.196205529001745 61.19179482361619, 24.19026064542983 61.19107198695369, 24.18964452411491 61.191826100745374))" . a , ; ; "biblio" . a , ; , , ; "input" . a , ; , , , , ; "tool" . a , ; , , ; "output" . a , ; "This Python Jupyter Notebook load this Research Object, update it e.g. add additional metadata information and fill its content. It also show the area of interest by visualizing the Sentinel-2 tile and the parccel shapefile where NDVI is calculated with EODIE Galaxy Tool."; "Jupyter Notebook to update Research Object and visualize area of interest" . a , ; ; "https://climate.usegalaxy.eu/datasets/11ac94870d0bb33a7f87b4af1c86f136/display?to_ext=shp"; ; "2022-03-11 12:49:24.260353+00:00"; "2022-03-12 15:15:47.216730+00:00"; ; "https://climate.usegalaxy.eu/datasets/11ac94870d0bb33a7f87b4af1c86f136/display?to_ext=shp"; "2022-03-11 12:49:24.260353+00:00" . a , ; ; "https://eodie.readthedocs.io/en/latest/"; ; "2022-03-11 10:13:54.654033+00:00"; "2022-03-12 15:15:46.885102+00:00"; ; "https://eodie.readthedocs.io/en/latest/"; "2022-03-11 10:13:54.654033+00:00" . a , ; ; "https://doi.org/10.5281/zenodo.4762323"; ; "2022-03-11 12:22:30.810417+00:00"; "2022-03-12 15:15:50.426715+00:00"; ; "https://doi.org/10.5281/zenodo.4762323"; "2022-03-11 12:22:30.810417+00:00" . a , ; "This input dataset is a shapefile corresponding the the area of interest e.g. on which statistics such as NDVI will be computed."; "test_parcels_32635" . a , ; ; "https://climate.usegalaxy.eu/datasets/11ac94870d0bb33a35a2897d442f793e/display?to_ext=shp"; ; "2022-03-11 12:48:40.259848+00:00"; "2022-03-12 15:15:47.399170+00:00"; ; "https://climate.usegalaxy.eu/datasets/11ac94870d0bb33a35a2897d442f793e/display?to_ext=shp"; "2022-03-11 12:48:40.259848+00:00" . a , ; "This is a link to Workflow Research Object stored in workflowhub.eu. It contains a Galaxy workflow (.ga), abstract CWL (.cwl) and diagram (.png)."; "Galaxy Workflow for EODIE Galaxy Tool" . a , ; ; "https://toolshed.g2.bx.psu.edu/view/climate/eodie/81b0ca76435d"; ; "2022-03-12 14:23:32.995366+00:00"; "2022-03-12 15:15:50.335647+00:00"; ; "https://toolshed.g2.bx.psu.edu/view/climate/eodie/81b0ca76435d"; "2022-03-12 14:23:32.995366+00:00" . a , ; ; "https://workflowhub.eu/workflows/274"; ; "2022-03-11 12:38:11.563886+00:00"; "2022-03-12 15:15:50.537808+00:00"; ; "https://workflowhub.eu/workflows/274"; "2022-03-11 12:38:11.563886+00:00" . a , ; ; "https://climate.usegalaxy.eu/datasets/11ac94870d0bb33a1d47bf13200d6d20/display?to_ext=txt"; ; "2022-03-11 12:56:45.981431+00:00"; "2022-03-12 15:15:48.030119+00:00"; ; "https://climate.usegalaxy.eu/datasets/11ac94870d0bb33a1d47bf13200d6d20/display?to_ext=txt"; "2022-03-11 12:56:45.981431+00:00" . a , ; "Abstract CWL Automatically generated from the Galaxy workflow file: Workflow constructed from history 'EODIE Sentinel'"; "Abstract CWL figure for EODIE Galaxy Tool" . a , ; ; "https://climate.usegalaxy.eu/datasets/11ac94870d0bb33a325d171940e10e66/display?to_ext=tar"; ; "2022-03-11 12:47:07.047116+00:00"; "2022-03-12 15:15:47.705381+00:00"; ; "https://climate.usegalaxy.eu/datasets/11ac94870d0bb33a325d171940e10e66/display?to_ext=tar"; "2022-03-11 12:47:07.047116+00:00" . a , ; ; "https://workflowhub.eu/workflows/274/diagram?version=1"; ; "2022-03-11 12:44:21.317999+00:00"; "2022-03-12 15:15:48.334662+00:00"; ; "https://workflowhub.eu/workflows/274/diagram?version=1"; "2022-03-11 12:44:21.317999+00:00" . a , ; ; "https://climate.usegalaxy.eu/datasets/11ac94870d0bb33a15a5227662283bd6/display?to_ext=data&hdca_id=f0508a112d4c9309&element_identifier=ndvi_20200626_34VFN_statistics.csv"; ; "2022-03-11 12:54:38.554141+00:00"; "2022-03-12 15:15:48.196664+00:00"; ; "https://climate.usegalaxy.eu/datasets/11ac94870d0bb33a15a5227662283bd6/display?to_ext=data&hdca_id=f0508a112d4c9309&element_identifier=ndvi_20200626_34VFN_statistics.csv"; "2022-03-11 12:54:38.554141+00:00" . a , ; "This output is the logfile generated when running EODIE Galaxy Tool over the specified geographical area (test_parcels_32635) and with the input Sentinel-2 dataset."; "logfile" . a , ; "This output dataset is a csv file containing NDVI values computed over the specific geographical area e.g. given by the input shapefile called 'test_parcels_32635'."; "ndvi_20200626_34VFN_statistics.csv" . a , ; "10.5281/zenodo.4762323"; "Tarball containing the EODIE source code release 1.0.2 and its associated documentation."; "Source code of EODIE version 1.0.2 (zenodo)" . a , ; "This input dataset corresponds to the Sentinel-2 tile shapefile, originally provided by https://fromgistors.blogspot.com/2016/10/how-to-identify-sentinel-2-granule.html,"; "sentinel2_tiles_world" . a , ; ; "https://usegalaxy.eu/u/annefou/h/eodie-sentinel-1"; ; "2022-03-12 14:27:30.928413+00:00"; "2022-03-12 15:15:48.697531+00:00"; ; "https://usegalaxy.eu/u/annefou/h/eodie-sentinel-1"; "2022-03-12 14:27:30.928413+00:00" . a , ; "Link to the Galaxy Tool shed for EODIE Galaxy Tool repository. This repository is useful whenever you want to install EODIE Galaxy Tool in your own Galaxy instance. The version used in this example is revision: 0:81b0ca76435d"; "Galaxy Toolshed for EODIE Galaxy Tool repository" . a , ; "Sentinel2 input data. This input dataset corresponds to the data itself while sentinel2_tiles_world would be the corresponding shapefile for the tile."; "S2B_MSIL2A_20200626T095029_N0214_R079_T34VFN_20200626T123234.tar" . a , ; "Online documentation of EODIE Toolkit."; "EODIE documentation" . a , ; "This Galaxy history contains all the inputs and generated outputs for this EODIE example. 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To this, is added the pervasive and growing effects of human-induced perturbations of the climate system. International frameworks provide foundations for the protection of deep-sea ecosystems, but the lack of standardized criteria for the identification of areas deserving protection, insufficient legislative instruments and poor implementation hinder an efficient set up in practical terms. Here, we discuss the international legal frameworks and management measures in relation to the status of habitats and key species in the deep Mediterranean Basin. By comparing the results of a multi-criteria decision analysis (MCDA) and of expert evaluation (EE), we identify priority deep-sea areas for conservation and select five criteria for the designation of future protected areas in the deep Mediterranean Sea. Our results indicate that areas (1) with high ecological relevance (e.g., hosting endemic and locally endangered species and rare habitats),(2) ensuring shelf-slope connectivity (e.g., submarine canyons), and (3) subject to current and foreseeable intense anthropogenic impacts, should be prioritized for conservation. The results presented here provide an ecosystem-based conservation strategy for designating priority areas for protection in the deep Mediterranean Sea."; "application/ld+json"; , ; "https://w3id.org/ro-id/4fd0f1c2-d58f-4b20-9f12-503c31c607d9"; ; "Identifying Priorities for the Protection of Deep Mediterranean Sea Ecosystems Through an Integrated Approach - snapshot", "Identifying Priorities for the Protection of Deep Mediterranean Sea Ecosystems Through an Integrated Approach"; "MANUAL"; "https://w3id.org/ro-id/4fd0f1c2-d58f-4b20-9f12-503c31c607d9/9233b6cc-5495-423f-9af0-b60a83db22c0"; "Castellan, Giorgio. \"Identifying Priorities for the Protection of Deep Mediterranean Sea Ecosystems Through an Integrated Approach.\" ROHub. 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This research object, was created in order to further analyse and interpret the results from the research object http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/  (HD chromatin analysis). The workflows in this research object are using the anni web services, implemented by the Biosemantics group.

"; "application/ld+json"; , , , ; "https://w3id.org/ro-id/d1b1d427-2332-428e-a205-726ac7a0e951"; ; "HD data interpretation", "chromatin data interpretation"; "Eleni Mina. \"chromatin data interpretation.\" ROHub. Feb 21 ,2014. https://w3id.org/ro-id/d1b1d427-2332-428e-a205-726ac7a0e951." . a , ; , , , , ; "data_interpretation" . a , , ; ; "30787"^^xsd:integer; "https://api.rohub.org/api/resources/0390ff51-55a1-4af3-b99c-60ef059d0afc/download/"; ; "2014-02-25 16:10:46.463000+00:00"; "2022-03-25 09:07:52.840714+00:00"; "This workflow lists all IDs and descriptions of the predefined concept set"; ; "List Predefined Concept Sets"; "2014-02-25 16:10:46.463000+00:00" . a , , ; ; "188023"^^xsd:integer; "https://api.rohub.org/api/resources/45b81758-2d25-4c33-87c8-cb2968fbd849/download/"; ; "2014-02-25 16:12:14.228000+00:00"; "2022-03-25 09:07:51.492625+00:00"; "This workflow can prioritize genes that are related to a specific concept, e.g. HTT. In order to obtain the concept id of the term that is going to be matched against the gene list, the workflow Get concept suggestions from term, needs to run first. matchConceptProfileList: the gene list we want to match (order) against a particular concept queryConceptProfileList: the concept (or gene list) we want to match the query against"; ; "Prioritize gene list related to a concept /list of concepts"; "2014-02-25 16:12:14.228000+00:00" . a , , ; ; "63"^^xsd:integer; "https://api.rohub.org/api/resources/7a3f5ba3-b292-4c80-b0a1-76a15b20e50c/download/"; ; "2014-02-25 16:03:44.993000+00:00"; "2022-03-25 09:07:53.677489+00:00"; "text/plain"; ; "hypothesis.txt"; "2014-02-25 16:03:44.993000+00:00" . a , , ; ; "203555"^^xsd:integer; "https://api.rohub.org/api/resources/7aa50a5a-bc9a-4639-9e04-1fecc9bb5002/download/"; ; "2014-02-25 16:06:54.756000+00:00"; "2022-03-25 09:07:55.632943+00:00"; "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. \"5\" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services"; ; "Annotate a gene list with Biological processes"; "2014-02-25 16:06:54.756000+00:00" . a , , ; ; "69369"^^xsd:integer; "https://api.rohub.org/api/resources/99ba79b8-8172-4026-93b2-affd7320122f/download/"; ; "2014-02-26 13:14:06.663000+00:00"; "2022-03-25 09:07:56.525975+00:00"; """This workflow takes two concept ids as input and returns the top ranking \"B\" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the percentage of the contributions of the individual concepts to the coherence score (the average of the inner product scores of all possible concept pairs within the group). This workflow can be used together with other workflows in this pack: http://www.myexperiment.org/packs/282 for functional gene and SNP annotation and knowledge discovery."""; ; "Explain concept scores"; "2014-02-26 13:14:06.663000+00:00" . a , , ; ; "67"^^xsd:integer; "https://api.rohub.org/api/resources/da150b5d-9fd0-46fc-9745-06460dbed48e/download/"; ; "2014-02-25 16:03:12.283000+00:00"; "2022-03-25 09:07:49.577479+00:00"; "text/plain"; ; "conclusions.txt"; "2014-02-25 16:03:12.283000+00:00" . a , , ; ; "41692"^^xsd:integer; "https://api.rohub.org/api/resources/dcaecdee-b61a-4d22-9610-be3770345a8e/download/"; ; "2014-02-25 16:09:23.429000+00:00"; "2022-03-25 09:07:54.760474+00:00"; "This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example \"human\", \"htt\", \"Transcription\" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows"; ; "Get concept suggestions from term"; "2014-02-25 16:09:23.429000+00:00" . a , , ; ; "39476"^^xsd:integer; "https://api.rohub.org/api/resources/f34bc6b5-f6ab-41e7-b2fe-bd83df7041b6/download/"; ; "2014-02-25 16:04:13.823000+00:00"; "2022-03-25 09:07:50.657598+00:00"; "Sketch of the workflows and their explanation, for data interpretation, plus the connection to the output from the RO for chromatin analysis"; "image/png"; ; "workflow sketch data interpretation"; "2014-02-25 16:04:13.823000+00:00" . a ; dct:conformsTo ; . a ; "Eleni Mina" . a ; "Eleni Mina" . a ; "service-account-generation-service" . } sub:provenance { sub:assertion prov:wasDerivedFrom . } sub:pubinfo { this: a npx:RoCrateNanopub; dct:created "2026-03-03T15:46:22.919+01:00"^^xsd:dateTime; dct:creator ; npx:introduces ; rdfs:label "HD data interpretation" . sub:sig npx:hasAlgorithm "RSA"; npx:hasPublicKey "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAxszSDYX5tuCSkP7UiCtftYPFNQVTjgNu0I5fwdML2DLRDlp0xzmsQXRk8oHuvwGvG1aMjj6cpUqO+0rz2Sg/wvHOgUpkRH8VJXvmlkhafMLCMtUtk5JIx7e+fkzCby+fnmD7kMkGLrT+OaExWwEDmNlCAt0TPKcHSdwsjso2isXjtAsGevyCMke8ufnFYpjs746JES1eNzVnHnn2Kp/lqcm60GM+J8dLgRZp7fX0anW098xhKym6+xXFzqeju0vYRIHBPerv+r7skWxwk+a7Sd8msqVeYEv6NTqnyWvyWb6Yh8cvj04N6qm/T6C5FUPLQhzSaQgMVMU6yLqjPuu9DwIDAQAB"; npx:hasSignature "ZOzTf5JiOzL48jJxElmMEjSgBUDVfzX2P5hU1ksYQaD/V4N4zUkojB1r9U7xStluMIkMDgkjuZwn2VRG5n2jKqJqMMEtHOsgcio1bzmgr5piK7jZyT7vQ2utJgeaCSKvtbFN3TTg5lEG99Chb0yDiOHPxCX8Qba7JZI+TS9xOkwXUR+4WUO105kiaucyuaJe5MpwWG+U1sSkvSDOKIRSfU1v6cVzrD3hbttWRCM419K5Mp7fz3rKVC4J96MYUda3ZqvXnylSf5nKeggZ6nfGl14q/2pVpUZyZuthp/mtT54pWtmyX89TqzlhThyIiaUMTZ2bSqKWTu+R/9Ebz+rfgQ=="; npx:hasSignatureTarget this:; npx:signedBy . } @prefix this: . @prefix sub: . @prefix np: . @prefix dct: . @prefix pav: . @prefix rdf: . @prefix owl: . @prefix rdfg: . @prefix dce: . @prefix xsd: . @prefix rdfs: . @prefix prov: . @prefix npx: . sub:Head { this: a np:Nanopublication; np:hasAssertion sub:assertion; np:hasProvenance sub:provenance; np:hasPublicationInfo sub:pubinfo . } sub:assertion { a . a ; "D3.1: Workflow Evolution, Sharing and Collaboration Initial Requirements" . a ; "Taverna 2.4" . a ; "HYPERLEDA. I. Identification and designation of galaxies" . a ; "D4.1: Workflow Integrity and Authenticity Maintenance Initial Requirements" . a ; "D2.1 Workflow Lifecycle Management Initial Requirements" . a ; "Virtual Observatory activities in the AMIGA group" . a ; "D1.2: Wf4Ever Sandbox v1" . a ; "Python" . a ; "Topcat" . a ; "Capabilities of the HYPERLEDA database" . a . a ; "from. to. forSb galaxy" . a ; "logr25" . a ; "tool session" . a ; "Oxford University" . a ; "Lawrence" . a ; "property error value" . a ; "Amiga data revision" . a ; "mathematics" . a ; "United Kingdom" . a ; "astronomy" . a ; "Verley" . a ; "AMIGAsample" . a ; "Poznan" . a ; "Poland" . a ; "Oxford" . a ; "appendix B research object structure" . a ; "Madrid" . a ; "NamesLEDA.txt" . a ; "Leiden" . a ; "Hereafter" . a ; "Edinburgh" . a ; "axis ratio" . a ; "dust extinction coefficient" . a ; "deployment of a Research Object" . a ; "cig SDSS sample" . a ; "Colorado" . a ; "physics" . a ; "lumi nous galaxy" . a ; "Karachentseva" . a ; "HyperLEDA database" . a ; "Netherlands" . a ; "Calzetti" . a ; "statistics" . a ; "galaxy" . a ; "database" . a ; "research" . a ; "data" . a ; "sample" . a ; "red shift" . a ; "text file" . a ; "AMIGA" . a ; "FP ICT" . a ; "workflow" . a ; "value" . a ; "correction" . a ; "opticalAGN" . a ; "ratio" . a ; "information and communication technologies" . a ; "value" . a ; "optical luminosity in B-band" . a ; "luminosity" . a ; "e mail address" . a ; "CIG" . a ; "output" . a ; "Enrique Ruiz Minor" . a ; "Red Cross" . a ; "interactions galaxy" . a ; "University of Manchester" . a ; "Naciones" . a ; "evolution galaxy" . a ; "property" . a ; "mag" . a ; "research object management" . a ; "university" . a ; "inAMIGA" . a ; "Granada" . a ; "Alaska" . a ; "Manchester" . a ; "property value" . a ; "group database" . a ; "Vulkan Shmidta" . a ; "León" . a ; "colors" . a ; "SDSS" . a ; "workflow building" . a ; "sample" . a ; "type" . a ; "coordinate" . a ; "propagation" . a ; "Montenegro" . a ; "appendices" . a ; "database" . a ; "property" . a ; "value error" . a ; "calculation" . a ; "galaxy inclination" . a ; "galaxies", "galaxy" . a ; "galaxy" . a ; "sample" . a ; "sc galaxy" . a ; "type galaxies inAMIGA" . a ; "Boadilla del Monte" . a ; "propagation of property" . a ; "assigned galaxy type" . a ; "British Telecom" . a ; "evolution galaxy" . a ; "error of the coordinate" . a ; "AKwas" . a ; "Ai AK" . a ; "AGN" . a ; "IAA" . a ; "Pozna" . a ; "Mpc" . a ; "Sect." . a ; "Spain" . a ; "Golden Exemplar" . a ; "service-account-enrichment" . a , , ; pav:importedBy ; "http://sandbox.rohub.org/rodl/ROs/Pack585/"; "2014-01-27T17:31:15.131+01:00"; "https://www.google.com/accounts/o8/id?id=AItOawnZHKwZJglv16YBiUjsWEnx39mHA0RB250"; "http://w3id.org/ro-id/rohub/model#change_specifications/d3cea99d-3ccd-489d-88d2-97c0392888ff"; ; "2908927"^^xsd:integer; "https://api.rohub.org/api/ros/9faa4bd7-7c10-4a60-a418-b9dc338d966d/crate/download/"; ; "2014-01-24 15:04:31.757000+00:00"; "2025-03-05 01:16:58.682001+00:00"; "2014-01-24 15:04:31.757000+00:00"; """The scientific experiment represented by this research object pertains to the multi-wavelength study for a sample of the most isolated galaxies in the local universe. This study characterizes each galaxy of this sample through both the measurement of basic astrophysical properties:  - The equatorial coordinates in J2000 epoch - The velocities in km/s (v) - The dust extinction coefficient (ag) - The axis ratio of the isophote 25 mag/arcsec2 (logr25) - The apparent total B magnitude (BT) - The morphological type (t) and the calculation of the more complex properties: - The distance in Mega parsecs (D) - The corrected apparent B magnitude (btc) - The optical luminosity in B-band (LB) Specifically, this research object is focused on the calculation of the intrinsic luminosity in the Johnson B-band, in order to achieve it the measurement or calculation of all those astrophysical properties is needed. All the data involved in the characterization of the sample are stored in a local relational MySQL database. To maintain up to date this database and to register all the updates properly is part of this scientific experiment."""; "application/ld+json"; ; "https://w3id.org/ro-id/9faa4bd7-7c10-4a60-a418-b9dc338d966d"; ; "Propagation of properties extracted from the HyperLEDA catalog in the calculation of luminosities of galaxies"; rdfs:comment "Design Sketch and Experiment hypothesis will improve readability. Consider adding these elements.", "Please, take into account Hubble constant value in the determination of distances", "The Hubble constant value has been considered in the script calculateDistance.py"; prov:wasRevisionOf "http://sandbox.rohub.org/rodl/ROs/Pack585-snapshot/"; "Jose Enrique Ruiz. \"Propagation of properties extracted from the HyperLEDA catalog in the calculation of luminosities of galaxies.\" ROHub. 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Aug 30 ,2013. https://w3id.org/ro-id/3a129ea9-7d50-4d4a-bcce-499729c5f3e0." . a , ; , , , , ; "data_interpretation" . a , ; ; "41573"^^xsd:integer; "https://api.rohub.org/api/resources/4264530f-42e9-45f0-9255-d232a3a558ac/download/"; ; "2013-11-05 13:09:46.561000+00:00"; "2022-03-25 09:24:37.622734+00:00"; "Purpose of workflow: This workflow takes two concept ids as input and returns the top ranking \"B\" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the percentage of the contributions of the individual concepts to the coherence score (the average of the inner product scores of all possible concept pairs within the group)."; ; "Explain Scores"; "2013-11-05 13:09:46.561000+00:00" . a , , ; ; "67"^^xsd:integer; "https://api.rohub.org/api/resources/4e604e6a-6c92-414d-a49e-4e67a8b39116/download/"; ; "2013-08-31 15:11:30.970000+00:00"; "2022-03-25 09:24:40.710743+00:00"; "text/plain"; ; "conclusion"; "2013-08-31 15:11:30.970000+00:00" . a , , ; ; "188023"^^xsd:integer; "https://api.rohub.org/api/resources/55c4a47f-eb4d-4461-aaf3-f718a38bc803/download/"; ; "2013-11-05 13:07:43.493000+00:00"; "2022-03-25 09:24:47.224634+00:00"; "This workflow can prioritize genes that are related to a specific concept, e.g. HTT. In order to obtain the concept id of the term that is going to be matched against the gene list, the workflow Get concept suggestions from term, needs to run first. matchConceptProfileList: the gene list we want to match (order) against a particular concept queryConceptProfileList: the concept (or gene list) we want to match the query against"; ; "Prioritize gene list related to a concept /list of concepts"; "2013-11-05 13:07:43.493000+00:00" . a , , ; ; "214639"^^xsd:integer; "https://api.rohub.org/api/resources/5872d7d2-57d6-4b92-854a-815c2dc665b4/download/"; ; "2014-02-11 15:25:01.110000+00:00"; "2022-03-25 09:24:49.007856+00:00"; "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. \"5\" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services"; ; "Annotate a gene list with Biological processes"; "2014-02-11 15:25:01.110000+00:00" . a , , ; ; "39476"^^xsd:integer; "https://api.rohub.org/api/resources/7a77bf73-c2d0-41ca-8a13-b91c31de14d8/download/"; ; "2013-08-31 15:37:06.058000+00:00"; "2022-03-25 09:24:39.842471+00:00"; "Sketch of the workflows and their explanation, for data interpretation, plus the connection to the output from the RO for chromatin analysis"; "image/png"; ; "workflow sketch data interpretation"; "2013-08-31 15:37:06.058000+00:00" . a , , ; ; "63"^^xsd:integer; "https://api.rohub.org/api/resources/97a1ffa9-8d56-4499-827b-8d4e2d313fbc/download/"; ; "2013-08-31 15:04:48.724000+00:00"; "2022-03-25 09:24:28.805556+00:00"; "text/plain"; ; "hypothesis.txt"; "2013-08-31 15:04:48.724000+00:00" . a , , ; ; "30787"^^xsd:integer; "https://api.rohub.org/api/resources/ab98dfb6-be33-4c6d-bb69-1ecccdac03b8/download/"; ; "2013-11-05 13:09:01.493000+00:00"; "2022-03-25 09:24:44.673277+00:00"; "This workflow lists all IDs and descriptions of the predefined concept set"; ; "ListPredefinedConceptSets"; "2013-11-05 13:09:01.493000+00:00" . a , , ; ; "41692"^^xsd:integer; "https://api.rohub.org/api/resources/f0c4d8f6-4ef6-43bd-806f-f6ee04fe6cbf/download/"; ; "2013-08-31 15:02:18.108000+00:00"; "2022-03-25 09:24:48.176013+00:00"; "This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example \"human\", \"htt\", \"Transcription\" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows"; ; "Get concept suggestions from term"; "2013-08-31 15:02:18.108000+00:00" . a ; dct:conformsTo ; . a ; "gene"; "3.399327605528577"; "9.1" . a ; "earth sciences"; "47.691405491207696"; "0.9814894795417786" . a ; "role"; "5.363204344874406"; "15.8" . a ; "missing link"; "4.514596062457569"; "13.3" . a ; "analyzation"; "1.4596062457569585"; "4.3" . a ; "life sciences"; "35.76177208527657"; "0.9203993678092957" . a ; "HD"; "4.632050803137841"; "12.4" . a ; "analysis of Ro"; "3.843514070006863"; "11.2" . a ; "Animal"; "Human interest/Animal" . a ; "system"; "3.6320434487440596"; "10.7" . a ; "deregulation"; "9.911744738628649"; "29.2" . a ; "Interpretation of the results from the analysis of RO: http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/. 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Aug 30 ,2013. https://w3id.org/ro-id/cc288df3-b3fd-4622-b22d-0a5995a60182." . a , ; , , , ; "data_interpretation" . a , , ; ; "41692"^^xsd:integer; "https://api.rohub.org/api/resources/22f6a795-b434-4dab-9fd1-db2f70510a4f/download/"; ; "2013-08-31 15:02:18.108000+00:00"; "2022-03-25 09:25:32.687725+00:00"; "This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example \"human\", \"htt\", \"Transcription\" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows"; ; "Get concept suggestions from term"; "2013-08-31 15:02:18.108000+00:00" . a , , ; ; "188023"^^xsd:integer; "https://api.rohub.org/api/resources/2d792031-89e3-48c9-8a8b-5d860fb1eddc/download/"; ; "2013-11-05 13:07:43.493000+00:00"; "2022-03-25 09:25:31.366149+00:00"; "This workflow can prioritize genes that are related to a specific concept, e.g. HTT. In order to obtain the concept id of the term that is going to be matched against the gene list, the workflow Get concept suggestions from term, needs to run first. matchConceptProfileList: the gene list we want to match (order) against a particular concept queryConceptProfileList: the concept (or gene list) we want to match the query against"; ; "Prioritize gene list related to a concept /list of concepts"; "2013-11-05 13:07:43.493000+00:00" . a , , ; ; "67"^^xsd:integer; "https://api.rohub.org/api/resources/4e9c8958-d814-4ddb-bc22-1ec5455e2283/download/"; ; "2013-08-31 15:11:30.970000+00:00"; "2022-03-25 09:25:19.712506+00:00"; "text/plain"; ; "conclusions.txt"; "2013-08-31 15:11:30.970000+00:00" . a , , ; ; "39476"^^xsd:integer; "https://api.rohub.org/api/resources/b525b766-e586-4ffa-85f9-1c035a9d4910/download/"; ; "2013-08-31 15:37:06.058000+00:00"; "2022-03-25 09:25:24.978095+00:00"; "Sketch of the workflows and their explanation, for data interpretation, plus the connection to the output from the RO for chromatin analysis"; "image/png"; ; "workflow sketch data interpretation"; "2013-08-31 15:37:06.058000+00:00" . a , , ; ; "30787"^^xsd:integer; "https://api.rohub.org/api/resources/c3eabd9c-7b2b-44a9-a3bc-2a088ff7769a/download/"; ; "2013-11-05 13:09:01.493000+00:00"; "2022-03-25 09:25:29.623682+00:00"; "This workflow lists all IDs and descriptions of the predefined concept set"; ; "ListPredefinedConceptSets"; "2013-11-05 13:09:01.493000+00:00" . a , , ; ; "63"^^xsd:integer; "https://api.rohub.org/api/resources/c81c3e0f-1ec6-49f2-9420-8b65fa31ba7c/download/"; ; "2013-08-31 15:04:48.724000+00:00"; "2022-03-25 09:25:17.742156+00:00"; "text/plain"; ; "hypothesis.txt"; "2013-08-31 15:04:48.724000+00:00" . a , , ; ; "203555"^^xsd:integer; "https://api.rohub.org/api/resources/ff9e943b-ebf1-4ef2-be95-77a3aaf55b51/download/"; ; "2013-11-05 13:07:17.887000+00:00"; "2022-03-25 09:25:30.549318+00:00"; "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. \"5\" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services"; ; "Annotate a gene list with Biological processes"; "2013-11-05 13:07:17.887000+00:00" . a ; dct:conformsTo ; . a ; "role"; "5.491221516623086"; "14.7" . a ; "deregulation"; "11.31864026895779"; "30.3" . a ; "earth sciences"; "27.692441186701984"; "0.5699106454849243" . a ; "epigenetic role"; "6.554564172958133"; "19.1" . a ; "missing link"; "5.304445274561076"; "14.2" . a ; "life sciences (general)"; "28.363564182847412"; "0.7299919724464417" . a ; "HD"; "3.8696537678207736"; "11.4" . a ; "HD chromatin analysis"; "14.13864104323953"; "41.2" . a ; "linguistics"; "100.0"; "7.7" . a ; "gene"; "13.06856754921928"; "38.5" . a ; "Ro"; "5.790063503922301"; "15.5" . a ; "HD gene deregulation"; "25.806451612903224"; "75.2" . a ; "gene deregulation"; "1.8188057652711047"; "5.3" . a ; "Genes deregulated in HD, are participating in epigenetic processes"; "33.333333333333336"; "100.0" . a ; "Economic policy"; "Economy, business and finance/Economy/Economic policy" . a ; 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Aug 30 ,2013. https://w3id.org/ro-id/d81accb2-84af-4fd1-8b84-1dfb453d6970." . a , ; , , , , ; "data_interpretation" . a , , ; ; "67"^^xsd:integer; "https://api.rohub.org/api/resources/25bb3ac0-5250-4981-85af-ef7926658fdf/download/"; ; "2013-08-31 15:11:30.970000+00:00"; "2022-03-25 09:26:12.975347+00:00"; "text/plain"; ; "conclusion"; "2013-08-31 15:11:30.970000+00:00" . a , ; ; "41573"^^xsd:integer; "https://api.rohub.org/api/resources/2b72df47-8faa-48bf-b415-b63cd1df2d50/download/"; ; "2013-11-05 13:09:46.561000+00:00"; "2022-03-25 09:26:09.896623+00:00"; "Purpose of workflow: This workflow takes two concept ids as input and returns the top ranking \"B\" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the percentage of the contributions of the individual concepts to the coherence score (the average of the inner product scores of all possible concept pairs within the group)."; ; "Explain Scores"; "2013-11-05 13:09:46.561000+00:00" . a , , ; ; "30787"^^xsd:integer; "https://api.rohub.org/api/resources/39bae470-b4df-4340-8967-bf677ad04918/download/"; ; "2013-11-05 13:09:01.493000+00:00"; "2022-03-25 09:26:16.702256+00:00"; "This workflow lists all IDs and descriptions of the predefined concept set"; ; "ListPredefinedConceptSets"; "2013-11-05 13:09:01.493000+00:00" . a , , ; ; "63"^^xsd:integer; "https://api.rohub.org/api/resources/51b8c865-2634-4639-aafc-6d1d14471851/download/"; ; "2013-08-31 15:04:48.724000+00:00"; "2022-03-25 09:26:01.458551+00:00"; "text/plain"; ; "hypothesis.txt"; "2013-08-31 15:04:48.724000+00:00" . a , , ; ; "39476"^^xsd:integer; "https://api.rohub.org/api/resources/525b7316-4b51-4c76-99f8-29c99846ee53/download/"; ; "2013-08-31 15:37:06.058000+00:00"; "2022-03-25 09:26:11.723471+00:00"; "Sketch of the workflows and their explanation, for data interpretation, plus the connection to the output from the RO for chromatin analysis"; "image/png"; ; "workflow sketch data interpretation"; "2013-08-31 15:37:06.058000+00:00" . a , , ; ; "188023"^^xsd:integer; "https://api.rohub.org/api/resources/dc093497-63fb-4022-b9b6-a9ec966bb384/download/"; ; "2013-11-05 13:07:43.493000+00:00"; "2022-03-25 09:26:18.928586+00:00"; "This workflow can prioritize genes that are related to a specific concept, e.g. HTT. In order to obtain the concept id of the term that is going to be matched against the gene list, the workflow Get concept suggestions from term, needs to run first. matchConceptProfileList: the gene list we want to match (order) against a particular concept queryConceptProfileList: the concept (or gene list) we want to match the query against"; ; "Prioritize gene list related to a concept /list of concepts"; "2013-11-05 13:07:43.493000+00:00" . a , , ; ; "214639"^^xsd:integer; "https://api.rohub.org/api/resources/ef2ee587-0615-4ab0-8b31-c355babf448d/download/"; ; "2014-02-11 15:25:01.110000+00:00"; "2022-03-25 09:26:20.800487+00:00"; "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. \"5\" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services"; ; "Annotate a gene list with Biological processes"; "2014-02-11 15:25:01.110000+00:00" . a , , ; ; "41692"^^xsd:integer; "https://api.rohub.org/api/resources/fccab2ac-33f2-48c6-86c6-b4789dcb5585/download/"; ; "2013-08-31 15:02:18.108000+00:00"; "2022-03-25 09:26:19.956163+00:00"; "This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example \"human\", \"htt\", \"Transcription\" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows"; ; "Get concept suggestions from term"; "2013-08-31 15:02:18.108000+00:00" . a ; dct:conformsTo ; . a ; "gene deregulation"; "1.8188057652711047"; "5.3" . a ; "life sciences"; "28.363564182847412"; "0.7299919724464417" . a ; "deregulation"; "3.598099117447386"; "10.6" . a ; "chromatin analysis"; "0.857927247769389"; "2.5" . a ; "geology"; "47.691405491207696"; "0.9814894795417786" . a ; "Language"; "Arts, culture and entertainment/Culture/Language" . a ; "gene"; "3.399327605528577"; "9.1" . a ; "analysis"; "3.0257751214045574"; "8.1" . a ; "deregulation"; "9.911744738628649"; "29.2" . a ; "deregulation"; "4.333208815838626"; "11.6" . a ; "HD chromatin analysis"; "14.13864104323953"; "41.2" . a ; "http"; "2.0706042090970804"; "6.1" . a ; "gene"; "13.06856754921928"; "38.5" . a ; "Interpretation of the results from the analysis of RO: http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/. This RO is an extension of the HD chromatin analysis to interpret the results and reveal missing links that can according to literature explain HD gene deregulation"; "33.333333333333336"; "100.0" . a ; "Animal"; "Human interest/Animal" . a ; "Eleni Mina" . a ; "service-account-generation-service" . } sub:provenance { sub:assertion prov:wasDerivedFrom . } sub:pubinfo { this: a npx:RoCrateNanopub; dct:created "2026-03-03T15:46:12.282+01:00"^^xsd:dateTime; dct:creator ; npx:introduces ; rdfs:label "Interpretation of the results from the analysis of RO: http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/" . sub:sig npx:hasAlgorithm "RSA"; npx:hasPublicKey "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAxszSDYX5tuCSkP7UiCtftYPFNQVTjgNu0I5fwdML2DLRDlp0xzmsQXRk8oHuvwGvG1aMjj6cpUqO+0rz2Sg/wvHOgUpkRH8VJXvmlkhafMLCMtUtk5JIx7e+fkzCby+fnmD7kMkGLrT+OaExWwEDmNlCAt0TPKcHSdwsjso2isXjtAsGevyCMke8ufnFYpjs746JES1eNzVnHnn2Kp/lqcm60GM+J8dLgRZp7fX0anW098xhKym6+xXFzqeju0vYRIHBPerv+r7skWxwk+a7Sd8msqVeYEv6NTqnyWvyWb6Yh8cvj04N6qm/T6C5FUPLQhzSaQgMVMU6yLqjPuu9DwIDAQAB"; npx:hasSignature "cJCZSdoHuzBoEL7A80ueN6p17yi6oy5wmbfeGQwU0rrH0KHuaOyQtvRvKi4Ms5vYt5MKtCSoRUzHo+UTFPWPqLrjGa4Jlgrd6A0HVs9EAJvIIdIpNC7aky1etyTGpcW2squdZLoSRkJvuHHoJXgOybl6uczqoojhERs8x2cKtX4aRX+Nk4zKq4vwTPJfJRHlLSTfQxY0mhURg/vKeXnPOiXaAQ5678y7tCvlvdTAEUM5gobIGZTZW31Trta57CxdvElCIX4favBtXdT6sMKjm9yI7Q77klq2fepkBtKGADJQ0i8dK6YbDOyFX81o/JCJxKwyf8Ns1eWsQnXQeyPaHA=="; npx:hasSignatureTarget this:; npx:signedBy . } @prefix this: . @prefix sub: . @prefix np: . @prefix dct: . @prefix pav: . @prefix rdf: . @prefix owl: . @prefix rdfg: . @prefix dce: . @prefix xsd: . @prefix rdfs: . @prefix prov: . @prefix npx: . sub:Head { this: a np:Nanopublication; np:hasAssertion sub:assertion; np:hasProvenance sub:provenance; np:hasPublicationInfo sub:pubinfo . } sub:assertion { a . a ; "involve in HD gene deregulation" . a ; "HD" . a ; "participate in epigenetic processes" . a ; "genetics" . a ; "genes" . a ; "have an epigenetic role" . a , ; "Purpose of workflow: This workflow takes two concept ids as input and returns the top ranking \"B\" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the percentage of the contributions of the individual concepts to the coherence score (the average of the inner product scores of all possible concept pairs within the group)."; "Explain Scores" . a ; "testing"; "2.545824847250509"; "7.5" . a ; "HD"; "8.06873365707882"; "21.6" . a ; "life sciences (general)"; "35.87466373187602"; "0.9233048558235168" . a ; "hard drive"; "4.107264086897488"; "12.1" . a ; "http"; "2.0706042090970804"; "6.1" . a ; "analysis of Ro"; "3.843514070006863"; "11.2" . a ; "Ro"; "5.790063503922301"; "15.5" . a ; "Interpretation of the results from the analysis of RO: http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/. 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"deregulate in HD"; "16.197666437886067"; "47.2" . a ; "life sciences (general)"; "28.363564182847412"; "0.7299919724464417" . a ; "gene"; "14.60590212924916"; "39.1" . a ; "deregulation"; "11.31864026895779"; "30.3" . a ; "life sciences (general)"; "35.76177208527657"; "0.9203993678092957" . a ; "epigenetic"; "1.5274949083503053"; "4.5" . a ; "geology"; "24.616153322090323"; "0.5066006183624268" . a ; "epigenetic process"; "17.84488675360329"; "52.0" . a ; "service-account-enrichment" . a , , ; pav:importedBy ; "http://sandbox.rohub.org/rodl/ROs/data_interpretation/"; "2014-02-11T16:00:29.893+01:00"; "https://www.google.com/accounts/o8/id?id=AItOawnOAeiyuU0cZ91YBD1EW7d43AlWw8xdALU"; ; "81525"^^xsd:integer; "https://api.rohub.org/api/ros/95a9036b-bee9-48fb-81eb-7e9a90014293/crate/download/"; ; "2013-08-30 16:15:52.229000+00:00"; "2025-03-05 00:55:19.037479+00:00"; "2013-08-30 16:15:52.229000+00:00"; "This RO is an extension of the HD chromatin analysis to interpret the results and reveal missing links that can according to literature explain HD gene deregulation"; 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"https://w3id.org/ro-id/0ef41513-eaa9-4e76-994a-e90587f4069e", "https://w3id.org/ro-id/80f188fc-a15a-40e1-9843-303b0be67656", "https://w3id.org/ro-id/8978ed0f-74e3-4ca4-bea3-c366b5ac4a27", "https://w3id.org/ro-id/b8bcb4cf-ba2b-438b-a8e3-d9e460152a09", "https://w3id.org/ro-id/cb11d942-fce9-459d-bfe2-4a4ed9d1fe1d", "https://w3id.org/ro-id/e24af000-2fbd-4820-bf60-bd01890f4b89"; "https://w3id.org/ro-id/15ba1d7a-c420-4e56-870a-99df018d8907", "https://w3id.org/ro-id/2b8c0d56-d5b4-4689-a663-1752b449dc0a", "https://w3id.org/ro-id/78cd33c6-3425-4ecf-a833-00cf96855d21", "https://w3id.org/ro-id/7f465c71-cf0c-4f7d-8406-3eaef5ad7c0b", "https://w3id.org/ro-id/93f1ab58-022a-4598-97f7-7807f93f2aa1", "https://w3id.org/ro-id/9d438ec7-40ed-4892-a79f-86270050c4f8", "https://w3id.org/ro-id/a852c4bf-efeb-436b-951e-b4dc59e1e4b7", "https://w3id.org/ro-id/aa30e810-a7cf-4844-9c02-c5f2cb97b671", "https://w3id.org/ro-id/af8a543b-f09a-4484-9a01-66fdcadbd631", "https://w3id.org/ro-id/d6a3e45a-7fea-4bce-89ce-e0c2574d972f", "https://w3id.org/ro-id/e907a28b-718c-45b7-9531-0e556e167c0c", "https://w3id.org/ro-id/f8fb6331-272a-4818-ad9a-1fa334ce7606"; "https://w3id.org/ro-id/1b53e2a7-75e0-4b9a-97e0-c61af6f89d96", "https://w3id.org/ro-id/1da386ca-5f4b-4458-9db0-2dfb98944d22", "https://w3id.org/ro-id/fa01854e-8511-436f-9f73-5e8db98dec87"; "Eleni Mina. \"Interpretation of the results from the analysis of RO: http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/.\" ROHub. Aug 30 ,2013. https://w3id.org/ro-id/95a9036b-bee9-48fb-81eb-7e9a90014293." . a , ; , , , ; "data_interpretation" . a , , ; ; "67"^^xsd:integer; "https://api.rohub.org/api/resources/207ea21e-4180-4f98-a6e9-9906672c0f49/download/"; ; "2013-08-31 15:11:30.970000+00:00"; "2022-03-25 09:26:52.370638+00:00"; "text/plain"; ; "conclusions.txt"; "2013-08-31 15:11:30.970000+00:00" . a , , ; ; "30787"^^xsd:integer; "https://api.rohub.org/api/resources/2328b548-0032-4dfb-97dd-2892668282c5/download/"; ; "2013-11-05 13:09:01.493000+00:00"; "2022-03-25 09:27:02.866468+00:00"; "This workflow lists all IDs and descriptions of the predefined concept set"; ; "ListPredefinedConceptSets"; "2013-11-05 13:09:01.493000+00:00" . a , , ; ; "41692"^^xsd:integer; "https://api.rohub.org/api/resources/574c5f85-a2ea-484f-92e6-f11fe184661d/download/"; ; "2013-08-31 15:02:18.108000+00:00"; "2022-03-25 09:27:05.517990+00:00"; "This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example \"human\", \"htt\", \"Transcription\" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows"; ; "Get concept suggestions from term"; "2013-08-31 15:02:18.108000+00:00" . a , , ; ; "203555"^^xsd:integer; "https://api.rohub.org/api/resources/71f79523-cf5b-48fb-b7b9-92ec04636326/download/"; ; "2013-11-05 13:07:17.887000+00:00"; "2022-03-25 09:27:03.799736+00:00"; "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. \"5\" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services"; ; "Annotate a gene list with Biological processes"; "2013-11-05 13:07:17.887000+00:00" . a , , ; ; "39476"^^xsd:integer; "https://api.rohub.org/api/resources/a220e0d8-7cdd-40ba-a8a5-6b264086dde3/download/"; ; "2013-08-31 15:37:06.058000+00:00"; "2022-03-25 09:26:58.184590+00:00"; "Sketch of the workflows and their explanation, for data interpretation, plus the connection to the output from the RO for chromatin analysis"; "image/png"; ; "workflow sketch data interpretation"; "2013-08-31 15:37:06.058000+00:00" . a , , ; ; "188023"^^xsd:integer; "https://api.rohub.org/api/resources/a8461986-76a4-49b2-8153-4c899df13854/download/"; ; "2013-11-05 13:07:43.493000+00:00"; "2022-03-25 09:27:04.663380+00:00"; "This workflow can prioritize genes that are related to a specific concept, e.g. HTT. In order to obtain the concept id of the term that is going to be matched against the gene list, the workflow Get concept suggestions from term, needs to run first. matchConceptProfileList: the gene list we want to match (order) against a particular concept queryConceptProfileList: the concept (or gene list) we want to match the query against"; ; "Prioritize gene list related to a concept /list of concepts"; "2013-11-05 13:07:43.493000+00:00" . a , , ; ; "63"^^xsd:integer; "https://api.rohub.org/api/resources/e60c67e6-6657-4ddf-99ed-b47687ce684c/download/"; ; "2013-08-31 15:04:48.724000+00:00"; "2022-03-25 09:26:50.571966+00:00"; "text/plain"; ; "hypothesis.txt"; "2013-08-31 15:04:48.724000+00:00" . a ; dct:conformsTo ; . a ; "Language"; "Arts, culture and entertainment/Culture/Language" . a ; "Animal"; "Human interest/Animal" . a ; "analysis"; "3.0257751214045574"; "8.1" . a ; "have an epigenetic role"; "0.06863417982155112"; "0.2" . a ; "participate in epigenetic process"; "0.20590253946465337"; 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This research object, was created in order to further analyse and interpret the results from the research object http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/  (HD chromatin analysis). The workflows in this research object are using the anni web services, implemented by the Biosemantics group.

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This research object, was created in order to further analyse and interpret the results from the research object http://sandbox.rohub.org/rodl/ROs/HD_chromatin_analysis/  (HD chromatin analysis). The workflows in this research object are using the anni web services, implemented by the Biosemantics group.

"; "application/ld+json"; , , , ; "https://w3id.org/ro-id/f84d00ef-47b2-40b3-af26-099ed7e82f5b"; ; "chromatin data interpretation"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; "Eleni Mina. \"chromatin data interpretation.\" ROHub. Feb 21 ,2014. https://w3id.org/ro-id/f84d00ef-47b2-40b3-af26-099ed7e82f5b." . a , ; , , , , ; "data_interpretation" . a , , ; ; "30787"^^xsd:integer; "https://api.rohub.org/api/resources/2ea2f7b6-1c15-454f-b62a-e7656bb81db4/download/"; ; "2014-02-25 16:10:46.463000+00:00"; "2022-03-25 16:50:57.659485+00:00"; "This workflow lists all IDs and descriptions of the predefined concept set"; ; "List Predefined Concept Sets"; "2014-02-25 16:10:46.463000+00:00" . a , , ; ; "69369"^^xsd:integer; "https://api.rohub.org/api/resources/473e57ab-4056-427a-a8d9-b2c62e9b34d4/download/"; ; "2014-02-26 13:14:06.663000+00:00"; "2022-03-25 16:51:01.271983+00:00"; """This workflow takes two concept ids as input and returns the top ranking \"B\" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the percentage of the contributions of the individual concepts to the coherence score (the average of the inner product scores of all possible concept pairs within the group). This workflow can be used together with other workflows in this pack: http://www.myexperiment.org/packs/282 for functional gene and SNP annotation and knowledge discovery."""; ; "Explain concept scores"; "2014-02-26 13:14:06.663000+00:00" . a , , ; ; "63"^^xsd:integer; "https://api.rohub.org/api/resources/5b168f58-186e-4335-8079-2c917c3173e3/download/"; ; "2014-02-25 16:03:44.993000+00:00"; "2022-03-25 16:50:58.525827+00:00"; "text/plain"; ; "hypothesis.txt"; "2014-02-25 16:03:44.993000+00:00" . a , , ; ; "203555"^^xsd:integer; "https://api.rohub.org/api/resources/7f5b48a1-083d-4891-b311-b4627ceaa7ab/download/"; ; "2014-02-25 16:06:54.756000+00:00"; "2022-03-25 16:51:00.400167+00:00"; "This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. \"5\" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The workflow is using the anni web services"; ; "Annotate a gene list with Biological processes"; "2014-02-25 16:06:54.756000+00:00" . a , , ; ; "188023"^^xsd:integer; "https://api.rohub.org/api/resources/840546e9-eecd-455e-b3f7-b1893b29e083/download/"; ; "2014-02-25 16:12:14.228000+00:00"; "2022-03-25 16:50:56.779303+00:00"; "This workflow can prioritize genes that are related to a specific concept, e.g. HTT. In order to obtain the concept id of the term that is going to be matched against the gene list, the workflow Get concept suggestions from term, needs to run first. matchConceptProfileList: the gene list we want to match (order) against a particular concept queryConceptProfileList: the concept (or gene list) we want to match the query against"; ; "Prioritize gene list related to a concept /list of concepts"; "2014-02-25 16:12:14.228000+00:00" . a , , ; ; "39476"^^xsd:integer; "https://api.rohub.org/api/resources/cb796e52-689f-4e9e-8842-09612588af02/download/"; ; "2014-02-25 16:04:13.823000+00:00"; "2022-03-25 16:50:55.921582+00:00"; "Sketch of the workflows and their explanation, for data interpretation, plus the connection to the output from the RO for chromatin analysis"; "image/png"; ; "workflow sketch data interpretation"; "2014-02-25 16:04:13.823000+00:00" . a , , ; ; "41692"^^xsd:integer; "https://api.rohub.org/api/resources/ccd9b022-3e2d-422b-a5c5-1e12af73b5c7/download/"; ; "2014-02-25 16:09:23.429000+00:00"; "2022-03-25 16:50:59.349734+00:00"; "This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example \"human\", \"htt\", \"Transcription\" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows"; ; "Get concept suggestions from term"; "2014-02-25 16:09:23.429000+00:00" . a , , ; ; "67"^^xsd:integer; "https://api.rohub.org/api/resources/f97e8e56-b0de-4fda-9e37-352412aa2d3c/download/"; ; "2014-02-25 16:03:12.283000+00:00"; "2022-03-25 16:50:54.643219+00:00"; "text/plain"; ; "conclusions.txt"; "2014-02-25 16:03:12.283000+00:00" . a ; dct:conformsTo ; . a ; "Eleni Mina" . a ; "Eleni Mina" . a ; "service-account-enrichment" . a ; "service-account-generation-service" . } sub:provenance { sub:assertion prov:wasDerivedFrom . } sub:pubinfo { this: a npx:RoCrateNanopub; dct:created "2026-03-03T15:33:25.579+01:00"^^xsd:dateTime; dct:creator ; npx:introduces ; rdfs:label "chromatin data interpretation" . sub:sig npx:hasAlgorithm "RSA"; npx:hasPublicKey "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAxszSDYX5tuCSkP7UiCtftYPFNQVTjgNu0I5fwdML2DLRDlp0xzmsQXRk8oHuvwGvG1aMjj6cpUqO+0rz2Sg/wvHOgUpkRH8VJXvmlkhafMLCMtUtk5JIx7e+fkzCby+fnmD7kMkGLrT+OaExWwEDmNlCAt0TPKcHSdwsjso2isXjtAsGevyCMke8ufnFYpjs746JES1eNzVnHnn2Kp/lqcm60GM+J8dLgRZp7fX0anW098xhKym6+xXFzqeju0vYRIHBPerv+r7skWxwk+a7Sd8msqVeYEv6NTqnyWvyWb6Yh8cvj04N6qm/T6C5FUPLQhzSaQgMVMU6yLqjPuu9DwIDAQAB"; npx:hasSignature "O2KKduLCxcHUx1omyWvqvye3hLX58kqQedS6rMsKvKjREqMw7YKt7IOUVL4Iu/n8g8bZdW/JvwtweJOR++/shpD2keb1GIo4EStPA3UOu5rtrmBGb5XOOqVfS01Ach8MUASsqhO5ym6HPUBNGrTkA1d/BzfWA7+/YYXbVdC1+wApBo2QS1HQ+CCeGw55VLGV7OXGdVkNAQadWicQtIVd/kTvNWaVdh+LorCHkABtEsQKdRbtwzc7JWxRbcfCA023x+PQLKnXNgogVxaOQRe5aDXSuVfVmnY9kmoFfvKZICav/m+mhYdg2ixTFqiStlVd1+4NVV470Wf+Gbjlb+QdmQ=="; npx:hasSignatureTarget this:; npx:signedBy . } @prefix this: . @prefix sub: . @prefix np: . @prefix dct: . @prefix pav: . @prefix rdf: . @prefix owl: . @prefix rdfg: . @prefix dce: . @prefix xsd: . @prefix rdfs: . @prefix prov: . @prefix npx: . sub:Head { this: a np:Nanopublication; np:hasAssertion sub:assertion; np:hasProvenance sub:provenance; np:hasPublicationInfo sub:pubinfo . } sub:assertion { a ; ""; "Earth sciences" . a ; "environmental monitoring"; "11.420612813370472"; "8.2" . a ; "environmental monitoring from space"; "11.598746081504702"; "11.1" . a ; "service-account-enrichment" . a , , ; "False"; "https://w3id.org/ro-id/d0694eaf-a561-4c9f-9a70-17c296da2140"; "2022-03-29 07:03:12.340483+00:00"; "https://orcid.org/0000-0002-2736-0052"; ; ; "533964"^^xsd:integer; "https://api.rohub.org/api/ros/15e9432f-53ee-4ea8-b1a3-6fdcaca7cf9e/crate/download/"; ; "2021-12-14 10:41:17.716553+00:00"; "2024-03-05 12:16:56.530781+00:00"; "2021-12-14 10:41:17.716553+00:00"; "Collection and analysis of satellite data to monitor the effects of COVID-19 lockdown on water clarity in the north Adriatic Sea"; "application/ld+json"; , , , ; "https://w3id.org/ro-id/15e9432f-53ee-4ea8-b1a3-6fdcaca7cf9e"; ; "Analysis from satellite data – Environmental monitoring from space - snapshot", "Analysis from satellite data – Environmental monitoring from space"; "MANUAL"; "https://w3id.org/ro-id/81696625-5dc7-413b-a2c5-0815dee8dc2a"; "https://w3id.org/ro-id/08e10088-5d06-4d9a-a7a0-7a6bf4a0d199", "https://w3id.org/ro-id/4266cc91-2256-44f6-b790-90445838a46e", "https://w3id.org/ro-id/5549dbaf-583c-4c8c-8dfa-a39ad54b848e", "https://w3id.org/ro-id/6c915ada-20b3-43cf-a69c-8773c78a0eaa", "https://w3id.org/ro-id/6f7e5fac-e969-4048-9f37-c6b31a3c612e", "https://w3id.org/ro-id/70d4f966-c4d0-48f5-9fa5-811f884e7b1e", "https://w3id.org/ro-id/97bb139d-ef31-4724-96c5-ea9425fc7c37", "https://w3id.org/ro-id/d2a7c5cc-1102-43cd-8f62-288373b07b06", "https://w3id.org/ro-id/f3594549-487e-496f-9517-0860ce40f088"; "https://w3id.org/ro-id/74dd5244-227a-4a04-b482-735a591fd8c1", "https://w3id.org/ro-id/b72312be-71d7-47a7-b84c-4bfe2e2e23dd"; "https://w3id.org/ro-id/7b96142d-d1dc-4dd2-9f96-5dd9fb851416"; "https://w3id.org/ro-id/32c4e511-07a6-4aed-8e1e-484785703c49", "https://w3id.org/ro-id/3ee3f89c-1f32-41b6-a676-baa8abd9d56f", "https://w3id.org/ro-id/63bbaf66-12ba-4747-88a4-b84d914c3b7e", "https://w3id.org/ro-id/ac96b0ba-720f-47cb-a2fe-a19e3e7e7713", "https://w3id.org/ro-id/c922ffbe-2d7f-4489-aaa7-b1aae735efc5", "https://w3id.org/ro-id/cf67ee27-302a-48bc-a5ee-904c4e50fa3e", "https://w3id.org/ro-id/d6fe7e21-0924-4201-b407-8df494f726ed"; "https://w3id.org/ro-id/5b45c2e1-bd6d-494f-8f0b-71842e9ff0c6", "https://w3id.org/ro-id/aa125d6d-2a3d-4e86-a386-fca35f89cfff"; "https://w3id.org/ro-id/14db60f4-ba75-4054-8b25-9588535e5441", "https://w3id.org/ro-id/3a19afd2-96fe-46f3-a8ff-a00267cec7a9", "https://w3id.org/ro-id/3bea0d90-d8aa-4e43-9a10-49f192c86cf9", "https://w3id.org/ro-id/99a7f0a1-d957-45a2-b2db-21a5a4d52bee", "https://w3id.org/ro-id/ecb76892-a19f-4944-bdbc-7859c36c5de9"; "https://w3id.org/ro-id/6b907ad3-41f5-4c92-a60a-fa30c01895d6", "https://w3id.org/ro-id/d95b93a0-106a-483a-af39-2d4e03335ad7", "https://w3id.org/ro-id/f5db11a5-bf5a-4f0e-8924-4cef9408845f"; "Castellan, Giorgio. \"Analysis from satellite data – Environmental monitoring from space.\" ROHub. 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Galaxy is an open, web-based platform for accessible, reproducible, and transparent computational research. One of the strength of Galaxy is that it does not require programming experience and allow researchers to easily upload data, run complex tools and workflows in a reproducible manner, and visualize results. Galaxy Climate is quite new and aims at offering tools to everyone interested in Climate Science so that they can analyse and visualize climate data produced by climate scientists. However, climate scientists and in particular climate modellers have very different working practices: they often like to use command lines for running climate models and thanks to the PANGEO community (a community platform for Big Data geoscience) the Jupyter ecosystem has become very popular with several deployments of JupyterHubs dedicated to climate data analysis. By deploying JupyterLab with PANGEO, CESM and ESMValTool conda environments as a new Climate Galaxy interactive tool (https://live.usegalaxy.eu/?tool_id=interactive_tool_climate_notebook), we are aiming at bridging the gap between climate scientists and non-climate specialists. On this poster, we will show typical use cases both for research (https://nordicesmhub.github.io/eosc-nordic-climate-demonstrator/02-use-cases/) and for teaching (https://nordicesmhub.github.io/NEGI-Abisko-2019/intro)."""; ; "Climate JupyterLab as an interactive tool in Galaxy"; "2022-03-28 14:18:39.324751+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.6394185"; ; "2022-03-29 17:55:05.034625+00:00"; "2022-03-29 18:08:05.535928+00:00"; """This is a tarball for the Docker climate-JupyterLab image - Version 2021-03-18. To use it: download the image file docker-climate-notebook-2021-03-18.tar load it with docker with the command: docker load --input docker-climate-notebook-2021-03-18.tar launch the Docker container binding of your data folder (on the local machine) with the /import folder i(inside the container) with the command: docker run -v my_data_folder:/import -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook:2021-03-18 start your favorite web browser and go to: http://localhost:7777/ipython/ See https://github.com/NordicESMhub/docker-climate-notebook for more details"""; ; "Docker climate-JupyterLab image Version 2021-03-18"; "2022-03-29 17:55:05.034625+00:00" . a , , ; ; "https://github.com/NordicESMhub/docker-climate-notebook"; ; "2022-03-29 12:01:31.834492+00:00"; "2022-03-29 18:08:06.488065+00:00"; "This github repository contains all the sources required for building the docker containers that are made available in Quay Container Registry."; ; "Source code for building the docker container (github repository)"; "2022-03-29 12:01:31.834492+00:00" . a , , ; ; "https://jupyterlab.readthedocs.io/en/stable/"; ; "2022-03-28 14:14:45.648769+00:00"; "2022-03-29 18:08:02.576584+00:00"; "Link to the online JupyterLab documentation."; ; "JupyterLab Documentation"; "2022-03-28 14:14:45.648769+00:00" . a ; "University of Freiburg, Freiburg (Germany)"; "bjoern.gruening@gmail.com"; "Björn Grüning"; "0000-0002-3079-6586" . a , , ; ; "https://quay.io/repository/nordicesmhub/docker-climate-notebook"; ; "2022-03-29 11:58:28.213223+00:00"; "2022-03-29 18:08:06.281346+00:00"; """These docker images (different tags) correspond to the docker images built for Galaxy Climate JupyterLab. The docker images can be used within Galaxy and as standalone docker images. You can use the same images we use in Galaxy on your local computer or any other platform: 1. Pull an existing image locally docker pull quay.io/nordicesmhub/docker-climate-notebook 2. Run a pre-build image from docker registry 3. To start your JupyterLab: docker run -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook and you will top open a new terminal and start your favorite web browser. your running Jupyter Notebook instance on http://localhost:7777/ipython/. Remark: for reproducibility purpose, we suggest you use a specific tag e.g. docker pull quay.io/nordicesmhub/docker-climate-notebook:2021-03-18 Then use the same tag when starting your JupyterLab application: docker run -p 7777:8888 quay.io/nordicesmhub/docker-climate-notebook:2021-03-18"""; ; "Docker images for Galaxy Climate JupyterLab (Quay Container Registry)"; "2022-03-29 11:58:28.213223+00:00" . a , , ; ; "https://raw.githubusercontent.com/NordicESMhub/docker-climate-notebook/ie2/climate-jupyter-galaxy_web.gif"; ; "2022-03-29 11:41:30.552728+00:00"; "2022-03-29 18:08:02.662870+00:00"; "This is a gif animated image showing how to start the Galaxy Climate JupyterLab in Galaxy Europe"; "image/gif"; ; "How to start Galaxy Climate JupyterLab (gif animated)"; "2022-03-29 11:41:30.552728+00:00" . a , , ; ; "https://raw.githubusercontent.com/NordicESMhub/docker-climate-notebook/ie2/map_vis_Galaxy.gif"; ; "2022-03-29 11:43:11.075459+00:00"; "2022-03-29 18:08:03.597880+00:00"; "This is a gif animated image showing some of the functionalities of the Galaxy Climate JupyterLab"; "image/gif"; ; "Demo of some of the functionalities of the Galaxy Climate JupyterLab (gif animated)"; "2022-03-29 11:43:11.075459+00:00" . a , ; "01xtthb56"; "University of Oslo" . a , ; "04jcwf484"; "Nordic e-Infrastructure Collaboration" . a ; ; "857652"; "EOSC-Nordic"; "EOSC-Nordic" . a ; ; "30a6fc3f-4d1d-4792-92e0-33129ff5cd2d"; "POINT (10.766601562500002 59.921531172441085)" . a ; "7.8337097307667145"; "48.01044395569975"; "POINT (7.8337097307667145 48.01044395569975)" . a ; ; "84203539-105a-4412-82b0-1359fafa840a"; "POINT (7.8337097307667145 48.01044395569975)" . a ; "10.766601562500002"; "59.921531172441085"; "POINT (10.766601562500002 59.921531172441085)" . a , , , , ; "False"; ; "2022-03-29 18:08:11.857053+00:00"; ; , ; ; , ; "30283"^^xsd:integer; "https://api.rohub.org/api/ros/cb869c7a-7a89-49dd-9038-b8a05a91dc6e/crate/download/"; ; ; ; "2022-03-26 09:45:54.364171+00:00"; "2025-10-18 11:54:14.993216+00:00"; "2022-03-26 09:45:54.364171+00:00"; "🐳 🔬 📚 Jupyter running in a docker container. 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; "Example of targets detection from bathymetry (zoom)"; "2022-05-09 10:56:21.011021+00:00" . a , , ; ; "https://doi.org/10.3997/1873-0604.2012018"; ; "2022-05-09 10:57:24.554269+00:00"; "2022-08-30 14:29:49.853481+00:00"; "This paper presents a semi-automated method to recognize, spatially delineate and characterise morphometrically pockmarks at the seabed"; ; "Semi-automated characterisation of seabed pockmarks in the central North Sea"; "2022-05-09 10:57:24.554269+00:00" . a , , ; ; "https://notebooks.egi.eu/user/da47d3640f619a02cb075c15d288fc09e053bf46b90d26ec335392acdfae866b@egi.eu/doc/tree/datahub/Reliance/MarGnet_ML/arcWorkflow.ipynb"; ; "2022-05-09 10:55:53.416434+00:00"; "2022-08-30 14:29:46.615503+00:00"; "This Notebook provides a workflow of ArcGis toolboxes to identify ML targets from bathynetry."; ; "Marine Litter Targets Identification"; "2022-05-09 10:55:53.416434+00:00" . a , , ; ; "http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/dd465b46-0217-426a-ba81-4acadf0d12b9"; 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To execute this Jupyter Notebook, data contained in the \"input folder\" is needed (please create a folder called \"data\" in the folder where you have stored the notebook)."""; ; "How to use EarthDataLab.jl to do large scale computations (Jupyter Notebook)"; "2022-09-02 19:19:48.682613+00:00" . a , ; "04jcwf484"; "Nordic e-Infrastructure Collaboration" . a ; "POLYGON ((6.152342408895493 36.11420992771953, 6.152342408895493 46.14432008685165, 19.042966514825824 46.14432008685165, 19.042966514825824 36.11420992771953, 6.152342408895493 36.11420992771953))"; "6.152342408895493 36.11420992771953, 6.152342408895493 46.14432008685165, 19.042966514825824 46.14432008685165, 19.042966514825824 36.11420992771953, 6.152342408895493 36.11420992771953" . a ; ; "c23c13de-3616-4fe4-9df0-64c0c303b28b"; "POLYGON ((6.152342408895493 36.11420992771953, 6.152342408895493 46.14432008685165, 19.042966514825824 46.14432008685165, 19.042966514825824 36.11420992771953, 6.152342408895493 36.11420992771953))" . a , , , , ; dct:doi "10.24424/2byf-7r07"; "False"; ; "2022-10-05 11:05:15.777066+00:00"; ; , ; ; ; "163759"^^xsd:integer; "https://api.rohub.org/api/ros/77a61d94-3318-4d33-a3c0-4730e7026fdb/crate/download/"; ; ; "2022-09-02 19:02:01.731061+00:00"; "2024-03-05 12:18:33.627372+00:00"; "2022-09-02 19:02:01.731061+00:00"; """This talk is part of the Pangeo Show & Tell series and was given on September 1st 2022 by Felix Cremer. Bio Felix Cremer received his diploma in mathematics from the University of Leipzig in 2014. In 2016 he started his PhD study on time series analysis of hypertemporal Sentinel-1 radar data. He currently works at the Max-Planck-Institute for Biogeochemistry on the development of the JuliaDataCubes ecosystem in the scope of the NFDI4Earth 5 project. Abstract The Earth Data Lab (EDL) is a data cube framework in Julia for the efficient handling of raster data. It is based on the YAXArrays.jl package. YAXArrays.jl provides functionality to deal with labelled arrays, similar to the xarray python package and it also provides efficient and easy multithreading and distributed computation of user defined functions along arbitrary slices of the data. EarthDataLab.jl uses DiskArrays.jl in the backend to deal with out of memory datasets. In this Show-and-Tell Felix is going to give a short introduction into the EarthDataLab.jl package for raster data handling in Julia."""; "application/ld+json"; , , , ; "https://w3id.org/ro-id/77a61d94-3318-4d33-a3c0-4730e7026fdb"; "geodata", "julia"; ; "Video"; "Handling large geo data with Julia - snapshot", "Handling large geo data with Julia"; ; ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; ; "Felix Cremer, and Pangeo Europe. \"Handling large geo data with Julia.\" ROHub. Sep 02 ,2022. https://doi.org/10.24424/2byf-7r07." . a , ; "POLYGON ((6.152342408895493 36.11420992771953, 6.152342408895493 46.14432008685165, 19.042966514825824 46.14432008685165, 19.042966514825824 36.11420992771953, 6.152342408895493 36.11420992771953))" . a , ; , , ; "output" . a , ; , ; "tool" . a , ; , ; "biblio" . a , ; , , , , , , ; "input" . a , , ; ; "138593"^^xsd:integer; "https://api.rohub.org/api/resources/9b5c569a-f9bd-4147-9844-4d856bd858db/download/"; ; "2022-09-02 19:30:37.195378+00:00"; "2022-10-05 11:05:15.216316+00:00"; "Plot from the Julia Jupyter notebook."; "image/png"; ; "plot_italy_julia_pangeo_ST.png"; "2022-09-02 19:30:37.195378+00:00" . a ; dct:conformsTo ; . a . a ; "A community platform for Big Data geoscience"; "pangeo-europe@gmail.com"; "Pangeo"; "https://pangeo.io/" . a ; "raster data"; "13.14031180400891"; "5.9" . a ; "memory dataset"; "14.823008849557521"; "6.7" . a ; "computer operations and hardware"; "100.0"; "0.9168391823768616" . a ; "on Sep-1-2022" . a ; "diploma"; "7.854406130268199"; "4.1" . a ; "In this Show-and-Tell Felix is going to give a short introduction into the EarthDataLab.jl package for raster data handling in Julia."; "35.1981351981352"; "15.1" . a ; "time series"; "10.727969348659006"; "5.6" . a ; "YAXArrays.jl package"; "24.557522123893804"; "11.1" . a ; "earth sciences"; "100.0"; "0.9773926138877869" . a ; "data"; "18.262806236080177"; "8.2" . a ; "Library and museum"; "Arts, culture and entertainment/Culture/Library and museum" . a ; "mathematical and computer sciences"; "100.0"; "0.9168391823768616" . a ; "EarthDataLab.jl"; "16.70378619153675"; "7.5" . a ; "handling"; "12.694877505567929"; "5.7" . a ; "Plovdiv"; . a ; "treatment"; "15.708812260536398"; "8.2" . a ; "data"; "21.839080459770116"; "11.4" . a ; "functionality"; "8.045977011494253"; "4.2" . a ; "in 2014" . a ; "computer science"; "51.54639175257732"; "5.0" . a ; "Science and technology"; "Science and technology" . a ; "other earth sciences"; "100.0"; "0.9773926138877869" . a ; "The Earth Data Lab (EDL) is a data cube framework in Julia for the efficient handling of raster data."; "31.934731934731936"; "13.7" . a ; "dataset"; "10.244988864142538"; "4.6" . a ; "This talk is part of the Pangeo Show & Tell series and was given on September 1st 2022 by Felix Cremer."; "32.86713286713287"; "14.1" . a ; "raster data handling"; "26.106194690265486"; "11.8" . a ; "multithreading"; "6.8965517241379315"; "3.6" . a ; "geo data"; "19.469026548672566"; "8.8" . a ; "YAXArrays.jl"; "13.585746102449889"; "6.1" . a ; "In 2016" . a ; "Felix Cremer"; "15.367483296213809"; "6.9" . a ; "calculation"; "7.662835249042146"; "4.0" . a ; "dataset"; "12.452107279693488"; "6.5" . a ; "parcel"; "8.812260536398467"; "4.6" . a ; "database"; "48.453608247422686"; "4.7" . a ; "series analysis"; "15.044247787610619"; "6.8" . a , , ; ; "https://youtu.be/18_e8wmI9Os"; ; "2022-09-02 19:13:04.311770+00:00"; "2022-10-05 11:05:08.693363+00:00"; "This is the recorded talk from Felix Cremer during the Pangeo Show & Tell in September 1st, 2022. Felix is going through his Julia Notebook and explain us about handling large geo data with Julia."; ; "Youtube video \"Handling large geo data with julia by Felix Cremer.\""; "2022-09-02 19:13:04.311770+00:00" . a ; "Max-Planck-Institute (Germany)"; "fcremer@bgc-jena.mpg.de"; "Felix Cremer" . a ; "pangeo.europe@gmail.com"; "Pangeo Europe" . } sub:provenance { sub:assertion prov:wasDerivedFrom . } sub:pubinfo { this: a npx:RoCrateNanopub; dct:created "2026-03-03T15:22:40.389+01:00"^^xsd:dateTime; dct:creator ; npx:introduces ; rdfs:label "Handling large geo data with Julia - snapshot" . sub:sig npx:hasAlgorithm "RSA"; npx:hasPublicKey "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAxszSDYX5tuCSkP7UiCtftYPFNQVTjgNu0I5fwdML2DLRDlp0xzmsQXRk8oHuvwGvG1aMjj6cpUqO+0rz2Sg/wvHOgUpkRH8VJXvmlkhafMLCMtUtk5JIx7e+fkzCby+fnmD7kMkGLrT+OaExWwEDmNlCAt0TPKcHSdwsjso2isXjtAsGevyCMke8ufnFYpjs746JES1eNzVnHnn2Kp/lqcm60GM+J8dLgRZp7fX0anW098xhKym6+xXFzqeju0vYRIHBPerv+r7skWxwk+a7Sd8msqVeYEv6NTqnyWvyWb6Yh8cvj04N6qm/T6C5FUPLQhzSaQgMVMU6yLqjPuu9DwIDAQAB"; npx:hasSignature "p7+/JetPaC5vEs3gEqhj4Lbg/7HxgazbpVHbnDMpXWtSAvecZMjHYclXm/L2dt55idHyBkt3P6y38TMBlKOgAPi+nt4elsKgtCtADj7dGr/Xe7bIE47JCeCOS9F9HDWabFqaiBnY7CJRkFGOu6+tbjkFGkYBSgeLSAxG6rDMu8sZHL3Sqx3hgOhBuOa2IPBXM9SuMlpIbm+TCJfdSUCfcuZ5cttQxBhF8zQSs4pWh3mcatKEtYV0ZKG+/SRWPImxPCyI/Im9TAIpah+9+9b0qDb8N79juwejt//yTbO3vT9VcDveSfacALTW80MiBkhHz0yg8VOm+GWfl4tb+lfx/g=="; npx:hasSignatureTarget this:; npx:signedBy . } @prefix this: . @prefix sub: . @prefix np: . @prefix dct: . @prefix pav: . @prefix rdf: . @prefix owl: . @prefix rdfg: . @prefix dce: . @prefix xsd: . @prefix rdfs: . @prefix prov: . @prefix npx: . sub:Head { this: a np:Nanopublication; np:hasAssertion sub:assertion; np:hasProvenance sub:provenance; np:hasPublicationInfo sub:pubinfo . } sub:assertion { a ; ""; "Applied sciences" . a ; ""; "Earth sciences" . a ; ""; "Earth observation" . a , , ; ; "https://discourse.pangeo.io/t/discrete-global-grid-systems-dggs-use-with-pangeo/2274"; ; "2022-10-07 12:57:56.628114+00:00"; "2022-10-25 15:48:28.199436+00:00"; "Discussion from Pangeo Discourse on DGGS use with Pangeo."; "discussion"; ; "Pangeo discourse on \"Discrete Global Grid Systems (DGGS) use with Pangeo\""; "2022-10-07 12:57:56.628114+00:00" . a , , ; ; "https://discourse.pangeo.io/t/october-6-2022-dggs-and-their-potential-impact-in-geoscience-and-geospatial-communities/2759"; ; "2022-10-25 15:45:23.831383+00:00"; "2022-10-25 15:48:40.680580+00:00"; "Pangeo discourse announcement."; "discourse"; ; """Pangeo discourse announcement Show & Tell on \"October 6, 2022: DGGS and their potential impact in Geoscience and Geospatial communities\""""; "2022-10-25 15:45:23.831383+00:00" . a , , ; ; "https://github.com/allixender/pangeo_dggs_2022"; ; "2022-10-07 12:51:00.692996+00:00"; "2022-10-25 15:48:26.907094+00:00"; """Github repository with examples used during the Pangeo Show and Tell - 06. Oct., 2022 on \"DGGS and their potential impact in Geoscience and Geospatial\" by Alexander Kmoch (Landscape Geoinformatics Lab, University of Tartu, Estonia). Twitter: @Lgeoinformatics │ @allixender"""; "jupyter notebook"; ; "Pangeo Show and Tell : DGGS play ground"; "2022-10-07 12:51:00.692996+00:00" . a , , ; ; "https://hackmd.io/@pangeo/showandtell"; ; "2022-10-25 07:27:19.067533+00:00"; "2022-10-25 15:48:28.394740+00:00"; """This is the shared document we use for all the Pangeo Show and Tell. We collect information, Q&A and feedback. Each Show and Tell has its own sub-section."""; "hackmd"; ; "HackMD Pangeo Show and Tell"; "2022-10-25 07:27:19.067533+00:00" . a ; "University of Tartu, Estonia"; "alexander.kmoch@ut.ee"; "Alexander Kmoch"; "0000-0003-4386-4450" . a , , ; ; "https://raw.githubusercontent.com/allixender/pangeo_dggs_2022/main/environment.yml"; ; "2022-10-17 14:04:26.842481+00:00"; "2022-10-25 15:48:24.056839+00:00"; "Conda environment for running DGGS notebook examples."; "environment"; ; "environment.yml"; "2022-10-17 14:04:26.842481+00:00" . a , , ; ; "https://raw.githubusercontent.com/allixender/pangeo_dggs_2022/main/h3_intro.ipynb"; ; "2022-10-17 14:07:52.027331+00:00"; "2022-10-25 15:48:40.921243+00:00"; "Jupyter Notebook demonstrating how to perform Spatial Data Analysis with H3."; "H3"; ; "h3_intro.ipynb"; "2022-10-17 14:07:52.027331+00:00"; . a , ; "post@simula.no"; "00vn06n10"; "Simula Research Laboratory" . a . a ; "A community platform for Big Data geoscience"; "pangeo-europe@gmail.com"; "Pangeo"; "https://pangeo.io/" . a ; "POLYGON ((-175.78125000000003 -80.21861403809504, -175.78125000000003 84.00379284323029, 191.25002145767215 84.00379284323029, 191.25002145767215 -80.21861403809504, -175.78125000000003 -80.21861403809504))"; "-175.78125000000003 -80.21861403809504, -175.78125000000003 84.00379284323029, 191.25002145767215 84.00379284323029, 191.25002145767215 -80.21861403809504, -175.78125000000003 -80.21861403809504" . a ; ; "c0cb3d9d-0b6e-46b0-8a78-c03449698c8d"; "POLYGON ((-175.78125000000003 -80.21861403809504, -175.78125000000003 84.00379284323029, 191.25002145767215 84.00379284323029, 191.25002145767215 -80.21861403809504, -175.78125000000003 -80.21861403809504))" . a , , , , ; dct:doi "https://doi.org/10.24424/tg01-kv33"; "False"; ; "2022-10-25 15:48:48.641529+00:00"; ; , , ; ; ; "10306143"^^xsd:integer; "https://api.rohub.org/api/ros/d1f369cd-25a2-4fc6-b418-b2e7feed7cde/crate/download/"; ; ; "2022-10-04 09:22:53.114240+00:00"; "2024-03-05 12:17:36.266464+00:00"; "2022-10-04 09:22:53.114240+00:00"; """A Discrete Global Grid Systems (DGGS) is a unique type of spatial reference system comprising of a hierarchy of uniquely identifiable discrete grid cells that span the globe at multiple resolutions. 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While the signing will take place at the end of the conference, in Leiden, we would like to invite you to add your name to the movement initiated by FDO2022 by signing the declaration online. It is an opportunity for all of us working in research, technology, policy and beyond to support an unprecedented effort to further develop FAIR digital objects, open standards and protocols, and increased reliability and trustworthiness of data. In short, a new environment that works as a truly meaningful data space. You can sign the declaration using the button at the end of the page. 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Researchers, disciplinary groups and anyone interested to learn about both EOSC-related tools and services for data sharing and discoverability as well as discipline-related solutions are invited to the webinar. Attendees will also hear first-hand accounts from early-adopter communities that have integrated some of these core EOSC services. 1 programme, 2 days Check out the agenda to get a glimpse of the cases in the programme, in addition to a at the users, EU and UN officials who will be weighing in on discussions. Day 1 – 5 December • 09.30-11.00: Digital assets supporting SDG 13: Climate action • 11.15-12.00: Digital assets supporting SDG 3: Good health and well-being • 12:15-13:00: Discovering services for open science Day 2 – 6 December • 09.00-09.45: Digital assets supporting SDG 9 Industry, innovation and infrastructure • 10.00-10.45: Experiences from Early Adopters approaching EOSC: the RELIANCE Open challenge • 11.00-12.00: Lessons Learnt from use cases and Looking forward"""; "application/ld+json"; , , , , , , , ; "https://w3id.org/ro-id/107487d2-a9d5-4224-8b00-b321e133b6c8"; "deep learning", "forecasting", "sea-ice"; ; "Presentation"; "Pan-European digital assets supporting research communities – Climate Change with RELIANCE & EOSC - snapshot", "Pan-European digital assets supporting research communities – Climate Change with RELIANCE & EOSC"; ; "MANUAL"; "https://w3id.org/ro-id/107487d2-a9d5-4224-8b00-b321e133b6c8/1c144684-1ea3-4cb5-93e6-8cffecf3b849"; "Anne Foilloux, Jean Iaquinta, and Alejandro Coca-Castro. \"Pan-European digital assets supporting research communities – Climate Change with RELIANCE & EOSC.\" ROHub. 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ESMs used in the Nordic countries are clearly not ready for EuroHPC and very little dedicated funding from the scientific community is used for porting existing codes to future architectures. Providers have hired several specialists to support the scientific community but the commitment from the scientific community is not there. Exchange of knowledge of involved staff (scientists, RSEs, technical support) would be very helpful. For instance, being able to organize meetings/hackathons (online or face to face) with both experts from NorESM and EC-EARTH has been highlighted as an important requirements by those involved in the GPU hackathon. Code refactoring and best software practices are the most important component for efficient usage of new architecture, including EuroHPC."""; ; "NICEST2 - D4.5: First report on the identified bottlenecks for an efficient usage of Nordic ESMs on EuroHPC"; "2023-01-08 21:06:32.125399+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.4944686"; ; "2023-01-08 21:03:28.636733+00:00"; "2023-02-19 13:17:22.369015+00:00"; "This report summarizes the first NICEST2 hackathon with FAIR experts and Earth System Model specialists to understand what needs to be done to make climate data FAIR. It will help us to define our roadmap for FAIR Climate in the Nordics."; ; "NICEST2 - D3.3: Report on NICEST2 FAIR climate data hackathon"; "2023-01-08 21:03:28.636733+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.5571344"; ; "2023-01-08 21:08:01.968412+00:00"; "2023-02-19 13:17:27.394767+00:00"; "The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system Models (ESMs) that is not widely used in the Nordics yet. A hackathon/workshop was held on March 12, 2021 as a joint event between the INES, NICEST2 and IS-ENES3 projects. During this hackathon, we identified the needs for specific diagnostics for the Nordics that could help researchers to diagnose strengths and deficiencies of current ESMs. We also discussed how to better organize access to data and share resources within the Nordics."; ; "NICEST2 - D2.1: Short report from the Nordic ESM diagnostics hackathon"; "2023-01-08 21:08:01.968412+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.5571416"; ; "2023-01-08 21:10:14.737755+00:00"; "2023-02-19 13:17:27.065885+00:00"; "The Nordic climate modeling community consists of research groups at universities, national meteorological institutes and research institutes, and holds demonstrable world class excellence in the field. Several of these groups contribute to the development of both global and regional climate models (GCMs and RCMs,respectively) in international projects with collaborations within Europe and the US. However, many users, including PhDs and postdocs, are developing and/or running Earth System Models (ESMs) for more fundamental scientific research and sensitivity studies, and/or cross-disciplinary research (economy & climate, biodiversity, etc.) and they do not always benefit from the advances, technologies or resources leveraged by these large projects/consortiums. One concrete example is IS-ENES project (https://is.enes.org/) where only one university, namely Linköpings Universitet (not part of the NICEST2 consortium) from the Nordics is involved; Nordic contributions are mostly from Meteorological services and Research Institutes. From a practical point of view this translates in a lot of time/energy wasted “reinventing the wheel”, repeated simulations, lack of transparency, suboptimal use of the infrastructures, etc. In this context, supporting these researchers and realizing the benefits of Open Science and EOSC are our priorities within NICEST2 and WP4."; ; "NICEST2 - D4.1: Identification of the Nordic ESM community needs for ESM workflows"; "2023-01-08 21:10:14.737755+00:00" . a , , ; ; "https://nordicesmhub.github.io/NorESM_user_workshop_2021/intro.html"; ; "2023-01-08 20:50:23.537300+00:00"; "2023-02-19 13:17:27.609612+00:00"; "Training material on containers for ESM. This training material uses the Norwegian Earth System Model (NorESM) and has been delivered in 2021 as part of the NorESM user meeting."; "text/html"; "training"; ; "Running NorESM in a container"; "2023-01-08 20:50:23.537300+00:00" . a , , ; ; "https://nordicesmhub.github.io/nicest2-fair-hackathon/"; ; "2023-01-08 20:52:04.176203+00:00"; "2023-02-19 13:17:18.829914+00:00"; "First NICEST2 hackathon to understand the FAIR concept and how they can apply to the Nordic Earth System Modelling Community."; ; "NICEST2 hackathon on FAIR climate data"; "2023-01-08 20:52:04.176203+00:00" . a , , ; ; "https://nordicesmhub.github.io/nicest2/2020/05/04/plan.html"; ; "2023-01-09 08:28:36.495799+00:00"; "2023-02-19 13:17:20.174631+00:00"; "Link to the NICEST2 project plan."; "text/html"; ; "Project plan"; "2023-01-09 08:28:36.495799+00:00" . a ; "Finnish Meteorological Institute (Finland)"; "antti-ilari.partanen@fmi.fi"; "Antti-Ilari Partanen"; "0000-0002-0883-8161" . a ; "Simula Research Laboratory"; "annef@simula.no"; "Anne Fouilloux"; "0000-0002-1784-2920" . a ; "NSC (Sweden)"; "struthers@nsc.liu.se"; "Hamish Struthers"; "0000-0002-4214-2213" . a ; "NERSC (Norway)"; "yanchun.he@nersc.no"; "Yanchun He"; "0000-0002-5932-3627" . a ; "Finnish Meteorological Institute (Finland)"; "tommi.bergman@fmi.fi"; "Tommi Bergman"; "0000-0002-6133-2231" . a ; "Norwegian Meteorological Institute (Norway)"; "oskaral@met.no"; "Oskar Landgren"; "0000-0002-6264-8502" . a ; "jeani@uio.no"; "Jean Iaquinta"; "0000-0002-8763-1643" . a ; "Finnish Meteorological Institute (Finland)"; "risto.makkonen@fmi.fi"; "Risto Makkonen"; "0000-0002-8961-3393" . a , ; "post@simula.no"; "00vn06n10"; "Simula Research Laboratory" . a , ; "04jcwf484"; "Nordic e-Infrastructure Collaboration" . a ; ; "8fc9a20e-fa82-43a8-93f4-cd4cc4a45ac8"; "POINT (10.138547627793743 61.47037998202813)" . a ; "10.138547627793743"; "61.47037998202813"; "POINT (10.138547627793743 61.47037998202813)" . a , , ; dct:doi "https://doi.org/10.24424/9y3x-hg89"; "False"; ; "2023-02-19 13:17:31.060596+00:00"; ; ; , , , , ; ; "763258"^^xsd:integer; "https://api.rohub.org/api/ros/b62e5267-8fe1-4fe1-ada2-47e484c2b107/crate/download/"; , , , , , , , , , ; , ; ; "2023-01-08 20:41:20.579173+00:00"; "2024-03-05 12:18:19.992972+00:00"; "2023-01-08 20:41:20.579173+00:00"; "Overview of the NICEST2 project and reflection on the successes, failures and possible improvements for follow-up projects."; "application/ld+json"; , , , , , , ; "https://w3id.org/ro-id/b62e5267-8fe1-4fe1-ada2-47e484c2b107"; "climate", "e-infrastructure"; ; "Poster"; "Experience from the NeIC NICEST2 project - NeIC All-Hands meeting (23–26 Jan 2023)", "Experience from the NeIC NICEST2 project - snapshot"; , ; ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , ; ; "Iaquinta, Jean, Oskar Landgren, Alok Kumar Gupta, Prashanth Dwarakanath, Anne Fouilloux, Tommi Bergman, Tyge Løvseth, et al. \"Experience from the NeIC NICEST2 project - NeIC All-Hands meeting (23–26 Jan 2023).\" ROHub. 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In view of COVID-19 pandemic, lockdowns were imposed in India. Travel, fishing, tourism and religious activities were halted, while domestic and industrial activities were restricted. Comparison of the pre- and post-lockdown data shows that water parameters such as turbidity, nutrient concentration and microbial levels have come down from pre- to post-lockdown period, and parameters such as dissolved oxygen levels, phytoplankton and fish densities have improved. The concentration of macroplastics has also dropped from the range of 138 ± 4.12 and 616 ± 12.48 items/100 m2 to 63 ± 3.92 and 347 ± 8.06 items/100 m2. Fish density in the reef areas has increased from 406 no. 250 m−2 to 510 no. 250 m−2. The study allows an insight into the benefits of effective enforcement of various eco-protection regulations and proper management of the marine ecosystems to revive their health for biodiversity conservation and sustainable utilization."; "Reef fish", "covid-19", "environmental health", "plastic pollution"; ; "COVID-19 lockdown improved the health of coastal environment and enhanced the population of reef-fish"; "2023-01-08 19:24:00.526730+00:00" . a , , ; ; "https://earthobservatory.nasa.gov/images/83394/parting-the-sea-to-save-venice"; ; "2023-01-08 19:58:47.516622+00:00"; "2023-02-19 13:22:55.402245+00:00"; "The natural-color Landsat images above show some of the MOSE engineering efforts that are visible above the water line near the Lido Inlet. The top image was acquired on June 20, 2000, by the Enhanced Thematic Mapper+ on Landsat 7. The second image, from the Operational Land Imager on Landsat 8, was collected on September 4, 2013. Turn on the image comparison tool to make the changes easier to see. (Note that Landsat 8 has a greater dynamic range than Landsat 7, so the Landsat 8 image is crisper the Landsat 7 image.)"; ; "Parting the Sea to Save Venice"; "2023-01-08 19:58:47.516622+00:00" . a ; "giorgio.castellan@bo.ismar.cnr.it"; "Giorgio Castellan"; "0000-0001-6084-1504" . a ; "Simula Research Laboratory"; "annef@simula.no"; "Anne Fouilloux"; "0000-0002-1784-2920" . a ; "federica.foglini@ismar.cnr.it"; "Federica Foglini"; "0000-0002-2736-0052" . a ; "jeani@uio.no"; "Jean Iaquinta"; "0000-0002-8763-1643" . a ; "CNR-ISMAR"; "malek.belgacem@ve.ismar.cnr.it"; "Malek Belgacem"; "0000-0003-0745-4155" . a ; "Małgorzata Wolniewicz" . a , , ; ; ; "https://reliance.adamplatform.eu/?dataset=69623:EU_CAMS_SURFACE_NO2_G"; ; "2023-01-08 19:40:14.176174+00:00"; "2023-02-19 13:22:52.387115+00:00"; "CAMS NITROGEN DIOXIDE"; "2022-12-27T23:00:00Z"; "NO2"; ; "CAMS European air quality forecasts: NO2"; "2023-01-08 19:40:14.176174+00:00"; "2018-07-12T00:00:00Z"; ; "Float32"; "mailto:govoni@meeo.it"; "[1.354510459350422e-07]"; "[0.0]" . a , , ; ; ; "https://reliance.adamplatform.eu/?dataset=69625:EU_CAMS_SURFACE_O3_G"; ; "2023-01-08 19:41:17.789149+00:00"; "2023-02-19 13:22:49.529744+00:00"; "CAMS OZONE"; "2022-12-27T23:00:00Z"; "O3"; ; "CAMS European air quality forecasts: O3"; "2023-01-08 19:41:17.789149+00:00"; "2018-07-12T00:00:00Z"; ; "Float32"; "mailto:govoni@meeo.it"; "[2.2007016298175586e-07]"; "[0.0]" . a , , ; ; ; "https://reliance.adamplatform.eu/?dataset=69627:EU_CAMS_SURFACE_PM25_G"; ; "2023-01-08 19:42:25.690080+00:00"; "2023-02-19 13:22:51.053690+00:00"; "CAMS SURFACE PARTICULATE METTER D<2.5"; "2022-12-27T23:00:00Z"; "PM2.5"; ; "CAMS European air quality forecasts: PM25"; "2023-01-08 19:42:25.690080+00:00"; "2018-07-12T00:00:00Z"; ; "Float32"; "mailto:govoni@meeo.it"; "[709.8012084960938]"; "[0.0]" . a , ; "post@simula.no"; "00vn06n10"; "Simula Research Laboratory" . a , , ; ; "https://w3id.org/ro-id/0869e396-3733-4aff-8fb2-94c8937b28aa"; ; "2023-01-08 19:15:20.212877+00:00"; "2023-02-19 13:22:55.556680+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."; ; "Snapshot 2021 study case: Lockdown impacts on the Northern Adriatic Sea at selected site: AcquaAlta Platform Water quality"; "2023-01-08 19:15:20.212877+00:00" . a , , ; ; "https://w3id.org/ro-id/53aa90bf-c593-4e6d-923f-d4711ac4b0e1"; ; "2023-01-08 19:14:03.311972+00:00"; "2023-02-19 13:22:50.947789+00:00"; "The COVID-19 pandemic has led to significant reductions in economic activity, especially during lockdowns. Several studies has shown that the concentration of nitrogen dioxyde and particulate matter levels have reduced during lockdown events. Reductions in transportation sector emissions are most likely largely responsible for the NO2 anomalies. In this study, we analyze the impact of lockdown events on the air quality using data from Copernicus Atmosphere Monitoring Service over Europe and at selected locations."; ; "Impact of the Covid-19 Lockdown on Air quality over Europe"; "2023-01-08 19:14:03.311972+00:00" . a , , ; ; "https://w3id.org/ro-id/53aa90bf-c593-4e6d-923f-d4711ac4b0e1/resources/2a2b6f01-be2e-414e-af08-d882aa995a71"; ; "2023-01-08 19:21:48.221333+00:00"; "2023-02-19 13:22:50.794426+00:00"; "In order to fight against the spread of COVID-19, the most hard-hit countries in the spring of 2020 implemented different lockdown strategies. To assess the impact of the COVID-19 pandemic lockdown on air quality worldwide, Air Quality Index (AQI) data was used to estimate the change in air quality in 20 major cities on six continents. Our results show significant declines of AQI in NO2, SO2, CO, PM2.5 and PM10 in most cities, mainly due to the reduction of transportation, industry and commercial activities during lockdown. This work shows the reduction of primary pollutants, especially NO2, is mainly due to lockdown policies. However, preexisting local environmental policy regulations also contributed to declining NO2, SO2 and PM2.5 emissions, especially in Asian countries. In addition, higher rainfall during the lockdown period could cause decline of PM2.5, especially in Johannesburg. By contrast, the changes of AQI in ground-level O3 were not significant in most of cities, as meteorological variability and ratio of VOC/NOx are key factors in ground-level O3 formation."; ; "Impact of the COVID-19 Pandemic Lockdown on Air Quality Pollution in 20 Major cities around the World"; "2023-01-08 19:21:48.221333+00:00" . a . a , , ; ; "https://w3id.org/ro-id/c2c64bf9-7625-4442-9ca9-dcd978b1d38b"; ; "2023-01-08 19:19:35.675216+00:00"; "2023-02-19 13:22:48.215320+00:00"; "Integration of data on Air and Water quality in the Venice Lagoon to assess the impact of the Covid-19 Lockdown"; ; "Impact of the Covid-19 Lockdown on Air and Water quality in the Venice Lagoon"; "2023-01-08 19:19:35.675216+00:00" . a ; "The main interest is upon marine litter pollution and in particular ranging from marco to mirco and nano size. 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Govaart, Simon M. Hofmann, Evelyn Medawar. Ever-increasing anthropogenic greenhouse gas emissions narrow the timeframe for humanity to mitigate the climate crisis. Scientific research activities are resource demanding and, consequently, contribute to climate change; at the same time, scientists have a central role in advancing knowledge, also on climate-related topics. In this opinion piece, we discuss (1) how open science – adopted on an individual as well as on a systemic level – can contribute to making research more environmentally friendly, and (2) how open science practices can make research activities more efficient and thereby foster scientific progress and solutions to the climate crisis. While many building blocks are already at hand, systemic changes are necessary in order to create academic environments that support open science practices and encourage scientists from all fields to become more carbon-conscious, ultimately contributing to a sustainable future."""; "climate crisis", "open science", "sustainability"; ; "The Sustainability Argument for Open Science"; "2022-10-14 12:43:21.299002+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.6589624"; ; "2022-10-14 13:44:35.094465+00:00"; "2023-02-19 13:45:14.339103+00:00"; """Sharan, Malvika In this talk, I discuss open science as a framework to ensure that all our research components can be easily accessed, openly examined and built upon by others. I will introduce The Turing Way - an open source, open collaboration and community-driven guide to reproducible, ethical and inclusive data science and research. Drawing insights from the project, I will share best practices that researchers should integrate to ensure the highest reproducible and ethical standards from the start of their projects so that their research work is easy to reuse and reproduce at all stages of the development. All attendees will leave the talk understanding the many dimensions of openness and how they can participate in an inclusive, kind and inspiring open source ecosystem as they collaboratively seek to improve research culture. All questions and contributions are welcome at the GitHub repository: https://github.com/alan-turing-institute/the-turing-way. Home page: https://malvikasharan.github.io/ This was a closing keynote at Concordia University in Montreal on 27 May 2022."""; ; "Open science for enabling reproducible, ethical and collaborative research: Insights from The Turing Way"; "2022-10-14 13:44:35.094465+00:00" . a , , ; ; "https://en.wikipedia.org/wiki/Climate_justice"; ; "2022-10-15 08:03:53.413292+00:00"; "2023-02-19 13:45:22.058293+00:00"; "Definition of Climate Justice from Wikipedia."; "wikipedia"; ; "Climate Justice (Wikipedia)"; "2022-10-15 08:03:53.413292+00:00" . a , , ; ; "https://en.wikipedia.org/wiki/Environmental_justice"; ; "2022-10-15 08:02:56.218937+00:00"; "2023-02-19 13:45:11.910714+00:00"; "Definition of Environmental Justice from Wikipedia"; "wikipedia"; ; "Environmental Justice (Wikipedia)"; "2022-10-15 08:02:56.218937+00:00" . a ; "Simula Research Laboratory"; "annef@simula.no"; "Anne Fouilloux"; "0000-0002-1784-2920" . a ; "jeani@uio.no"; "Jean Iaquinta"; "0000-0002-8763-1643" . a , ; "post@simula.no"; "00vn06n10"; "Simula Research Laboratory" . a . a ; "POLYGON ((-170.15625 -81.09321385260837, -170.15625 84.67351256610525, 191.25000000000003 84.67351256610525, 191.25000000000003 -81.09321385260837, -170.15625 -81.09321385260837))"; "-170.15625 -81.09321385260837, -170.15625 84.67351256610525, 191.25000000000003 84.67351256610525, 191.25000000000003 -81.09321385260837, -170.15625 -81.09321385260837" . a ; ; "bf216e0e-aa84-449a-9cc2-dc6454de6d14"; "POLYGON ((-170.15625 -81.09321385260837, -170.15625 84.67351256610525, 191.25000000000003 84.67351256610525, 191.25000000000003 -81.09321385260837, -170.15625 -81.09321385260837))" . a , , , , ; dct:doi "https://doi.org/10.24424/pm9w-vq46"; "False"; ; "2023-02-19 13:45:25.668867+00:00"; ; , ; ; ; "5188278"^^xsd:integer; "https://api.rohub.org/api/ros/0e6ee388-ce22-4237-bf54-74336d1215ce/crate/download/"; , ; ; ; "2022-10-14 12:24:09.298835+00:00"; "2024-03-05 12:22:11.007454+00:00"; "2022-10-14 12:24:09.298835+00:00"; """OpenAIRE OAWeek - Research communities & climate action; being open to drive change Description This session will invite expert researchers to discuss their scientific impact in climate related topics. Why are they embracing open science practices in their current research workflows? How are they using the resources provided in the European Open Science Cloud (EOSC)? Is open access enabling researchers to contribute better to Climate Change solutions? If you’re curious about these innovative initiatives by the research communities, make sure you attend! Speakers: Anne Fouilloux (RELIANCE) Anabela de Oliveira (EGI-ACE) Bjorn Backeberg (C-SCALE) Prof Spyridon Rapsomanikis, Athena RC, NEANIAS"""; "application/ld+json"; , , , , , , ; "https://w3id.org/ro-id/0e6ee388-ce22-4237-bf54-74336d1215ce"; "climate change", "climate justice", "open science"; ; "Presentation"; "OpenAIRE OAWeek: Open for Climate Justice - snapshot", "OpenAIRE OAWeek: Open for Climate Justice"; ; ; "MANUAL"; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ; "http://w3id.org/ro/earth-science#BibliographyCentricResearchObjectTemplate"; ; "Fouilloux, Anne, Jean Iaquinta, and Pangeo Europe. \"OpenAIRE OAWeek: Open for Climate Justice.\" ROHub. 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Mar 26 ,2022. https://doi.org/10.24424/f0q9-8e35." . a , ; "POINT (7.8337097307667145 48.01044395569975)" . a , ; "POINT (10.766601562500002 59.921531172441085)" . a , ; , ; "output" . a , ; , ; "input" . a , ; , , ; "biblio" . a , ; , , ; "tool" . a , , ; ; "448436"^^xsd:integer; "https://api.rohub.org/api/resources/039f0e1f-ddb5-4a6b-8047-094aeb37b259/download/"; ; "2022-03-30 16:49:24.424570+00:00"; "2023-02-19 13:50:03.407487+00:00"; "Copernicus Atmosphere Monitoring Service PM2.5, 2 day forecasts, 24th December 2021 at 12:00 UTC"; "image/png"; ; "CAMS PM2.5, 2 day forecasts, 24th December 2021 at 12:00 UTC"; "2022-03-30 16:49:24.424570+00:00" . a . a , , ; ; "https://training.galaxyproject.org/training-material/topics/climate/tutorials/pangeo-notebook/tutorial.html"; ; "2022-03-30 15:59:56.246391+00:00"; "2023-02-19 13:49:56.427998+00:00"; """Training material (hands-on) where Pangeo Notebook is used to learn Xarray. This training is part of the Galaxy Training Network (GTN). In this tutorial, we will learn about Xarray, one of the most used Python library from the Pangeo ecosystem. We will be using data from Copernicus Atmosphere Monitoring Service and more precisely PM2.5 (Particle Matter < 2.5 μm) 4 days forecast from December, 22 2021. Parallel data analysis with Pangeo is not covered in this tutorial."""; "text/html"; ; "Pangeo Notebook in Galaxy - Introduction to Xarray (GTN)"; "2022-03-30 15:59:56.246391+00:00" . a , , ; ; "https://quay.io/repository/nordicesmhub/docker-pangeo-notebook"; ; "2022-03-29 11:58:28.213223+00:00"; "2023-02-19 13:49:55.588074+00:00"; """These docker images (different tags) correspond to the docker images built for Galaxy Pangeo JupyterLab. The docker images can be used within Galaxy and as standalone docker images. You can use the same images we use in Galaxy on your local computer or any other platform: 1. Pull an existing image locally docker pull quay.io/nordicesmhub/docker-pangeo-notebook 2. Run a pre-build image from docker registry 3. To start your JupyterLab: docker run -p 7777:8888 quay.io/nordicesmhub/docker-pangeo-notebook and you will top open a new terminal and start your favorite web browser. your running Jupyter Notebook instance on http://localhost:7777/ipython/. Remark: for reproducibility purpose, we suggest you use a specific tag e.g. docker pull quay.io/nordicesmhub/docker-pangeo-notebook:1c0f66b Then use the same tag when starting your JupyterLab application: docker run -p 7777:8888 quay.io/nordicesmhub/docker-pangeo-notebook:1c0f66b"""; ; "Docker images for Galaxy Pangeo JupyterLab (Quay Container Registry)"; "2022-03-29 11:58:28.213223+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.5805953"; ; "2022-03-30 16:52:19.796786+00:00"; "2023-02-19 13:49:55.345103+00:00"; """Dataset used in the Galaxy Pangeo tutorials on Xarray. 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Oak Ridge National Laboratory (ORNL) and Los Alamos National Laboratory (LANL) are collaborating on porting and optimizing Open MPI and related components for use on HPE Cray EX systems, with a focus on the DOE Frontier and Aurora exa-scale systems. A key component of this effort involves development of a new LinkX Open Fabrics Interface (OFI) provider. In this paper, we describe enhancements to Open MPI, OpenPMIx runtime components, and the LinkX OFI provider. Performance results are presented for point to point and collective communication operations using both the vendor CXI provider and the LinkX provider, including results obtained using GPU accelerators. Recommended deployment options for EX systems will be discussed, along with future work."""; "Slingshot 11", "libfabric"; ; "Open MPI for HPE Cray EX Systems"; "2024-01-17 10:54:09.114061+00:00" . } sub:provenance { sub:assertion prov:wasDerivedFrom . } sub:pubinfo { this: a npx:RoCrateNanopub; dct:created "2026-03-03T15:15:44.181+01:00"^^xsd:dateTime; dct:creator ; npx:introduces ; rdfs:label "OSU MPI Get Bandwidth Test v7.2 with OpenMPI 4.1.6 on Fram & Betzy" . sub:sig npx:hasAlgorithm "RSA"; npx:hasPublicKey "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAxszSDYX5tuCSkP7UiCtftYPFNQVTjgNu0I5fwdML2DLRDlp0xzmsQXRk8oHuvwGvG1aMjj6cpUqO+0rz2Sg/wvHOgUpkRH8VJXvmlkhafMLCMtUtk5JIx7e+fkzCby+fnmD7kMkGLrT+OaExWwEDmNlCAt0TPKcHSdwsjso2isXjtAsGevyCMke8ufnFYpjs746JES1eNzVnHnn2Kp/lqcm60GM+J8dLgRZp7fX0anW098xhKym6+xXFzqeju0vYRIHBPerv+r7skWxwk+a7Sd8msqVeYEv6NTqnyWvyWb6Yh8cvj04N6qm/T6C5FUPLQhzSaQgMVMU6yLqjPuu9DwIDAQAB"; npx:hasSignature "VKbxj4o74UWPK2L+apSYP/8k+oJZ8L5XAALPqMSTgDTBTjKa/I2TX5QLxA4efh0IGC8TvvX7EkH0z46LDbAwrZNeTaISBUMBMlyckrubIu3UD5ZcmMU/Po5/HJi6Vtb2emiqeM7sfDYwAdqOqersAvk6bn7OJQDPd6fLkWfyajRQnSl17QxCeiLhkGc20hB36mXXsRmrs+r7XgzjDDguC+8C47mxx65ppvVzYwpYM8vVx2lqnrXXt1nz/gZ0mT6GWJdPaXyljsg3BYi0J7GqzAI2NOE2WQxnp9JnMDD0A/PnUH5WRdQy5Qf2smY5zl8/Ek4MCOe5H6ok/nHbK4CM0w=="; 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"Link to the official GFTS DESP use case."; "WebSite"; ; "DestinE Use Case official website: Global Fish Tracking System (GFTS) DESP Use Case"; "2024-03-13 08:41:04.316157+00:00" . a , , ; ; "https://destination-earth.github.io/DestinE_ESA_GFTS"; ; "2024-03-13 08:45:35.825465+00:00"; "2024-08-12 19:50:16.380874+00:00"; "These webpages are rendered from GitHub repository and contain all the information about the GFTS project. This includes internal description of the use case, technical documentation, progress, presentations, etc."; "WebSite"; ; "GFTS Use case project website"; "2024-03-13 08:45:35.825465+00:00" . a . a , , ; ; "https://doi.org/10.5281/zenodo.10372387"; ; "2023-12-13 20:50:53.907411+00:00"; "2024-08-12 19:50:17.291963+00:00"; "Slides presented by Mathieu Woillez at the Roadshow Webinar: DestinE in action – meet the first DESP use cases (13 December 2023)"; ; "Global Fish Tracking System - DESP Use Case"; "2023-12-13 20:50:53.907411+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.10809819"; ; "2024-03-12 15:34:59.645366+00:00"; "2024-08-12 19:50:18.034736+00:00"; "Poster presented at the 8th InternationalBio-logging Science Symposium by Tina Odaka, March 2024."; "BSL8"; ; "Leveraging Pangeo to Geolocate Fish Using Biologging Data: The Pangeo-Fish Initiative"; "2024-03-12 15:34:59.645366+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11185948"; ; "2024-05-13 14:46:37.545543+00:00"; "2024-08-12 19:50:27.882827+00:00"; "Project Management Plan for the Global fish Tracking System Use Case on the DestinE Platform."; ; "Deliverable 5.1 - Project Management Plan for GFTS Use Case Application"; "2024-05-13 14:46:37.545543+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186084"; ; "2024-05-13 14:52:05.526290+00:00"; "2024-08-12 19:50:21.743081+00:00"; "Deliverable 5.2 - Use Case Descriptor for the Global fish Tracking System Use Case on the DestinE Platform."; ; "Deliverable 5.2 - Use Case Descriptor for GFTS Use Case Application"; "2024-05-13 14:52:05.526290+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186123"; ; "2024-05-13 14:53:36.574750+00:00"; "2024-08-12 19:50:20.705135+00:00"; "The Gobal Fish track system Use case Application on the DestinE Platform"; ; "Deliverable 5.3 - GFTS Use case Application"; "2024-05-13 14:53:36.574750+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186179"; ; "2024-05-13 14:54:51.494324+00:00"; "2024-08-12 19:50:17.564291+00:00"; "Deliverable 5.5 corresponding to the Global Fish tracking System Use Case Promotion Package"; ; "Deliverable 5.5 - GFTS Use Case Promotion Package"; "2024-05-13 14:54:51.494324+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186191"; ; "2024-05-13 14:56:18.168828+00:00"; "2024-08-12 19:50:26.999845+00:00"; "This report corresponds to the Software Reuse File for the GFTS DestinE Platform Use Case. New version will be uploaded regularly."; ; "Software Reuse File for the GFTS DestinE Platform Use Case"; "2024-05-13 14:56:18.168828+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186227"; ; "2024-05-13 14:57:17.755650+00:00"; "2024-08-12 19:50:15.236431+00:00"; "The Software Release Plan for the Global Fish Tracking System DestinE Use Case."; ; "GFTS Software Release Plan"; "2024-05-13 14:57:17.755650+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186257"; ; "2024-05-13 14:58:42.259068+00:00"; "2024-08-12 19:50:18.592163+00:00"; "The Software Requirement Specifications for the Global fish Tracking System DestinE Use Case."; ; "GFTS Software Requirement Specifications"; "2024-05-13 14:58:42.259068+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186288"; ; "2024-05-13 15:02:41.488702+00:00"; "2024-08-12 19:50:12.780989+00:00"; "The Software Verification and Validation Plan for the Global fish Tracking System DestinE Use Case."; ; "GFTS Software Verification and Validation Plan"; "2024-05-13 15:02:41.488702+00:00" . a , , ; ; "https://doi.org/10.5281/zenodo.11186318"; ; "2024-05-13 15:04:39.257557+00:00"; "2024-08-12 19:50:19.449409+00:00"; "The Software Verification and Validation Report from the Global Fish Tracking System DestinE Use Case."; ; "GFTS Software Verification and Validation Report"; "2024-05-13 15:04:39.257557+00:00" . a , , ; ; "https://gfts.minrk.net/"; ; "2024-04-03 08:56:53.930425+00:00"; "2024-08-12 19:50:18.317893+00:00"; "Link to the Pangeo JupyterHub we are using for developing Pangeo Fish. 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; "2025-05-24 11:40:44.799549+00:00"; "2025-05-24 13:39:08.432963+00:00"; ; "workflows/f1ada1d68e850ab0.abstract"; ; "2025-05-24 11:40:44.799549+00:00" . a , ; ; "2"^^xsd:integer; "https://api.rohub.org/api/resources/c7f1c1fa-caa1-4d3f-8b81-9adf18090c74/download/"; ; "2025-05-24 11:40:44.793765+00:00"; "2025-05-24 13:39:22.602451+00:00"; "implicit collection jobs properties"; "application/json"; ; "implicit_collection_jobs_attrs.txt"; "2025-05-24 11:40:44.793765+00:00"; "2.0" . a , ; ; "2"^^xsd:integer; "https://api.rohub.org/api/resources/c891c902-f3d5-4ea8-b682-8553ea7ab434/download/"; ; "2025-05-24 11:40:44.789539+00:00"; "2025-05-24 13:39:14.036041+00:00"; "libraries properties"; "application/json"; ; "libraries_attrs.txt"; "2025-05-24 11:40:44.789539+00:00"; "2.0" . a , ; ; "2"^^xsd:integer; "https://api.rohub.org/api/resources/de997230-e253-4ea1-8ef3-367cad87f52e/download/"; ; "2025-05-24 11:40:44.791155+00:00"; "2025-05-24 13:39:23.412146+00:00"; "collections properties"; "application/json"; ; "collections_attrs.txt"; "2025-05-24 11:40:44.791155+00:00"; "2.0" . a , ; ; "2"^^xsd:integer; "https://api.rohub.org/api/resources/ee371b29-df2f-4f66-b301-1a25f5937d96/download/"; ; "2025-05-24 11:40:44.791921+00:00"; "2025-05-24 13:39:20.927491+00:00"; "text/plain"; ; "implicit_dataset_conversions.txt"; "2025-05-24 11:40:44.791921+00:00" . a , , , ; ; "3647"^^xsd:integer; "https://api.rohub.org/api/resources/ef444f9a-3d41-4f8a-8a62-b792e981a17a/download/"; ; "2025-05-24 11:40:44.798061+00:00"; "2025-05-24 13:39:20.496823+00:00"; ; "workflows/f1ada1d68e850ab0"; ; "2025-05-24 11:40:44.798061+00:00" . a ; dct:conformsTo ; . a ; "job"; "3.710862002319289"; "9.6" . a ; "other earth sciences"; "28.140164323698208"; "0.8604831099510193" . a ; "earth sciences"; "15.5005337397516"; "0.473982572555542" . a ; "galaxy"; "6.500646830530402"; "20.1" . a ; "info"; "4.020100502512563"; "10.4" . a ; "server"; "2.6843467011642956"; "8.3" . a ; "rerun"; "6.841901816776189"; "17.7" . a ; "IT-computer sciences"; "Science and technology/Technology and engineering/IT-computer sciences" . a ; "oceanography"; "14.137058879162895"; "0.43228960037231445" . a ; "designation ofilename"; "3.7470725995316156"; "12.8" . a ; "metadata"; "6.015523932729626"; "18.6" . a ; "ScienceLive"; "2.8604561267877853"; "7.4" . a ; "geology"; "42.222243057387296"; "1.291091501712799" . a ; "May-24-2025 11:18:13" . a ; "life sciences (general)"; "48.48964280977599"; "0.691840410232544" . a ; "atmospheric sciences"; "15.5005337397516"; "0.473982572555542" . a ; "template"; "3.285659064553537"; "8.5" . a ; "Hardware"; "Economy, business and finance/Economic sector/Computing and information technology/Hardware" . a ; "param"; "3.33117723156533"; "10.3" . a ; "database"; "39.473684210526315"; "19.5" . a ; "computer programming"; "5.870445344129555"; "2.9" . a ; """To rerun this workflow: 1."""; "2.6981450252951094"; "9.6" . a ; "earth sciences"; "42.222243057387296"; "1.291091501712799" . a ; "space sciences"; "3.5516765615937134"; "0.05067460238933563" . a ; "life sciences"; "48.48964280977599"; "0.691840410232544" . a ; "Capital punishment"; "Crime, law and justice/Law enforcement/Punishment (criminal)/Capital punishment" . a ; "My ScienceLive Stripes"; "28.015222482435597"; "95.7" . a ; "May-24-2025 11:15:49" . a ; "name"; "4.915912031047865"; "15.2" . a ; "dataset"; "8.796895213454075"; "27.2" . a ; "[{\"command_line\": \"python '/opt/galaxy/server/lib/galaxy/tools/data_fetch.py' --galaxy-root '/opt/galaxy/server' --datatypes-registry '/data/jwd05e/main/083/891/83891872/registry.xml' --request-version '1' --request '/data/jwd05e/main/083/891/83891872/configs/tmp9ijk_gw5'\", \"create_time\": \"2025-05-24T11:15:37.910670\", \"encoded_id\": \"9fa5573dd746a59a5204daf0450df025\", \"exit_code\": 0, \"galaxy_version\": \"24.2\", \"implicit_output_dataset_collection_mapping\": {}, \"info\": null, \"input_dataset_collection_element_mapping\": {}, \"input_dataset_collection_mapping\": {}, \"input_dataset_mapping\": {}, \"job_messages\": [], \"job_stderr\": \"\", \"job_stdout\": \"\", \"model_class\": \"Job\", \"output_dataset_collection_mapping\": {}, \"output_dataset_mapping\": {\"output0\": [\"31e7840b5aedca433fb349714141a239\"]}, \"params\": {\"file_count\": \"1\", \"files\": [{\"__index__\": 0, \"file_data\": \"/data/misc07/tus_upload/main/4c0201ed-0ac2-4bc9-bb7b-ee629ef6738b\"}], \"paramfile\": null, \"request_json\": \"{\\\"targets\\\": [{\\\"destination\\\": {\\\"type\\\": \\\"hdas\\\"}, \\\"elements\\\": [{\\\"name\\\": \\\"ts_cities.csv\\\", \\\"dbkey\\\": \\\"?\\\", \\\"ext\\\": \\\"auto\\\", \\\"space_to_tab\\\": false, \\\"to_posix_lines\\\": true, \\\"src\\\": \\\"path\\\", \\\"hashes\\\": [], \\\"in_place\\\": false, \\\"purge_source\\\": true, \\\"path\\\": \\\"/data/misc07/tus_upload/main/4c0201ed-0ac2-4bc9-bb7b-ee629ef6738b\\\", \\\"object_id\\\": 198375399}]}], \\\"auto_decompress\\\": false, \\\"check_content\\\": true}\", \"request_version\": \"1\"}, \"state\": \"ok\", \"tool_id\": \"__DATA_FETCH__\", \"tool_stderr\": \"\", \"tool_stdout\": \"\", \"tool_version\": \"0.1.0\", \"traceback\": null, \"update_time\": \"2025-05-24T11:16:35.950780\"}, {\"command_line\": \"python3 '/opt/galaxy/shed_tools/toolshed.g2.bx.psu.edu/repos/climate/climate_stripes/abdc27e01dca/climate_stripes/climate_stripes.py' '/data/dnb11/galaxy_db/files/b/3/c/dataset_b3cb61d2-2f69-478a-8d99-b015043391d4.dat' 'tg_anomalies_freiburg' --cmap 'RdBu_r' --title 'My ScienceLive Stripes' --output image.png\", \"create_time\": \"2025-05-24T11:15:49.359197\", \"encoded_id\": \"9fa5573dd746a59acc6f0e1eb8574ba7\", \"exit_code\": 0, \"galaxy_version\": \"24.2\", \"implicit_output_dataset_collection_mapping\": {}, \"info\": null, \"input_dataset_collection_element_mapping\": {}, \"input_dataset_collection_mapping\": {}, \"input_dataset_mapping\": {\"ifilename\": [\"31e7840b5aedca433fb349714141a239\"]}, \"job_messages\": [], \"job_stderr\": \"\", \"job_stdout\": \"\", \"model_class\": \"Job\", \"output_dataset_collection_mapping\": {}, \"output_dataset_mapping\": {\"ofilename\": [\"31e7840b5aedca43c0a4f330c3d24460\"]}, \"params\": {\"__input_ext\": \"auto\", \"__workflow_invocation_uuid__\": \"6db993da389011f08d47001e67d2ec02\", \"adv\": {\"colormap\": \"RdBu_r\", \"format_date\": \"\", \"format_plot\": \"\", \"nxsplit\": null, \"xname\": \"\"}, \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"dbkey\": \"?\", \"ifilename\": {\"values\": [{\"id\": \"31e7840b5aedca433fb349714141a239\", \"src\": \"hda\"}]}, \"title\": \"My ScienceLive Stripes\", \"variable\": \"tg_anomalies_freiburg\"}, \"state\": \"ok\", \"tool_id\": \"toolshed.g2.bx.psu.edu/repos/climate/climate_stripes/climate_stripes/1.0.2\", \"tool_stderr\": \"\", \"tool_stdout\": \"\", \"tool_version\": \"1.0.2\", \"traceback\": null, \"update_time\": \"2025-05-24T11:18:13.429890\""; "28.10567734682406"; "100.0" . a ; "b3cb61d2-2f69-478a-8d99-b015043391d4"; "2.8604561267877853"; "7.4" . a ; "software"; "7.08502024291498"; "3.5" . a ; "climate"; "3.4016235021260153"; "8.8" . a ; "datum"; "3.0150753768844223"; "7.8" . a ; "jwd05e"; "2.7831465017394668"; "7.2" . a ; "name stripes.png"; "4.947306791569086"; "16.9" . a ; "workflow input"; "2.781030444964871"; "9.5" . a ; "data"; "9.184993531694696"; "28.4" . a ; "metadata"; "3.8268264398917666"; "9.9" . a ; "workflow output"; "2.839578454332552"; "9.7" . a ; "WorkflowRequestInputParameter"; "4.290684190181678"; "11.1" . a ; "earth sciences"; "14.137058879162895"; "0.43228960037231445" . a ; "May-24-2025 11:15:41" . a ; "output"; "5.450328565906456"; "14.1" . a ; "earth sciences"; "28.140164323698208"; "0.8604831099510193" . a ; "adverb"; "2.9754204398447603"; "9.2" . a ; "May-24-2025 11:16:35" . a ; "climate"; "2.652005174644243"; "8.2" . a ; "IT-computer sciences"; "Science and technology/Technology and engineering/IT-computer sciences" . a ; "galaxy"; "5.914186316196367"; "15.3" . a ; "ScienceLive stripe"; "4.156908665105386"; "14.2" . a ; "input"; "3.0150753768844223"; "7.8" . a ; "information"; "4.406648627754156"; "11.4" . a ; """# Galaxy Workflow Rerun Information **Workflow:** Climate Stripes **Execution Status:** scheduled **Executed:** 2025-05-24 11:15:41.585048"""; "10.286677908937605"; "36.6" . a ; "dataset"; "9.277155005798223"; "24.0" . a ; "computer programming and software"; "47.9586806286303"; "0.684264749288559" . a ; "WorkflowInvocationStep"; "3.092385001932741"; "8.0" . a ; "galaxy workflow rerun information"; "8.899297423887587"; "30.4" . a ; "WorkflowInvocationOutputDatasetAssociation dataset"; "4.976580796252927"; "17.0" . a ; "rerun template"; "3.0444964871194378"; "10.4" . a ; "input"; "3.719275549805951"; "11.5" . a ; "hda title"; "1.2295081967213113"; "4.2" . a ; "delimiter t"; "4.332552693208431"; "14.8" . a ; "workflow"; "6.841901816776189"; "17.7" . a ; "fact"; "2.8137128072445017"; "8.7" . a ; "space sciences (general)"; "3.5516765615937134"; "0.05067460238933563" . a ; "[{\"model_class\": \"WorkflowInvocation\", \"state\": \"scheduled\", \"create_time\": \"2025-05-24 11:15:41.585048\", \"update_time\": \"2025-05-24 11:15:49.407239\", \"steps\": [{\"model_class\": \"WorkflowInvocationStep\", \"state\": \"scheduled\", \"create_time\": \"2025-05-24 11:15:49.372141\", \"update_time\": \"2025-05-24 11:15:49.372142\", \"order_index\": 0, \"action\": null, \"outputs\": [{\"output_name\": \"output\", \"dataset\": {\"model_class\": \"HistoryDatasetAssociation\", \"encoded_id\": \"31e7840b5aedca433fb349714141a239\"}}], \"output_collections\": []}, {\"model_class\": \"WorkflowInvocationStep\", \"state\": \"scheduled\", \"create_time\": \"2025-05-24 11:15:49.372143\", \"update_time\": \"2025-05-24 11:18:13.433603\", \"order_index\": 1, \"action\": null, \"job\": {\"model_class\": \"Job\", \"encoded_id\": \"9fa5573dd746a59acc6f0e1eb8574ba7\"}, \"outputs\": [{\"output_name\": \"ofilename\", \"dataset\": {\"model_class\": \"HistoryDatasetAssociation\", \"encoded_id\": \"31e7840b5aedca43c0a4f330c3d24460\"}}, {\"output_name\": \"ofilename\", \"dataset\": {\"model_class\": \"HistoryDatasetAssociation\", \"encoded_id\": \"31e7840b5aedca43c0a4f330c3d24460\"}}], \"output_collections\": []}], \"input_parameters\": [{\"model_class\": \"WorkflowRequestInputParameter\", \"name\": \"5453637\", \"value\": \"{\\\"title\\\": \\\"My ScienceLive Stripes\\\", \\\"variable\\\": \\\"tg_anomalies_freiburg\\\", \\\"adv|colormap\\\": \\\"RdBu_r\\\"}\", \"type\": \"step\"}, {\"model_class\": \"WorkflowRequestInputParameter\", \"name\": \"copy_inputs_to_history\", \"value\": \"false\", \"type\": \"meta\"}, {\"model_class\": \"WorkflowRequestInputParameter\", \"name\": \"use_cached_job\", \"value\": \"false\", \"type\": \"meta\"}], \"step_states\": [{\"model_class\": \"WorkflowRequestStepState\", \"value\": {\"__page__\": 0, \"__rerun_remap_job_id__\": null, \"input\": \"{\\\"__class__\\\": \\\"NoReplacement\\\"}\"}, \"order_index\": 0}, {\"model_class\": \"WorkflowRequestStepState\", \"value\": {\"__STEP_META_STATE__\": \"{\\\"__POST_JOB_ACTIONS__\\\": {}}\", \"__page__\": 0, \"__rerun_remap_job_id__\": null, \"adv\": \"{\\\"colormap\\\": \\\"RdBu_r\\\", \\\"format_date\\\": \\\"\\\", \\\"format_plot\\\": \\\"\\\", \\\"nxsplit\\\": null, \\\"xname\\\": \\\"\\\"}\", \"ifilename\": \"{\\\"__class__\\\": \\\"ConnectedValue\\\"}\", \"title\": \"\\\"My ScienceLive Stripes\\\"\", \"variable\": \"\\\"tg_anomalies_freiburg\\\"\"}, \"order_index\": 1}], \"input_step_parameters\": [], \"input_datasets\": [{\"model_class\": \"WorkflowRequestToInputDatasetAssociation\", \"name\": null, \"dataset\": {\"model_class\": \"HistoryDatasetAssociation\", \"encoded_id\": \"31e7840b5aedca433fb349714141a239\"}, \"order_index\": 0}], \"input_dataset_collections\": [], \"output_dataset_collections\": [], \"output_datasets\": [{\"model_class\": \"WorkflowInvocationOutputDatasetAssociation\", \"dataset\": {\"model_class\": \"HistoryDatasetAssociation\", \"encoded_id\": \"31e7840b5aedca43c0a4f330c3d24460\"}, \"order_index\": 1, \"workflow_output\": {\"model_class\": \"WorkflowOutput\", \"output_name\": \"ofilename\", \"label\": \"stripes.png\", \"uuid\": \"8413b0d2-5eb1-419f-a1ed-a329fcf7366b\"}}], \"output_values\": [], \"encoded_id\": \"37738047cb7b8ee8\", \"workflow\": \"f1ada1d68e850ab0\""; 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