Ziroli Plutschow RSA MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEApbztY8l4lWqVF8L/djJ1knoc7Nm5kVHT9NqSe0fXO9Hel3DRO2IyxJYVEvThhllBuHNtZK32ww23AlglArokhxPCSBPKvVgQS6r46khF2D85tnd5htaBq+bfjMqL+LDlQh3LdBpAqrLmsmfsPkU65CCxSGufBs2v39p41z5FkRXE1JKJ/UZe+1OUq+CibjOfo1g1Nz6HO0fZML7GnQBj5X9lvU0llmDk/sqdNMxAJDSQh2/Zh0kz7+Dm7vJOx3mNEXU4FuzVzKBYwTotvEcJod7Vot1fPOJXPGoNDVNKMQffCala9o4pqT739LS7R7ZFVMjzPkLUxYCjnEgOZI5t6wIDAQAB RSA MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAvsAJkaWPEoV2AfCEcz4YKiPYnz7hIKWaU64/JLJ4IyzvCnL3JEbW3Q2TzZM7fSR4GeWhs+u/2rpsxurjhDN8rF2NbKU5zkf8+//9lCqX1goC+F+EH7gx+vv14lB5XCYtVMUhHiviARnvAI2qK3YoKLaw27uBfrwQ08St2BQ4bbu3qW4uq2Af6ENu0tcMRXykoioP9eii+Cog2eMBJzjHRgObZm0AuHQ9VEl7HWMZIVyB15vjVjbQTfqg8HPYsArCzXOzjY97kj0diMzp6/1U6ZZAxQ7D+2jwVWGC/mQUzARzIPNeZ5299+/+xHMY7vufj5B2PAvO18BUz0Pw4NX9CQIDAQAB RSA MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQCRxqE9AJd10geyZVSAzaTl5ly3X0EBV59zn6ot8ZdcB77wkUqI44Mw5IYeG/isXoAZqq5yXWZjMOk0Uv94jqu31KnXlv2cazidBqJeO9GD0UAfX6hU3mpbC6Hj3MFNDYEDMX/yAC55oOr78B93NqhdiTieTMKzNe/kHyVhCIPjgQIDAQAB This query returns all RO-Crate nanopubs. Including the old and new type. Get all RO-Crate nanopubs prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> prefix dct: <http://purl.org/dc/terms/> prefix np: <http://www.nanopub.org/nschema#> prefix npa: <http://purl.org/nanopub/admin/> prefix npx: <http://purl.org/nanopub/x/> prefix kpxl: <https://w3id.org/kpxl/gen/terms/> # find all ro-crates, with old and new nanopub type select distinct ?rocrate ?date ?np where { graph npa:graph { {?np npx:hasNanopubType kpxl:RoCrateNanopub .} union {?np npx:hasNanopubType npx:RoCrateNanopub .} ?np npa:hasValidSignatureForPublicKeyHash ?pubkeyhash . filter not exists { ?npx npx:invalidates ?np ; npa:hasValidSignatureForPublicKey ?pubkeyhash . } ?np dct:created ?date . ?np npx:introduces ?rocrate . ?np npx:signedBy ?agent_iri . } } order by desc(?date) This query returns all RO-Crate nanopubs. Get all RO-Crate Nanopubs (new type) prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> prefix dct: <http://purl.org/dc/terms/> prefix np: <http://www.nanopub.org/nschema#> prefix npa: <http://purl.org/nanopub/admin/> prefix npx: <http://purl.org/nanopub/x/> prefix kpxl: <https://w3id.org/kpxl/gen/terms/> select distinct ?rocrate ?date (?__agent_iri as ?agent) ?np (?__pubkeyhash as ?pubkey) where { graph npa:graph { ?np npx:hasNanopubType kpxl:RoCrateNanopub . ?np npa:hasValidSignatureForPublicKeyHash ?__pubkeyhash . filter not exists { ?npx npx:invalidates ?np ; npa:hasValidSignatureForPublicKey ?__pubkeyhash . } ?np dct:created ?date . ?np npx:introduces ?rocrate . ?np npx:signedBy ?__agent_iri . } } order by desc(?date) This query returns all RO-Crate nanopubs. Get all RO-Crate Nanopubs (new type) prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> prefix dct: <http://purl.org/dc/terms/> prefix np: <http://www.nanopub.org/nschema#> prefix npa: <http://purl.org/nanopub/admin/> prefix npx: <http://purl.org/nanopub/x/> prefix kpxl: <https://w3id.org/kpxl/gen/terms/> select distinct ?rocrate ?date (?__agent_iri as ?agent) ?np (?__pubkeyhash as ?pubkey) where { graph npa:graph { ?np npx:hasNanopubType kpxl:RoCrateNanopub . ?np npa:hasValidSignatureForPublicKeyHash ?__pubkeyhash . filter not exists { ?npx npx:invalidates ?np ; npa:hasValidSignatureForPublicKey ?__pubkeyhash . } ?np dct:created ?date . ?np npx:introduces ?rocrate . ?np npx:signedBy ?__agent_iri . } } order by desc(?date) This query returns all RO-Crate nanopubs. Get all RO-Crate Nanopubs (old type) prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>prefix dct: <http://purl.org/dc/terms/>prefix np: <http://www.nanopub.org/nschema#>prefix npa: <http://purl.org/nanopub/admin/>prefix npx: <http://purl.org/nanopub/x/>select distinct ?rocrate ?date ?np where { graph npa:graph { ?np npx:hasNanopubType npx:RoCrateNanopub . filter not exists { ?npx npx:invalidates ?np } ?np dct:created ?date . ?np npx:introduces ?rocrate . }}order by desc(?date) This query returns all RO-Crate nanopubs. Get all RO-Crate Nanopubs (old type) prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>prefix dct: <http://purl.org/dc/terms/>prefix np: <http://www.nanopub.org/nschema#>prefix npa: <http://purl.org/nanopub/admin/>prefix npx: <http://purl.org/nanopub/x/>select distinct ?rocrate ?date ?np where { graph npa:graph { ?np npx:hasNanopubType npx:RoCrateNanopub . filter not exists { ?npx npx:invalidates ?np } ?np dct:created ?date . ?np npx:introduces ?rocrate . }}order by desc(?date) This query returns all RO-Crate nanopubs. Get all RO-Crate Nanopubs (old type) prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>prefix dct: <http://purl.org/dc/terms/>prefix np: <http://www.nanopub.org/nschema#>prefix npa: <http://purl.org/nanopub/admin/>prefix npx: <http://purl.org/nanopub/x/>select distinct ?rocrate ?date ?np where { graph npa:graph { ?np npx:hasNanopubType npx:RoCrateNanopub . filter not exists { ?npx npx:invalidates ?np } ?np dct:created ?date . ?np npx:introduces ?rocrate . }}order by desc(?date) And the text got updated again This is just a playground text. This query returns all RO-Crate nanopubs. Get all RO-Crate Nanopubs prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> prefix dct: <http://purl.org/dc/terms/> prefix np: <http://www.nanopub.org/nschema#> prefix npa: <http://purl.org/nanopub/admin/> prefix npx: <http://purl.org/nanopub/x/> select distinct ?rocrate ?date ?np where { graph npa:graph { ?np npx:hasNanopubType npx:RoCrateNanopub . filter not exists { ?npx npx:invalidates ?np } ?np dct:created ?date . ?np npx:introduces ?rocrate . } } order by desc(?date) This query returns all RO-Crate nanopubs. Get all RO-Crate nanopubs again prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> prefix dct: <http://purl.org/dc/terms/> prefix np: <http://www.nanopub.org/nschema#> prefix npa: <http://purl.org/nanopub/admin/> prefix npx: <http://purl.org/nanopub/x/> select distinct ?rocrate ?date ?np where { graph npa:graph { ?np npx:hasNanopubType npx:RoCrateNanopub . filter not exists { ?npx npx:invalidates ?np } ?np dct:created ?date . ?np npx:introduces ?rocrate . } } order by desc(?date) RO-Crate Bot RSA MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAxszSDYX5tuCSkP7UiCtftYPFNQVTjgNu0I5fwdML2DLRDlp0xzmsQXRk8oHuvwGvG1aMjj6cpUqO+0rz2Sg/wvHOgUpkRH8VJXvmlkhafMLCMtUtk5JIx7e+fkzCby+fnmD7kMkGLrT+OaExWwEDmNlCAt0TPKcHSdwsjso2isXjtAsGevyCMke8ufnFYpjs746JES1eNzVnHnn2Kp/lqcm60GM+J8dLgRZp7fX0anW098xhKym6+xXFzqeju0vYRIHBPerv+r7skWxwk+a7Sd8msqVeYEv6NTqnyWvyWb6Yh8cvj04N6qm/T6C5FUPLQhzSaQgMVMU6yLqjPuu9DwIDAQAB RSA MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEA4pPaESKwmC6l37P86K6TNLq6yeQtc7m9CvcqauLs/1FC0viHvQnFBgxj0a+loPDv/Egwe6OqFpa0iW9Ypnyz9YPoh+pxbRXonbuMOb+8Ry9hXZ+TEKfWjhjVDGEaClwfRwglh2HI/xfV4CD9AgvDOEoZQiyta8a90PYwJ3G6e70oCHTn61+OWTkI9KRYHOYgg3btdy2Z7q/30PTFawb2ZT5aIfIJYobUYv2a7yhtcqWCHZeKv0bxGnRjTFNx1rscBMlLJSzvRtpQc1cCRVEPFZHo1adaXCI9tGvn4cxeNQ96y8dxkN1XhpaJairde+23MDzf42Oe97KG2HYzKiyVnQIDAQAB Applied sciences Biology 0 https://api.rohub.org/api/ros/ad39ad6e-a644-46fa-a189-4dc66389314a/crate/download/ 2024-11-07 08:17:22.466300+00:00 2025-10-16 12:17:23.001159+00:00 2024-11-07 08:17:22.466300+00:00 As anyone who has spent time with cats knows, our feline companions are mysterious—much more so than those other furry family members. Here John Bradshaw, author of Cat Sense (Basic Books, 2013), fields a selection of questions submitted by Scientific American editors and Twitter followers about the cat’s many quirks. Bradshaw is a visiting fellow at the University of Bristol School of Veterinary Sciences in England, where he studies the behavior and welfare of cats and dogs, as well as their interactions with people. application/ld+json https://w3id.org/ro-id/ad39ad6e-a644-46fa-a189-4dc66389314a Cats Pets The Inner Life of Cats MANUAL Gniewek, Aleks. "The Inner Life of Cats." ROHub. Nov 07 ,2024. https://w3id.org/ro-id/ad39ad6e-a644-46fa-a189-4dc66389314a. life sciences 100.0 0.9659337401390076 author of Cat sense 13.114754098360656 7.2 University Education/School/Higher education/University disciple 9.354413702239789 7.1 Bradshaw is a visiting fellow at the University of Bristol School of Veterinary Sciences in England, where he studies the behavior and welfare of cats and dogs, as well as their interactions with people. 30.717488789237674 27.4 England Çat dog 9.565217391304348 5.5 environmental science and management 100.0 0.993445634841919 Twitter 10.803689064558627 8.2 veterinary medicine 8.95915678524374 6.8 cat 21.217391304347824 12.2 Twitter follower 18.0327868852459 9.9 choose 5.928853754940711 4.5 editor 5.665349143610013 4.3 life sciences (general) 100.0 0.9659337401390076 follower 10.782608695652174 6.2 relative 4.743083003952568 3.6 zoology 100.0 6.2 As anyone who has spent time with cats knows, our feline companions are mysterious—much more so than those other furry family members. 37.44394618834081 33.4 Twitter 12.695652173913043 7.3 veterinary science 10.26086956521739 5.9 dog 8.300395256916996 6.3 behavior 4.743083003952568 3.6 welfare of cat 33.697632058287795 18.5 University of Bristol School of veterinary sciences 18.214936247723134 10.0 welfare 5.270092226613965 4.0 Science and technology Science and technology Twitter selection of question 16.939890710382517 9.3 Veterinarian science Science and technology/Biomedical science/Veterinarian science John Bradshaw 26.782608695652176 15.4 environmental sciences 100.0 0.993445634841919 quirk 5.006587615283267 3.8 Çat 5.533596837944664 4.2 cat 18.577075098814227 14.1 England 7.1146245059288535 5.4 University of Bristol School 8.695652173913043 5.0 Animal Human interest/Animal Here John Bradshaw, author of Cat Sense (Basic Books, 2013), fields a selection of questions submitted by Scientific American editors and Twitter followers about the cat’s many quirks. 31.83856502242153 28.4 Aleks Gniewek Applied sciences Social sciences xyz 0 https://api.rohub.org/api/ros/5930c9e6-8f23-4c8c-9b1b-84d55deaaf00/crate/download/ 2024-11-14 08:02:26.064775+00:00 2025-10-16 12:17:13.898108+00:00 2024-11-14 08:02:26.064775+00:00 Metadata-enriched Polish Novel Corpus from the 19th and 20th centuries The corpus consists of 1,000 novels originally written in Polish and initially published as books between 1864 and 1939, with the plot timeframe set after 1815. The current version is v1.0.1. Following Linked Open Data (LOD) standards, we do not publish the corpus texts in .txt format. Instead, the entire corpus is accessible through a knowledge graph in Turtle (.ttl) format, with each text being linked separately. The repository contains code to download all corpus texts independently. An explanation of the code can be found in the Data section. application/ld+json https://w3id.org/ro-id/5930c9e6-8f23-4c8c-9b1b-84d55deaaf00 Corpora LinkedOpenData LiteraryStudies Ontology Annotation Collection Korpus 19-20MetaPNC MANUAL Hubar-Kołodziejczyk, Patryk. "Korpus 19-20MetaPNC." ROHub. Nov 14 ,2024. https://w3id.org/ro-id/5930c9e6-8f23-4c8c-9b1b-84d55deaaf00. raw data metadata data biblio 86599 https://api.rohub.org/api/resources/86143851-8706-4b88-b70e-41c184211080/download/ 2024-11-14 08:15:28.902820+00:00 2024-11-14 08:15:29.775352+00:00 image/jpeg TCO_ontology.jpg 2024-11-14 08:15:28.902820+00:00 43938 https://api.rohub.org/api/resources/961c69a7-79d1-49ac-8ad2-d5a2e7801d65/download/ 2024-11-14 08:15:39.635599+00:00 2024-11-14 08:15:40.563302+00:00 image/png Meta_tree.png 2024-11-14 08:15:39.635599+00:00 text 11.520737327188941 7.5 corpus consist 20.66905615292712 17.3 model 3.4285714285714284 3.0 consist 4.457142857142857 3.9 geophysics 100.0 0.3627100884914398 text 9.6 8.4 computer code 5.371428571428571 4.7 literature 100.0 10.3 computer operations and hardware 100.0 0.9055352807044983 Linked Open Datum 9.216589861751153 6.0 Book industry Economy, business and finance/Economic sector/Media/Book industry after 1815 corpus 35.63748079877112 23.2 mathematical and computer sciences 100.0 0.9055352807044983 metadata 9.37019969278034 6.1 v1.0.1 8.141321044546851 5.3 corpus 27.2 23.8 novel 4.0 3.5 Polish 3.7714285714285714 3.3 Fiction Arts, culture and entertainment/Arts and entertainment/Literature/Fiction graph 4.457142857142857 3.9 code 6.912442396313365 4.5 earth sciences 100.0 0.3627100884914398 The repository contains code to download all corpus texts independently. 27.053140096618357 16.8 Instead, the entire corpus is accessible through a knowledge graph in Turtle (.ttl) format, with each text being linked separately. 30.756843800322063 19.1 between 1864 and 1939 time frame 4.228571428571429 3.7 Following Linked Open Data (LOD) standards, we do not publish the corpus texts in .txt format. 42.19001610305958 26.2 Literature Arts, culture and entertainment/Arts and entertainment/Literature format 19.201228878648234 12.5 corpus texts in.txt format 44.32497013142174 37.1 format 22.285714285714285 19.5 plot timeframe 5.017921146953404 4.2 metadata 7.085714285714285 6.2 repository 4.114285714285714 3.6 novel corpus 24.731182795698924 20.7 knowledge graph 5.256869772998805 4.4 Patryk Hubar-Kołodziejczyk Environmental research https://doi.org/10.5281/zenodo.14279111 2024-12-04 23:00:28.915134+00:00 2024-12-04 23:00:30.048350+00:00 Contains outputs, (results), generated in the Jupyter notebook of Livestock detection using DeepForest Outputs 2024-12-04 23:00:28.915134+00:00 https://doi.org/10.7910/DVN/N7GJYU 2024-12-04 23:00:24.659570+00:00 2024-12-04 23:00:25.667439+00:00 Contains input Input dataset for the fine-tuned model used in the Jupyter notebook of Livestock detection using DeepForest Input Input dataset for the fine-tuned model 2024-12-04 23:00:24.659570+00:00 https://doi.org/https://doi.org/10.1111/2041-210X.13472 2024-12-04 23:00:33.471709+00:00 2024-12-04 23:00:34.525430+00:00 Related publication of the modelling presented in the Jupyter notebook Deepforest: a python package for rgb deep learning tree crown delineation 2024-12-04 23:00:33.471709+00:00 https://edsbook.org/notebooks/gallery/95199651-9e81-4cae-a3a7-66398a9a5f62/notebook.html 2024-12-04 23:00:46.367365+00:00 2024-12-04 23:00:47.573187+00:00 Rendered version of the Jupyter Notebook hosted by the Environmental Data Science Book text/html Online rendered version of the Jupyter notebook 2024-12-04 23:00:46.367365+00:00 https://github.com/eds-book-gallery/95199651-9e81-4cae-a3a7-66398a9a5f62/blob/main/notebook.ipynb 2024-12-04 23:00:20.603543+00:00 2024-12-04 23:00:21.556504+00:00 Jupyter Notebook hosted by the Environmental Data Science Book Jupyter notebook 2024-12-04 23:00:20.603543+00:00 https://github.com/eds-book-gallery/95199651-9e81-4cae-a3a7-66398a9a5f62/tree/main/.binder/environment.yml 2024-12-04 23:00:41.963542+00:00 2024-12-04 23:00:43.056070+00:00 Conda environment when user want to have the same libraries installed without concerns of package versions Conda environment 2024-12-04 23:00:41.963542+00:00 https://github.com/eds-book-gallery/95199651-9e81-4cae-a3a7-66398a9a5f62/tree/main/.lock/conda-lock.yml 2024-12-04 23:00:37.727861+00:00 2024-12-04 23:00:38.784747+00:00 Lock conda file of the Jupyter notebook hosted by the Environmental Data Science Book Lock conda file 2024-12-04 23:00:37.727861+00:00 University of Florida ethanwhite@ufl.edu Ethan P. White 0000-0001-6728-7745 The Alan Turing Institute lvanzeeland@turing.ac.uk Louisa Van Zeeland 0009-0005-0392-4377 2025-05-27 16:35:09.245985+00:00 0 https://api.rohub.org/api/ros/7ad44bec-6784-437f-b5f3-2199b43a5303/crate/download/ 2024-12-04 22:59:05.987316+00:00 2025-10-16 12:17:04.846237+00:00 2024-12-04 22:59:05.987316+00:00 The research object refers to the Livestock detection using DeepForest notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/7ad44bec-6784-437f-b5f3-2199b43a5303 Livestock detection using DeepForest (Jupyter Notebook) published in the Environmental Data Science book MANUAL Cameron Appel, Ethan P. White, and Louisa Van Zeeland. "Livestock detection using DeepForest (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 04 ,2024. https://w3id.org/ro-id/7ad44bec-6784-437f-b5f3-2199b43a5303. output tool input biblio 457238 https://api.rohub.org/api/resources/832ec27f-3faf-4051-9a42-dfa6d421a6ed/download/ 2024-12-04 23:00:16.094540+00:00 2024-12-04 23:00:17.222084+00:00 image/png Image showing an example of the finetuned model predictions to detect livestock 2024-12-04 23:00:16.094540+00:00 aim 21.489001692047378 12.7 DeepForest notebook 34.64249748237664 34.4 research 13.348164627363737 12.0 Language Arts, culture and entertainment/Culture/Language Book industry Economy, business and finance/Economic sector/Media/Book industry notebook 13.125695216907674 11.8 object 14.571746384872078 13.1 Environmental Data Science book 15.609264853977846 15.5 research object 34.038267875125875 33.8 DeepForest 17.797552836484982 16.0 publishing 100.0 6.9 Livestock detection using DeepForest (Jupyter Notebook) published in the Environmental Data Science book. 39.23923923923924 39.2 Livestock detection 15.105740181268883 15.0 research 19.4585448392555 11.5 book 22.84263959390863 13.5 geosciences 100.0 0.4561961591243744 geophysics 100.0 0.4561961591243744 use DeepForest notebook 0.6042296072507553 0.6 geology 100.0 0.7395366430282593 notebook 19.120135363790187 11.3 earth sciences 100.0 0.7395366430282593 The research object refers to the Livestock detection using DeepForest notebook published in the Environmental Data Science book. 60.76076076076076 60.7 Literature Arts, culture and entertainment/Arts and entertainment/Literature detection 17.089678510998308 10.1 detection 11.345939933259174 10.2 book 12.235817575083425 11.0 Environmental Data Science 17.575083426028918 15.8 Queen Mary University London c.appel@qmul.ac.uk Cameron Appel Environmental Data Science Book Community Applied sciences https://fair2adapt.github.io/NRDA-example/ 2025-05-19 06:55:45.523201+00:00 2025-10-14 08:33:04.563688+00:00 Rendered version of the Jupyter notebooks showcasing the usage of the NRDA. https://fair2adapt.github.io/NRDA-example/ 2025-05-19 06:55:45.523201+00:00 https://github.com/FAIR2Adapt/NRDA-example 2025-05-19 06:54:52.480118+00:00 2025-10-14 08:33:04.333200+00:00 Github repository with an example showing how to access data from the NRDA via RO-Crate https://github.com/FAIR2Adapt/NRDA-example 2025-05-19 06:54:52.480118+00:00 https://github.com/annefou/ckanext-signposting 2024-12-11 12:20:51.016321+00:00 2025-05-19 06:45:18.786943+00:00 Github repository containing the CKAN extension code for implementing signposting in CKAN. CKAN extension for Signposting 2024-12-11 12:20:51.016321+00:00 https://github.com/annefou/nird-ckan2ro 2024-12-11 12:22:22.949411+00:00 2025-05-19 06:45:25.228363+00:00 Source code repository (github) showing how to create a Research Object from the Test Norwegian Research Data Archive. It uses the CKAN API. CKAN to Research Object 2024-12-11 12:22:22.949411+00:00 Anne Fouilloux Sigma2, Norway adilhasan2@gmail.com Adil Hasan 0000-0003-2373-7112 https://raw.githubusercontent.com/FAIR2Adapt/NRDA-example/refs/heads/main/notebooks/NRDA-RO-crate-explore.ipynb 2025-05-19 07:25:51.954071+00:00 2025-10-14 08:33:04.777760+00:00 Jupyter notebook to showcase the use of the NRDA. NRDA-RO-crate-explore.ipynb (Jupyter notebook) 2025-05-19 07:25:51.954071+00:00 post@simula.no 00vn06n10 Simula Research Laboratory 0 https://api.rohub.org/api/ros/7733ebf0-b1be-4522-a909-8089251749c4/crate/download/ 2024-12-11 12:17:40.090186+00:00 2025-10-16 12:17:00.022006+00:00 2024-12-11 12:17:40.090186+00:00 The increasing volume and complexity of research data necessitate robust data management practices to ensure data is Findable, Accessible, Interoperable, and Reusable (FAIR). The Norwegian Research Data Archive (NRDA) is at the forefront of this effort in Norway, providing a comprehensive platform for researchers to store, share, and archive their data. This paper discusses NRDA's ongoing initiatives to enhance its infrastructure in alignment with FAIR principles, emphasizing the integration of Research Objects (ROs) and RO-Crate technologies. These improvements aim to facilitate better data discoverability, accessibility, and interoperability, thereby fostering a more integrated and sustainable data ecosystem. The paper also highlights NRDA's collaborative efforts with other platforms via the use of Research Objects to support data sharing and reuse across repositories. By focusing on standardized metadata, persistent identifiers, and interoperability, NRDA is advancing Open Science practices, ultimately contributing to a more transparent, efficient, and collaborative research environment. The challenges and future directions of these initiatives are also explored, providing insights into the ongoing efforts to create a more open and interconnected scientific landscape. application/ld+json https://w3id.org/ro-id/7733ebf0-b1be-4522-a909-8089251749c4 fair Enhancing FAIR Data Practices in the Norwegian Research Data Archive: Towards Research Objects and Improved interoperability MANUAL Fouilloux, Anne, and Adil Hasan. "Enhancing FAIR Data Practices in the Norwegian Research Data Archive: Towards Research Objects and Improved interoperability." ROHub. Dec 11 ,2024. https://w3id.org/ro-id/7733ebf0-b1be-4522-a909-8089251749c4. Folder containing tools or link to tools related to the Research Object. tool 961641 https://api.rohub.org/api/resources/02b43109-5847-44fa-9b7c-a2747c15279b/download/ 2025-05-19 06:50:18.905599+00:00 2025-10-14 08:33:04.114639+00:00 Presentation given at the FDO Forum on May 19th 2025. application/pdf NIRD-Archive_May2025.pdf 2025-05-19 06:50:18.905599+00:00 43137799 https://api.rohub.org/api/resources/03530455-5a74-4165-a85d-08cf04a39dd6/download/ 2025-05-19 06:47:25.736944+00:00 2025-10-14 08:33:03.675762+00:00 Demonstration of the Norwegian Research Data Archive: - Create a new dataset and upload files in the data collection - Explore a published dataset and reuse it in a Jupyter notebook. video/mp4 NRDA-CKAN.mp4 (demo) 2025-05-19 06:47:25.736944+00:00 data management practice 33.07086614173228 12.6 Norway Library and museum Arts, culture and entertainment/Culture/Library and museum complexity 6.0529634300126105 4.8 social and information sciences 100.0 0.7921985387802124 Science and technology Science and technology collaborative effort 14.698162729658792 5.6 data library 5.926860025220681 4.7 NRDA 19.120458891013385 10.0 Ro-crate technology 19.42257217847769 7.4 data 12.045889101338433 6.3 documentation and information science 100.0 0.7921985387802124 interoperability 13.997477931904163 11.1 The increasing volume and complexity of research data necessitate robust data management practices to ensure data is Findable, Accessible, Interoperable, and Reusable (FAIR). The Norwegian Research Data Archive (NRDA) is at the forefront of this effort in Norway, providing a comprehensive platform for researchers to store, share, and archive their data. 34.883720930232556 21.0 data management 12.48423707440101 9.9 computer science 29.646017699115042 6.7 practice 14.880201765447667 11.8 data sharing 4.918032786885246 3.9 By focusing on standardized metadata, persistent identifiers, and interoperability, NRDA is advancing Open Science practices, ultimately contributing to a more transparent, efficient, and collaborative research environment. 22.591362126245848 13.6 Enhancing FAIR Data Practices in the Norwegian Research Data Archive: Towards Research Objects and Improved interoperability. 42.524916943521596 25.6 database 70.35398230088495 15.9 datum 9.36902485659656 4.9 environmental science and management 100.0 0.9605517387390137 Customs and tradition Arts, culture and entertainment/Culture/Customs and tradition research datum 17.060367454068242 6.5 environmental sciences 100.0 0.9605517387390137 data 16.64564943253468 13.2 data ecosystem 15.74803149606299 6.0 practice 12.237093690248567 6.4 information 5.926860025220681 4.7 interoperability 19.88527724665392 10.4 data management 18.164435946462717 9.5 datum 6.557377049180328 5.2 initiative 5.296343001261034 4.2 Research Object 9.177820267686425 4.8 research 7.313997477931904 5.8 Applied sciences http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/0ad11a2d-9625-420b-9746-e7afdc473ac6 2024-12-20 15:12:15.310174+00:00 2025-05-26 15:46:27.371052+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2023) carried out in the mussel farm site to detect the macro-litter on the seafloor after the cleaning activities performed by the Seabed Robotic Cleaning Platform.m. Macrolitter detection on the seafloor - Mussel Farm 2023 2024-12-20 15:12:15.310174+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/1988bdeb-d639-41f7-a825-5b2ba641ebfa 2024-12-20 15:20:31.518510+00:00 2025-05-26 15:41:11.981201+00:00 Bathymetry collected in the Sacca Fisola site on May 2022 before the the cleaning activities performed by the Seabed Robotic Cleaning Platform. Sacca Fisola 2022 May Bathymetry 2024-12-20 15:20:31.518510+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/236ed88f-a25f-48c8-9701-1fe4fdd61a84 2024-12-20 14:39:04.973619+00:00 2025-05-26 15:56:33.879435+00:00 Tables, protocols and shapefiles related to the post-cleaning surveys (2023, 2024) carried out in a mussel farm near Cavallino-Jesolo to assess the microplastic in fishes after the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Fish, Mussel Farm 2023-2024 (Post-cleaning Survey) 2024-12-20 14:39:04.973619+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/34f2c1f1-a864-46fd-ba4b-2e62a4b1c860 2024-12-20 15:07:27.466315+00:00 2025-05-26 15:55:28.108642+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2022) carried out in Sacca Fisola to assess the microplastic in surface water before the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Surface Water, Sacca Fisola 2022 (Pre-cleaning Survey) 2024-12-20 15:07:27.466315+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/4307497e-6702-42c7-98b4-0a7aee345750 2024-12-20 14:49:56.705295+00:00 2025-05-26 15:55:19.870615+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2022) carried out in Sacca Fisola to assess the microplastic in bivalves before the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Bivalves, Sacca Fisola 2022 (Pre-cleaning Survey) 2024-12-20 14:49:56.705295+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/47d7b107-31f7-44c2-8eb2-fbe8a65d68cd 2024-12-20 14:39:32.211885+00:00 2025-05-26 15:56:42.998388+00:00 Tables, protocols and shapefiles related to the post-cleaning surveys (2023, 2024) carried out in a mussel farm near Cavallino-Jesolo to assess the microplastic in bivalves after the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Bivalves, Mussel Farm 2023-2024 (Post-cleaning Survey) 2024-12-20 14:39:32.211885+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/48529609-9704-42e5-b15b-dbe43f3308f0 2024-12-20 14:35:52.811399+00:00 2025-05-26 15:56:25.182921+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2022) carried out in a mussel farm near Cavallino-Jesolo to assess the microplastic in fishes before the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Fish, Mussel Farm 2022 (Pre-cleaning Survey) 2024-12-20 14:35:52.811399+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/5ef4e275-f53e-498b-8717-05da17b5bfa2 2024-12-20 14:38:32.430464+00:00 2025-05-26 15:55:01.389222+00:00 Tables, protocols and shapefiles related to the post-cleaning surveys (2023, 2024) carried out in Sacca Fisola to assess the microplastic in surface water after the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Surface Water, Sacca Fisola 2023-2024 (Post-cleaning Survey) 2024-12-20 14:38:32.430464+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/71b1f56c-efe0-440f-8e15-f3db60134a33 2024-12-20 14:40:37.183586+00:00 2025-05-26 15:56:57.760910+00:00 Tables, protocols and shapefiles related to the post-cleaning surveys (2023, 2024) carried out in a mussel farm near Cavallino-Jesolo to assess the microplastic in surface water after the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Surface Water, Mussel Farm 2023-2024 (Post-cleaning Survey) 2024-12-20 14:40:37.183586+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/784e7e2c-3b4c-44c6-9023-64dbc740f5d8 2024-12-20 15:07:50.929964+00:00 2025-05-26 15:55:43.608256+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2022) carried out in Sacca Fisola to assess the microplastic in fishes before the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Fish, Sacca Fisola 2022 (Pre-cleaning Survey) 2024-12-20 15:07:50.929964+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/839f5610-43a3-4e96-bb61-a2b069ca01e7 2024-12-20 15:16:29.189661+00:00 2025-05-23 13:44:40.159266+00:00 Bathymetry collected in the mussel farm site on December 2022 before the the cleaning activities performed by the Seabed Robotic Cleaning Platform. Mussel Farm 2023 December Bathymetry 2024-12-20 15:16:29.189661+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/aa52596d-586b-4c2e-bb5c-48022ab6c04a 2024-12-20 14:34:38.008000+00:00 2025-05-26 15:56:17.514990+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2022) carried out in a mussel farm near Cavallino-Jesolo to assess the microplastic in surface water before the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Surface Water, Mussel Farm 2022 (Pre-cleaning Survey) 2024-12-20 14:34:38.008000+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/bbbd2fc8-77cd-4095-b1ff-0cf3f9c789e4 2024-12-20 15:17:41.000199+00:00 2025-05-26 15:42:21.445118+00:00 Bathymetry collected in the Sacca Fisola site on December 2023 after the the cleaning activities performed by the Seabed Robotic Cleaning Platform. Sacca Fisola 2023 December Bathymetry 2024-12-20 15:17:41.000199+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/c9b7e1ee-cdbf-4ffb-9610-98df251d844f 2024-12-20 14:41:38.664513+00:00 2025-05-26 15:55:10.681343+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2022) carried out in Sacca Fisola to assess the microplastic in sediments before the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Sediment, Sacca Fisola 2022 (Pre-cleaning Survey) 2024-12-20 14:41:38.664513+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/cfe5ea83-0679-4186-b006-40c3747f322d 2024-12-20 14:36:33.492754+00:00 2025-05-26 15:54:31.591424+00:00 Tables, protocols and shapefiles related to the post-cleaning surveys (2023, 2024) carried out in Sacca Fisola to assess the microplastic in fishes after the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Fish, Sacca Fisola 2023-2024 (Post-cleaning Survey) 2024-12-20 14:36:33.492754+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/d130e73e-cd9e-4e0b-8b85-e0b440d2dbfc 2024-12-20 14:40:05.680064+00:00 2025-05-26 15:56:50.424085+00:00 Tables, protocols and shapefiles related to the post-cleaning surveys (2023, 2024) carried out in a mussel farm near Cavallino-Jesolo to assess the microplastic in sediments after the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Sediment, Mussel Farm 2023-2024 (Post-cleaning Survey) 2024-12-20 14:40:05.680064+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/d4704eba-e738-4b2c-a042-3704bbef473b 2024-12-20 15:13:46.791576+00:00 2025-05-26 15:46:37.512834+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2022) carried out in the mussel farm site to assess the microplastic in sediments before the cleaning activities performed by the Seabed Robotic Cleaning Platform. Macrolitter detection on the seafloor - Mussel Farm 2022 2024-12-20 15:13:46.791576+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/d6c4c669-a416-4ac3-839e-2515d8428477 2024-12-20 15:19:45.739840+00:00 2025-05-23 13:45:01.652966+00:00 Bathymetry collected in the in the mussel farm site on february 2022 before the the cleaning activities performed by the Seabed Robotic Cleaning Platform. Mussel Farm 2022 Bathymetry 2024-12-20 15:19:45.739840+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/ef25728b-a87f-4a9d-a29d-51f5e5fcbc59 2024-12-20 14:37:11.222446+00:00 2025-05-26 15:54:41.415165+00:00 Tables, protocols and shapefiles related to the post-cleaning surveys (2023, 2024) carried out in Sacca Fisola to assess the microplastic in sediments after the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Sediment, Sacca Fisola 2023-2024 (Post-cleaning Survey) 2024-12-20 14:37:11.222446+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/ef445f1d-addc-4f9f-b831-6339d8bc3b04 2024-12-20 15:10:25.406876+00:00 2025-06-10 10:55:23.959284+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2022) carried out in Sacca Fisola to detect the macro-litter on the seafloor before the cleaning activities performed by the Seabed Robotic Cleaning Platform. Macrolitter detection on the seafloor - Sacca Fisola 2022 (pre-cleaning) 2024-12-20 15:10:25.406876+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/f4bfe20e-8b91-4de4-974c-b18faa95e79d 2024-12-20 14:50:50.887677+00:00 2025-05-26 15:57:04.726679+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2022) carried out in a mussel farm near Cavallino-Jesolo to assess the microplastic in sediments before the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Sediment, Mussel Farm 2022 (Pre-cleaning Survey) 2024-12-20 14:50:50.887677+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/f544dadb-1ee8-47cb-ad37-86bf034cf50d 2024-12-20 15:18:08.708289+00:00 2025-05-26 15:40:39.220185+00:00 Bathymetry collected in the Sacca Fisola site on May 2023 after the the cleaning activities performed by the Seabed Robotic Cleaning Platform. Sacca Fisola 2023 May Bathymetry 2024-12-20 15:18:08.708289+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/f5b2f2c6-91cc-4815-9ee0-70a048d3b329 2024-12-20 15:06:39.315950+00:00 2025-05-26 15:57:11.943203+00:00 Tables, protocols and shapefiles related to the pre-cleaning survey (2022) carried out in a mussel farm near Cavallino-Jesolo to assess the microplastic in bivalves before the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Bivalves, Mussel Farm 2022 (Pre-cleaning Survey) 2024-12-20 15:06:39.315950+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/f72ceecd-9a62-4354-aac7-b08b3e3f29a1 2024-12-20 14:37:37.024253+00:00 2025-05-26 15:54:53.683679+00:00 Tables, protocols and shapefiles related to the post-cleaning surveys (2023, 2024) carried out in Sacca Fisola to assess the microplastic in bivalbes after the cleaning activities performed by the Seabed Robotic Cleaning Platform. Microplastics Assessment in Bivalves, Sacca Fisola 2023-2024 (Post-cleaning Survey) 2024-12-20 14:37:37.024253+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/f8092cbe-bcd1-4b19-a571-516489c9cedd 2025-06-10 15:05:54.994211+00:00 2025-10-14 08:33:53.823824+00:00 Canal Grande 2023 April marine litter distribution 2025-06-10 15:05:54.994211+00:00 http://libeccio.bo.ismar.cnr.it:8080/geonetwork/srv/eng/catalog.search#/metadata/fe49ceb8-59ca-43aa-8456-7b7ef7f8a55a 2024-12-20 15:17:04.196501+00:00 2025-05-23 13:44:53.397619+00:00 Bathymetry collected in the mussel farm site on May 2023 after the the cleaning activities performed by the Seabed Robotic Cleaning Platform. Mussel Farm 2023 May Bathymetry 2024-12-20 15:17:04.196501+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/eng/catalog.search#/metadata/ef796898-5baf-465f-9eef-4aebb4e7e3c9 2025-06-10 15:05:26.439415+00:00 2025-10-14 08:33:53.380074+00:00 Canal Grande 2013 marine litter distribution 2025-06-10 15:05:26.439415+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/38a82b77-26c6-44cb-bd3e-972daf295b74 2025-06-11 09:30:44.441430+00:00 2025-10-14 08:33:56.016359+00:00 As part of the European MAELSTROM project, a combined approach using bathymetric analysis and underwater video inspections was applied to investigate marine litter (ML) accumulation on the seafloor in the urban area of Sacca Fisola (SF). The integration of multibeam echosounder (MBES) data with diver-operated video transects allowed not only the visual validation of acoustic results but also a more detailed mapping of litter items. During a 100-metre transect conducted by professional divers on 12 July 2022, 34 marine litter objects were identified and classified. This multiparametric strategy enabled the spatial georeferencing of debris and an estimate of their percentage coverage on the seafloor. Video Inspections - Sacca Fisola 2022 2025-06-11 09:30:44.441430+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/457123f4-edad-47f2-9462-455cae51f913 2025-05-27 09:01:43.184503+00:00 2025-10-14 08:33:57.414475+00:00 As part of the European MAELSTROM project, passive acoustic monitoring (PAM) was conducted using a hydrophone deployed before and after the cleaning campaign carried out with a robotic platform at the Mussel Farm site. The primary aim of this acoustic monitoring was to analyze underwater soundscapes to detect the presence of soniferous organisms, with particular attention to fish and potentially invertebrate components Passive Acoustic Monitoring (PAM) - Mussel Farm 2022/2024 2025-05-27 09:01:43.184503+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/60aa5a5d-33bf-4610-9384-7493dc6168de 2025-06-06 08:49:32.624739+00:00 2025-10-14 08:33:49.369364+00:00 The ecological assessment of the Ave Estuary has been conducted since the beginning of the MAELSTROM project, covering the Spring and Autumn periods each year (seasons with the highest biological activity for this type of water body). After the installation of the Bubble Barrier, ecological assessments were carried out seasonally to monitor the ecosystem's progression following the implementation of the waste collection technology. MAELSTROM: Ecological assessment campaigns in the Ave River estuary in Portugal (pre and post cleaning) 2025-06-06 08:49:32.624739+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/7436a689-b929-4ed0-a06e-0fc8b9df36e5 2025-06-11 09:29:17.874825+00:00 2025-10-14 08:33:55.639252+00:00 As part of the MAELSTROM project, a video survey was conducted on 23 September 2022 at the abandoned mussel farm (MF) site in the coastal area outside the Venetian lagoon. The purpose of the survey was to visually document and classify marine debris items on the seabed and to support the validation of previous bathymetric analyses. The inspection revealed several types of debris, including mooring structures, ropes, and derelict fishing gear, elements that are often challenging to detect through remote sensing techniques alone. Video Inspections - Mussel Farm 2022 2025-06-11 09:29:17.874825+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/83b154e3-a8a5-4cc4-9666-4a3ae447a27b 2025-06-06 12:33:37.643035+00:00 2025-10-14 08:33:51.347699+00:00 Soft bottom macrozoobenthic communities were characterized in Sacca Fisola. In the lagoon site, three stations were defined: LV1 (on the planned cleaning area), LV2 (control) and LV3 (additional, in case more information would have been required). The protocol includes sampling by Van Veen grab (surface area of 0.1 m2, volume of approx. 17 L), taxonomic determination and quantitative analysis of the community matrix. MAELSTROM: Soft bottom macrozoobenthos - Sacca Fisola 2022 (pre-cleaning) 2025-06-06 12:33:37.643035+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/880ae033-6c52-406d-b10f-b44d05d65a4e 2025-06-06 12:07:02.510715+00:00 2025-10-14 08:33:50.578510+00:00 Soft bottom macrozoobenthic communities were characterized in Mussel Farm. In the coastal site, three stations were defined: CS1 (planned cleaning area and discontinued in September 2023), CS2 (control) and CS4 (cleaning area since september 2023). The protocol includes sampling by Van Veen grab (surface area of 0.1 m2, volume of approx. 17 L), taxonomic determination and quantitative analysis of the community matrix. Soft bottom macrozoobenthos - Mussel Farm 2023 (pre-cleaning) 2025-06-06 12:07:02.510715+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/8cc5e139-1ec0-4c75-acc2-60fa103ca79d 2025-06-10 07:31:35.283951+00:00 2025-10-14 08:33:52.621591+00:00 The bathymetry was acquired in 2013 in the Grand Canal (Venice) as part of the RITMARE (La Ricerca ITaliana per il MARE) research project. The data were collected using a Kongsberg EM-2040 dual-head multibeam system operating at 360 kHz, mounted on the CNR Litus vessel, and subsequently processed with Kongsberg SIS software. The information acquired was integrated with sound velocity profiles and georeferenced using the Seapath 300 positioning system. This survey will serve as a basis for comparison with data collected ten years later, in 2023, in order to assess any morphological and sedimentological changes in the bottom of the Grand Canal. Canal Grande 2013 Bathymetry 2025-06-10 07:31:35.283951+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/a48d47e6-6bda-4cae-a5bb-c71c3a5f6cf0 2025-06-06 08:51:27.045277+00:00 2025-10-14 08:33:49.718170+00:00 In the Ave River estuary, monitoring of Floating Macro-Litter (FML) was undertaken before (June 2021 - December 2023) and after the installation of the Bubble Barrier remediation technology in order to assess its effectiveness. Evaluation of FML followed standard European guidelines (Hanke et al., 2013, 2023) and was conducted through visual monitoring to assess the diversity and relative abundance of debris in the area. Monitoring campaigns were carried out monthly from June 2021 to December 2024. FML observations were performed using binoculars (during ebb tide at three designated locations in the estuary—downstream, midstream, and upstream. All three observation points were positioned at the same elevation along the estuary margin, approximately 2 meters above the water surface (mean sea level), ensuring a consistent viewing angle for reliable comparisons between locations. Although some FML objects may have been partially obscured by wind-generated ripples or small waves from passing boats, this impact was minimized as observations were conducted on calm days with high visibility. More details on the methodology can be found in D5.4 More details on the results can be found in D2.4. Monitoring of Floating Macro-Litter in the Ave River estuary in Portugal (pre and post the cleaning) 2025-06-06 08:51:27.045277+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/a600e3a4-9b02-40a8-ab01-590dd238015c 2025-06-06 12:37:11.630649+00:00 2025-10-14 08:33:52.203234+00:00 During the marine litter cleanup activities at the lagoon site, fouling organisms were sampled from a subset of the collected litter items. From each item, a 0.1 m² area was scraped from the surface exposed to epifaunal colonization. For the lagoon site, 5 items (4 tires and a metal frame) were subject to scraping on 26-27/09/2022. MAELSTROM: Marine litter fouling communities - Sacca Fisola 2022 2025-06-06 12:37:11.630649+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/af2484fc-7929-4034-bca8-7895894cbb8b 2025-06-06 12:36:29.777018+00:00 2025-10-14 08:33:51.732843+00:00 Soft bottom macrozoobenthic communities were characterized in Sacca Fisola. In the lagoon site, three stations were defined: LV1 (on the planned cleaning area), LV2 (control) and LV3 (additional, in case more information would have been required). The protocol includes sampling by Van Veen grab (surface area of 0.1 m2, volume of approx. 17 L), taxonomic determination and quantitative analysis of the community matrix. MAELSTROM: Soft bottom macrozoobenthos - Sacca Fisola 2023/2024 (post-cleaning) 2025-06-06 12:36:29.777018+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/c12f5031-7449-40e1-b41e-068075f0f0f8 2025-05-28 15:02:28.709570+00:00 2025-10-14 08:33:48.563190+00:00 MAELSTROM: Assessment of fish community in lagoon area, Sacca Fisola (Post-cleaning Survey) 2025-05-28 15:02:28.709570+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/c6779901-f2a5-4740-9791-0e712fa9e810 2024-12-20 15:11:07.324123+00:00 2025-06-10 10:57:06.842589+00:00 For this project, two study areas were selected and both are characterized by the presence of marine litter that has accumulated over time: a lagoon area (Sacca Fisola) and a coastal area, the latter located on an abandoned mussel farm.The lagoon site of Sacca Fisola is situated in an area where waste accumulates in substantial quantities. Consequently, the channel's seabed is marked by a significant presence of waste. Some of these waste items are buried beneath layers of sediment, while many others remain visible on the surface and can be identified using the bathymetric map generated from MultiBeam EchoSounder (MBES) data. Macrolitter detection on the seafloor - Sacca Fisola 2022 (post-cleaning) 2024-12-20 15:11:07.324123+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/ca2f4c3d-f4b3-4562-bf27-e955159f9cf9 2025-05-28 15:00:33.879751+00:00 2025-10-14 08:33:47.830443+00:00 Assessment of fish community in coastal area, Mussel Farm (Pre-cleaning Survey) 2025-05-28 15:00:33.879751+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/d033a6cb-4761-4e7c-b5fd-e4c9e59d9c1b 2025-05-28 15:03:50.259639+00:00 2025-10-14 08:33:48.970815+00:00 Assessment of fish community in coastal area, Mussel Farm (Post-cleaning Survey) 2025-05-28 15:03:50.259639+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/d92f8bc0-c8bf-422b-b2cf-2fa910de8196 2025-06-10 07:35:23.396790+00:00 2025-10-14 08:33:52.952429+00:00 Data collected in April 2023 by CNR- ISMAR VE within the MAELSTROM project with the aim to map marine litter on the seafloor Canal Grande 2023 April Bathymetry 2025-06-10 07:35:23.396790+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/dfc27d84-0dd0-4e59-98b8-3e02890866de 2025-05-28 15:01:45.265724+00:00 2025-10-14 08:33:48.209584+00:00 MAELSTROM: Assessment of fish community in lagoon area, Sacca Fisola (Pre-cleaning Survey) 2025-05-28 15:01:45.265724+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/e4c8d7e7-46b8-44cb-b236-038071c6698d 2025-06-06 12:08:38.478285+00:00 2025-10-14 08:33:51.003216+00:00 During the marine litter cleanup activities at the Mussel Farm site, fouling organisms were sampled from a subset of the collected litter items. From each item, a 0.1 m² area was scraped from the surface exposed to epifaunal colonization. In the coastal site, samples of sufficient quality could be acquired during May-June 2023 cleaning operations, 2 plastic buoys retained near the seabed and a section of synthetic rope, all of them leftover aquaculture equipment. Marine litter fouling communities - Mussel Farm 2023 2025-06-06 12:08:38.478285+00:00 http://seamap-catalog.data.ismar.cnr.it:8080/geonetwork/maelstrom/ita/catalog.search#/metadata/ec3ab102-f183-4f02-84fd-d64106c283ad 2025-06-06 12:05:09.250864+00:00 2025-10-14 08:33:50.129830+00:00 Soft bottom macrozoobenthic communities were characterized in Mussel Farm. In the marine site, three stations were defined: CS1 (planned cleaning area and discontinued in September 2023), CS2 (control) and CS4 (cleaning area since september 2023). The protocol includes sampling by Van Veen grab (surface area of 0.1 m2, volume of approx. 17 L), taxonomic determination and quantitative analysis of the community matrix. Soft bottom macrozoobenthos - Mussel Farm 2023/2024 (post-cleaning) 2025-06-06 12:05:09.250864+00:00 CNR-ISMAR valentina.grande@bo.ismar.cnr.it Valentina Grande 0000-0002-3489-268X 12.311973568866962 45.42473574369795 POINT (12.311973568866962 45.42473574369795) 12.316703791148031 45.42485120298669 POINT (12.316703791148031 45.42485120298669) b4abd3bf-6600-4e3d-9397-57d4493a50c4 POINT (12.311973568866962 45.42473574369795) b60d685d-9c0d-4359-8d99-3d80d0952542 POINT (-8.745117208454758 41.34139020920495) d4c8a9c2-15c1-48ed-ac59-699688dd3784 POINT (12.316703791148031 45.42485120298669) -8.745117208454758 41.34139020920495 POINT (-8.745117208454758 41.34139020920495) 10.24424/n4zj-z687 2025-06-16 11:45:39.717843+00:00 True 695223 https://api.rohub.org/api/ros/9d238d26-7ebd-4517-974f-f9f91b7055fc/crate/download/ 2024-12-20 14:13:22.405250+00:00 2025-10-16 12:11:19.378628+00:00 2024-12-20 14:13:22.405250+00:00 The first objective of the H2020 MAELSTROM Project is in support of the Marine Strategy Framework Directive (MSFD) and it aims at defining and implementing an Integrated Assessment Approach (IAA) to evaluate the effectiveness of ML remediation actions and their positive and/or negative impacts on marine coastal ecosystems and local economies. The IAA will consider both macro litter and microplastics, and it will include seafloor ML, as well as surface and water column ML. The IAA will integrate and operationalize knowledge and data related to ML sources, ML dispersion and fate, ML accumulation in hot spots, negative impacts on coastal ecosystems’ food chains, biodiversity and functioning, Marine Protected Areas, wildlife and the coastal and maritime sectors relevant for local economies. The IAA will also help improving marine and coastal spatial planning, conservation and restoration of coastal ecosystems in support of the EU Integrated Maritime Policy, delivering concrete benefits for maritime growth and sustainability in Europe. application/ld+json https://w3id.org/ro-id/9d238d26-7ebd-4517-974f-f9f91b7055fc ave estuary horizon europe maelstrom marine litter pollution assessment venice lagoon Result MAELSTROM Objective 1: Integrated assessment of the cleaning operations effectiveness and their impacts - archive MAELSTROM Objective 1: Integrated assessment of the cleaning operations effectiveness and their impacts MANUAL © MAELSTROM - Smart technology for MArinE Litter SusTainable RemOval and Management funded by the European Union, Programme H2020-EU.3.2.5.1. Grant agreement No 101000832. https://doi.org/10.3030/101000832. Fantina Madricardo, Vanessa Moschino, Susanna Mesghez, ANTONIO PETRIZZO, Taha Lahami, and Valentina Grande. "MAELSTROM Objective 1: Integrated assessment of the cleaning operations effectiveness and their impacts - archive." ROHub. Dec 20 ,2024. https://doi.org/10.24424/n4zj-z687. POINT (12.316703791148031 45.42485120298669) POINT (12.311973568866962 45.42473574369795) POINT (-8.745117208454758 41.34139020920495) VENICE_COASTAL_AREA mussel_farm_site macrolitter sacca_fisola_site microplastics mussel_farm_site bathymetry mussel_farm_site mussel_farm_site sacca_fisola_site fish_assessment mussel_farm_site sacca_fisola_site canal_grande_site macrozoobenthos Video_inspection bioacoustic ecological_assessment mussel_farm_site canal_grande_site sacca_fisola_site sacca_fisola_site AVE_ESTUARY 437549 https://api.rohub.org/api/resources/48e016b5-f151-466e-91a6-06bd66b39f18/download/ 2025-06-10 15:18:53.699972+00:00 2025-10-14 08:33:55.334566+00:00 image/png Integrated assessment framework 2025-06-10 15:18:53.699972+00:00 seafloor ML 25.925925925925924 12.6 European Union 9.812409812409813 6.8 Synthetic and plastic chemicals Economy, business and finance/Economic sector/Chemicals/Synthetic and plastic chemicals economy 10.183299389002036 5.0 The first objective of the H2020 MAELSTROM Project is in support of the Marine Strategy Framework Directive (MSFD) and it aims at defining and implementing an Integrated Assessment Approach (IAA) to evaluate the effectiveness of ML remediation actions and their positive and/or negative impacts on marine coastal ecosystems and local economies. 64.08977556109726 51.4 aim 5.916305916305916 4.1 ML accumulation 17.28395061728395 8.4 ecology 26.923076923076923 2.1 biology 15.384615384615385 1.2 ML 19.551934826883908 9.6 seabed 9.37950937950938 6.5 ML dispersion 19.95884773662551 9.7 planning 4.473304473304474 3.1 environmental sciences 100.0 0.9837613701820374 Oceans Environment/Natural resources/Water/Oceans The IAA will consider both macro litter and microplastics, and it will include seafloor ML, as well as surface and water column ML. 21.321695760598505 17.1 environmental science and management 100.0 0.9837613701820374 effectiveness 13.034623217922606 6.4 European Union 11.20162932790224 5.5 politics 12.820512820512821 1.0 ecosystem 13.275613275613274 9.2 remediation action 18.51851851851852 9.0 Integrated Assessment Approach 20.570264765784113 10.1 effectiveness 11.255411255411255 7.8 renovation 8.802308802308803 6.1 litter 4.761904761904762 3.3 geosciences 100.0 0.3251190781593323 The IAA will integrate and operationalize knowledge and data related to ML sources, ML dispersion and fate, ML accumulation in hot spots, negative impacts on coastal ecosystems’ 14.58852867830424 11.7 ecosystem 14.867617107942973 7.3 seafloor 10.590631364562118 5.2 conservation 8.225108225108226 5.7 information 6.204906204906205 4.3 Marine Strategy Framework Directive 18.31275720164609 8.9 geophysics 100.0 0.3251190781593323 policy 8.658008658008658 6.0 Renovation Economy, business and finance/Economic sector/Construction and property/Renovation economy 9.235209235209236 6.4 the economy 44.871794871794876 3.5 European Union https://zenodo.org/records/14930115 2025-03-13 14:40:54.914041+00:00 2025-10-14 08:33:57.027156+00:00 Antunes, S., Vieira, L., Iglesias, I., Sousa Pinto, I., Tomás Correia, A. M., Moreira, R., Padilha, D., Nesto, N., Sigovini, M., Guarneri, I., Tagliapietra, D., Madricardo, F., McKiver, W., Petrizzo, A., Marceta, T., Galvez, D., Bocci, M., Cecchi, T., & MOSCHINO, V. (2022). D2.3 Ecosystem state and ML pollution assessment in the two demo sites (Lagoon of Venice and the Porto region). MAELSTROM Project. https://doi.org/10.5281/zenodo.14930115 D2.3 Ecosystem state and ML pollution assessment in the two demo sites (Lagoon of Venice and the Porto region) 2025-03-13 14:40:54.914041+00:00 https://zenodo.org/records/15544591 2025-06-10 15:07:23.397206+00:00 2025-10-14 08:33:54.252675+00:00 MOSCHINO, V., Nesto, N., Sigovini, M., Guarneri, I., Madricardo, F., Mc Kiver, W., Ghezzo, M., Petrizzo, A., Marčeta, T., Mesghez, S., Lahami, T., Picciulin, M., Manfè, G., Bocci, M., Antunes, S., Vieira, L., Iglesias, I., Nogueira, S., del Oro Alcalde, D., … Sousa-Pinto, I. (2025). D2.4 Impact assessment report in the two demo sites (Lagoon of Venice and the Porto region). MAELSTROM Project. https://doi.org/10.5281/zenodo.15544591 D2.4 Impact assessment report in the two demo sites (Lagoon of Venice and the Porto region) 2025-06-10 15:07:23.397206+00:00 https://zenodo.org/records/15545862 2025-06-10 15:08:03.521215+00:00 2025-10-14 08:33:54.712060+00:00 Bocci, M., Poletto, D., MOSCHINO, V., Nesto, N., Madricardo, F., Sigovini, M., Marčeta, T., Mesghez, S., Petrizzo, A., Lahami, T., Vieira, L. R., Antunes, S. C., Iglesias, I., Kett, G., Nogueira, S., del Oro Alcalde, D., Bio, A., Pezzilli, C., de Casto, G., … Buschman, F. A. (2025). D2.5 Integrated assessment of the cleaning operations effectiveness and their impacts. MAELSTROM Project. https://doi.org/10.5281/zenodo.15545862 D2.5 Integrated assessment of the cleaning operations effectiveness and their impacts 2025-06-10 15:08:03.521215+00:00 Università Ca' Foscari 956784@stud.unive.it Susanna Mesghez antonio.petrizzo@cnr.it ANTONIO PETRIZZO direttore@ismar.cnr.it CNR-ISMAR CNR ISMAR fantina.madricardo@ve.ismar.cnr.it Fantina Madricardo CNR ISMAR taha.lahami@ve.ismar.cnr.it Taha Lahami CNR ISMAR Venice vanessa.moschino@ve.ismar.cnr.it Vanessa Moschino Environmental research https://doi.org/10.5281/zenodo.17171136 2025-09-22 10:50:40.131872+00:00 2025-09-22 10:50:40.766967+00:00 Contains outputs, (results), generated in the Jupyter notebook of Vehicle-based observation data processing and simple simulation experiments Outputs 2025-09-22 10:50:40.131872+00:00 https://doi.org/10.5281/zenodo.17175792 2025-09-22 10:50:38.422172+00:00 2025-09-22 10:50:39.116427+00:00 Contains input Input datasets used in the Jupyter notebook of Vehicle-based observation data processing and simple simulation experiments Input Input datasets 2025-09-22 10:50:38.422172+00:00 https://github.com/eds-book/dea59792-5a6d-4633-a74c-eb73edce61b8/blob/main/notebook.ipynb 2025-09-22 10:50:36.343361+00:00 2025-09-22 10:50:37.222607+00:00 Jupyter Notebook hosted by the Environmental Data Science Book Jupyter notebook 2025-09-22 10:50:36.343361+00:00 Rio de Janeiro State University rpedruzzi@eng.uerj.br Rizzieri Pedruzzi 0000-0003-0852-0396 Hangzhou Dianzi University Zehao Liu 0009-0000-3855-6352 0 https://api.rohub.org/api/ros/368f9594-6513-4f49-a510-275c07b1c3b6/crate/download/ 2025-09-22 10:50:14.653665+00:00 2025-10-16 11:11:03.381864+00:00 2025-09-22 10:50:14.653665+00:00 The research object refers to the Vehicle-based observation data processing and simple simulation experiments notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/368f9594-6513-4f49-a510-275c07b1c3b6 Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book MANUAL Lucky J. Yang, Rizzieri Pedruzzi, and Zehao Liu. "Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book." ROHub. 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Yang Earth sciences 0 https://api.rohub.org/api/ros/ce69f062-5218-46b5-8d8a-2437af6355a2/crate/download/ 2025-10-07 17:18:31.472234+00:00 2025-11-10 11:52:39.550603+00:00 2025-10-07 17:18:31.472234+00:00 This Research Object aggregates some relevant resources for the demo application/ld+json https://w3id.org/ro-id/ce69f062-5218-46b5-8d8a-2437af6355a2 RO-Crate workshop for earth scientists MANUAL Palma, Raul. "RO-Crate workshop for earth scientists." ROHub. 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Flood analysis with JupterGIS 2025-10-07 20:09:09.230244+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/static/flood_in_saarland_with_jqgis.png 2025-10-07 20:09:06.171136+00:00 2025-10-07 20:14:05.823700+00:00 This resource has this description image/png Image - updated 2025-10-07 20:09:06.171136+00:00 04jcwf484 Nordic e-Infrastructure Collaboration 101188256 FAIR2Adapt POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1 ecfa79a4-8abe-44e8-bcb0-5e23880030e0 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 0 https://api.rohub.org/api/ros/55a1b422-f279-4765-9ba7-d27268059844/crate/download/ 2025-10-07 20:07:57.245814+00:00 2025-10-16 11:10:27.079384+00:00 2025-10-07 20:07:57.245814+00:00 This Research Object is an example for FAIR2Adapt Case Study 2 application/ld+json https://w3id.org/ro-id/55a1b422-f279-4765-9ba7-d27268059844 FAIR2Adapt RO-Crate with Jupyter Notebook MANUAL Fouilloux, Anne. "FAIR2Adapt RO-Crate with Jupyter Notebook." ROHub. Oct 07 ,2025. https://w3id.org/ro-id/55a1b422-f279-4765-9ba7-d27268059844. POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) biblio output input tool 907 https://api.rohub.org/api/resources/814cf173-b4c3-4f46-a7e8-d6edae4cf14f/download/ 2025-10-07 20:08:57.775768+00:00 2025-10-07 20:08:59.321734+00:00 image/png Image to illustrate my case study 2025-10-07 20:08:57.775768+00:00 case study 13.456090651558075 9.5 example for FAIR2Adapt case study 2 8.316633266533067 8.3 earth resources and remote sensing 100.0 0.8493164777755737 This Research Object is an example for FAIR2Adapt Case Study 2 65.76576576576576 65.7 object 15.59536354056902 14.8 research 17.91359325605901 17.0 Ro-crate with Jupyter Notebook 17.935871743486974 17.9 geosciences 100.0 0.8493164777755737 Language Arts, culture and entertainment/Culture/Language Food and drink Lifestyle and leisure/Lifestyle/Food and drink crate 20.538243626062325 14.5 Ro 10.326659641728135 9.8 research 24.36260623229462 17.2 atmospheric sciences 100.0 0.9335481524467468 FAIR2Adapt 21.390937829293993 20.3 Food Economy, business and finance/Economic sector/Consumer goods/Food research object 73.44689378757515 73.3 crate 15.700737618545837 14.9 case study 2 0.30060120240480964 0.3 FAIR2Adapt RO-Crate with Jupyter Notebook. 34.234234234234236 34.2 example 7.36543909348442 5.2 Ro 13.597733711048159 9.6 earth sciences 100.0 0.9335481524467468 case study 10.010537407797681 9.5 aim 20.67988668555241 14.6 Jupyter notebook 9.062170706006322 8.6 Instytut Chemii Bioorganicznej PAN, Poznanskie Centrum Superkomputerowo-Sieciowe PSNC Environmental research Anne Fouilloux https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Flood_protection_line_Saarland.ipynb 2025-10-08 08:47:29.592762+00:00 2025-10-08 08:47:30.239969+00:00 Visualizing Generalized Flood Areas for HQ100 Event and relate to an existing flooding event. Flood analysis with JupterGIS 2025-10-08 08:47:29.592762+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/static/flood_in_saarland_with_jqgis.png 2025-10-08 08:46:18.994606+00:00 2025-10-08 08:46:19.636455+00:00 Example for FAIR2Adapt training on RO-Crate and ROHub image/png flood in saarland with JupyterGIS 2025-10-08 08:46:18.994606+00:00 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1 c6af7a2e-b3d6-4374-81af-d4b3fd482459 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 0 https://api.rohub.org/api/ros/8a351029-86a8-4e90-a9d1-a67d45d63656/crate/download/ 2025-10-08 08:39:21.885634+00:00 2025-10-16 11:10:21.642786+00:00 2025-10-08 08:39:21.885634+00:00 This Research Object is an example for FAIR2Adapt Case Study 2 application/ld+json https://w3id.org/ro-id/8a351029-86a8-4e90-a9d1-a67d45d63656 FAIR2Adapt RO-Crate with Jupyter Notebook MANUAL Fouilloux, Anne. "FAIR2Adapt RO-Crate with Jupyter Notebook." ROHub. Oct 08 ,2025. https://w3id.org/ro-id/8a351029-86a8-4e90-a9d1-a67d45d63656. POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) biblio tool input output 907 https://api.rohub.org/api/resources/4d1eee3a-9631-4d76-a15a-ab1de329fde1/download/ 2025-10-08 08:44:48.739835+00:00 2025-10-08 08:44:50.121842+00:00 image/png Image to illustrate my case study 2025-10-08 08:44:48.739835+00:00 earth sciences 100.0 0.9335481524467468 geosciences 100.0 0.8493164777755737 This Research Object is an example for FAIR2Adapt Case Study 2 65.76576576576576 65.7 case study 13.456090651558075 9.5 crate 15.700737618545837 14.9 research 17.91359325605901 17.0 FAIR2Adapt RO-Crate with Jupyter Notebook. 34.234234234234236 34.2 Ro-crate with Jupyter Notebook 17.935871743486974 17.9 object 15.59536354056902 14.8 FAIR2Adapt 21.390937829293993 20.3 example for FAIR2Adapt case study 2 8.316633266533067 8.3 earth resources and remote sensing 100.0 0.8493164777755737 Ro 10.326659641728135 9.8 crate 20.538243626062325 14.5 case study 2 0.30060120240480964 0.3 Ro 13.597733711048159 9.6 research object 73.44689378757515 73.3 Jupyter notebook 9.062170706006322 8.6 case study 10.010537407797681 9.5 example 7.36543909348442 5.2 research 24.36260623229462 17.2 atmospheric sciences 100.0 0.9335481524467468 aim 20.67988668555241 14.6 Food and drink Lifestyle and leisure/Lifestyle/Food and drink Language Arts, culture and entertainment/Culture/Language Food Economy, business and finance/Economic sector/Consumer goods/Food Applied sciences Biology Climatology Geographical information system Earth observation Centre for Ecology, Evolution and Environmental Changes, University of Lisbon igmarques@fc.ul.pt Ines Gomes Marques 0000-0002-2104-3187 ClimRisk, CE3C, Faculty of Sciences, U Lisbon tcapela@fc.ul.pt Tiago Capela Lourenço 0000-0002-8796-5993 0 https://api.rohub.org/api/ros/302b4ebf-db38-49d5-8ab4-4561181f4e94/crate/download/ 2025-10-13 11:12:49.327063+00:00 2025-10-20 13:33:34.491167+00:00 2025-10-13 11:12:49.327063+00:00 Presentation at the CE3C Annual Meeting, Azores - Portugal *10-12 October 2025* The first Portuguese National Strategy for Adaptation to Climate Change was adopted in 2010, aiming to adjust climate and other sectoral policies, and to increase the countries’ resilience to observed and projected climate change impacts. Since then, many resources (e.g. policy documents, scientific articles, data sets) relevant for national adaptation have been published, yet often remain unknown to, or inaccessible, for the multiple stakeholders that comprise the climate adaptation community (CCA) in Portugal. The application of FAIR (findability, accessibility, interoperability and reusability) principles to these resources has the potential to improve their discoverability, accessibility, and usability and ultimately promote a more effective climate adaptation planning in Portugal. This study explores the state of the art of scientific research on climate change adaptation in Portugal since 2010, to assess strengths and limitations of knowledge, identifying key priority areas for future research and the “FAIRification” of these resources. As the frequency and intensity of extreme heat events in Portugal increases, this study focused on heat-related hazards, and associated impacts. A systematic search was performed across Scopus and ISI Web of Science to identify relevant peer-reviewed articles between January 2010 and May 2025. The resulting publications were analysed by geographical scope, adaptation sectorial focus, knowledge sector, climate hazard and CCA needs. Alignment of the current scientific outputs with FAIR principles was also analysed. A total of 217 articles were reviewed. Research was mostly performed at the city or national level (37% each) and the majority of adaptation actions were done under the agricultural or urban sectors (19% and 26%, respectively). Research was multidisciplinary, covering different knowledge sectors, from health impacts to biodiversity, buildings and construction, and often included several knowledge sectors in the same article. All articles presented accessible metadata but only one made its scripts and data available for further replication. Results show that scientific research on heat-related climate change adaptation in Portugal is diverse and covers many knowledge areas, but the availability of its data needs improvement. Further work will include policy FAIR assessment of policy documents and datasets. This work was developed under the Horizon Europe project FAIR2ADAPT. application/ld+json https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94 FAIR adaptation climate change heat Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal MANUAL Simões, Francisca, Ines Gomes Marques, and Tiago Capela Lourenço. "Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal." ROHub. Oct 13 ,2025. https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94. 10.24424/xq9z-p873 1057305 https://api.rohub.org/api/resources/a6c04f4c-0a9f-4b8d-8492-96a06dba7808/download/ 2025-10-13 11:48:29.771773+00:00 2025-10-14 08:33:10.492170+00:00 application/pdf Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal 2025-10-13 11:48:29.771773+00:00 203263 https://api.rohub.org/api/resources/b1a0d3cc-179c-4077-9d29-f14b8bada1d7/download/ 2025-10-13 11:20:07.788069+00:00 2025-10-13 11:20:08.689183+00:00 image/png Captura de ecrã 2025-10-13 121949.png 2025-10-13 11:20:07.788069+00:00 398943 https://api.rohub.org/api/resources/ebc84d30-9700-471e-ae2f-d04486f18c8d/download/ 2025-10-13 11:18:02.624724+00:00 2025-10-13 11:18:03.764253+00:00 image/png NatAdaptHub.png 2025-10-13 11:18:02.624724+00:00 metadata 11.924119241192415 4.4 availability 10.569105691056912 3.9 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences Portugal 20.05420054200542 7.4 data 16.260162601626018 6.0 meteorology 20.979020979020977 3.0 Climate change Environment/Climate change stakeholder 5.228758169934641 4.0 Portugal heat event 12.602739726027396 4.6 Since then, many resources (e.g. policy documents, scientific articles, data sets) relevant for national adaptation have been published, yet often remain unknown to, or inaccessible, for the multiple stakeholders that comprise the climate adaptation community (CCA) in Portugal. 31.362467866323907 12.2 Weather Weather Portugal 14.640522875816993 11.2 from 15 years scientific research 11.924119241192415 4.4 between Jan-2010 and May-2025 Information Sciences Institute earth sciences 100.0 0.9895771741867065 article 13.279132791327916 4.9 sector 7.0588235294117645 5.4 application of fair 14.794520547945206 5.4 10-Oct-12-2025 meteorology and climatology 100.0 0.8513408899307251 computer science 20.27972027972028 2.9 Results show that scientific research on heat-related climate change adaptation in Portugal is diverse and covers many knowledge areas, but the availability of its data needs improvement. 30.07712082262211 11.7 assessment 4.967320261437909 3.8 climate 8.235294117647058 6.3 knowledge sector 21.643835616438356 7.9 availability 12.026143790849671 9.2 in 2010 data 11.895424836601308 9.1 heat 4.836601307189542 3.7 Science and technology Science and technology climate change adaptation in Portugal 11.780821917808218 4.3 geosciences 100.0 0.8513408899307251 metadata 8.758169934640524 6.7 climate adaptation community 22.739726027397264 8.3 scientific research 8.627450980392156 6.6 ecology 31.468531468531467 4.5 dataset 13.72549019607843 10.5 since 2010 dataset 15.989159891598916 5.9 heat extreme 16.438356164383563 6.0 database 27.27272727272727 3.9 atmospheric sciences 100.0 0.9895771741867065 Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal. 38.56041131105398 15.0 ce3c@ciencias.ulisboa.pt CE3C - Centre for Ecology, Evolution and Environmental Changes francisca.simoes@edu.ulisboa.pt Francisca Simões Environmental research 10.3030/101188256 European Commission 10.3030/101188256 European Commission Anne Fouilloux https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Hamburg_urban_data_portal_WFS.ipynb 2025-10-07 20:09:09.230244+00:00 2025-10-07 20:14:08.069536+00:00 Visualizing Generalized Flood Areas for HQ100 Event and relate to an existing flooding event. Flood analysis with JupterGIS 2025-10-07 20:09:09.230244+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/static/flood_in_saarland_with_jqgis.png 2025-10-07 20:09:06.171136+00:00 2025-10-07 20:14:05.823700+00:00 This resource has this description image/png Image - updated 2025-10-07 20:09:06.171136+00:00 04jcwf484 Nordic e-Infrastructure Collaboration 101188256 FAIR2Adapt POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1 daf5e7a5-2cc7-4899-8d2b-3fac4779a419 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 0 https://api.rohub.org/api/ros/55a1b422-f279-4765-9ba7-d27268059844/crate/download/ 2025-10-07 20:07:57.245814+00:00 2025-10-16 11:10:27.079384+00:00 2025-10-07 20:07:57.245814+00:00 This Research Object is an example for FAIR2Adapt Case Study 2 application/ld+json https://w3id.org/ro-id/55a1b422-f279-4765-9ba7-d27268059844 FAIR2Adapt RO-Crate with Jupyter Notebook MANUAL Fouilloux, Anne. "FAIR2Adapt RO-Crate with Jupyter Notebook." ROHub. Oct 07 ,2025. https://w3id.org/ro-id/55a1b422-f279-4765-9ba7-d27268059844. POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) biblio output input tool 907 https://api.rohub.org/api/resources/814cf173-b4c3-4f46-a7e8-d6edae4cf14f/download/ 2025-10-07 20:08:57.775768+00:00 2025-10-07 20:08:59.321734+00:00 image/png Image to illustrate my case study 2025-10-07 20:08:57.775768+00:00 case study 13.456090651558075 9.5 example for FAIR2Adapt case study 2 8.316633266533067 8.3 earth resources and remote sensing 100.0 0.8493164777755737 This Research Object is an example for FAIR2Adapt Case Study 2 65.76576576576576 65.7 object 15.59536354056902 14.8 research 17.91359325605901 17.0 Ro-crate with Jupyter Notebook 17.935871743486974 17.9 geosciences 100.0 0.8493164777755737 Language Arts, culture and entertainment/Culture/Language Food and drink Lifestyle and leisure/Lifestyle/Food and drink crate 20.538243626062325 14.5 Ro 10.326659641728135 9.8 research 24.36260623229462 17.2 atmospheric sciences 100.0 0.9335481524467468 FAIR2Adapt 21.390937829293993 20.3 Food Economy, business and finance/Economic sector/Consumer goods/Food research object 73.44689378757515 73.3 crate 15.700737618545837 14.9 case study 2 0.30060120240480964 0.3 FAIR2Adapt RO-Crate with Jupyter Notebook. 34.234234234234236 34.2 example 7.36543909348442 5.2 Ro 13.597733711048159 9.6 earth sciences 100.0 0.9335481524467468 case study 10.010537407797681 9.5 aim 20.67988668555241 14.6 Jupyter notebook 9.062170706006322 8.6 Instytut Chemii Bioorganicznej PAN, Poznanskie Centrum Superkomputerowo-Sieciowe PSNC Environmental research 10.3030/101188256 European Commission 10.3030/101188256 European Commission Anne Fouilloux https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Hamburg_urban_data_portal_WFS.ipynb 2025-10-07 20:09:09.230244+00:00 2025-10-07 20:14:08.069536+00:00 Visualizing Generalized Flood Areas for HQ100 Event and relate to an existing flooding event. Flood analysis with JupterGIS 2025-10-07 20:09:09.230244+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/static/flood_in_saarland_with_jqgis.png 2025-10-07 20:09:06.171136+00:00 2025-10-07 20:14:05.823700+00:00 This resource has this description image/png Image - updated 2025-10-07 20:09:06.171136+00:00 04jcwf484 Nordic e-Infrastructure Collaboration 101188256 FAIR2Adapt POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1 9ff513c5-c403-42bf-95dc-aadc8a73c36d POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 0 https://api.rohub.org/api/ros/55a1b422-f279-4765-9ba7-d27268059844/crate/download/ 2025-10-07 20:07:57.245814+00:00 2025-10-16 11:10:27.079384+00:00 2025-10-07 20:07:57.245814+00:00 This Research Object is an example for FAIR2Adapt Case Study 2 application/ld+json https://w3id.org/ro-id/55a1b422-f279-4765-9ba7-d27268059844 FAIR2Adapt RO-Crate with Jupyter Notebook MANUAL Fouilloux, Anne. "FAIR2Adapt RO-Crate with Jupyter Notebook." ROHub. Oct 07 ,2025. https://w3id.org/ro-id/55a1b422-f279-4765-9ba7-d27268059844. POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) biblio output input tool 907 https://api.rohub.org/api/resources/814cf173-b4c3-4f46-a7e8-d6edae4cf14f/download/ 2025-10-07 20:08:57.775768+00:00 2025-10-07 20:08:59.321734+00:00 image/png Image to illustrate my case study 2025-10-07 20:08:57.775768+00:00 case study 13.456090651558075 9.5 example for FAIR2Adapt case study 2 8.316633266533067 8.3 earth resources and remote sensing 100.0 0.8493164777755737 This Research Object is an example for FAIR2Adapt Case Study 2 65.76576576576576 65.7 object 15.59536354056902 14.8 research 17.91359325605901 17.0 Ro-crate with Jupyter Notebook 17.935871743486974 17.9 geosciences 100.0 0.8493164777755737 Language Arts, culture and entertainment/Culture/Language Food and drink Lifestyle and leisure/Lifestyle/Food and drink crate 20.538243626062325 14.5 Ro 10.326659641728135 9.8 research 24.36260623229462 17.2 atmospheric sciences 100.0 0.9335481524467468 FAIR2Adapt 21.390937829293993 20.3 Food Economy, business and finance/Economic sector/Consumer goods/Food research object 73.44689378757515 73.3 crate 15.700737618545837 14.9 case study 2 0.30060120240480964 0.3 FAIR2Adapt RO-Crate with Jupyter Notebook. 34.234234234234236 34.2 example 7.36543909348442 5.2 Ro 13.597733711048159 9.6 earth sciences 100.0 0.9335481524467468 case study 10.010537407797681 9.5 aim 20.67988668555241 14.6 Jupyter notebook 9.062170706006322 8.6 Instytut Chemii Bioorganicznej PAN, Poznanskie Centrum Superkomputerowo-Sieciowe PSNC Environmental research 10.3030/101188256 European Commission 10.3030/101188256 European Commission Anne Fouilloux https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Hamburg_urban_data_portal_WFS.ipynb 2025-10-07 20:09:09.230244+00:00 2025-10-07 20:14:08.069536+00:00 Visualizing Generalized Flood Areas for HQ100 Event and relate to an existing flooding event. Flood analysis with JupterGIS 2025-10-07 20:09:09.230244+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/static/flood_in_saarland_with_jqgis.png 2025-10-07 20:09:06.171136+00:00 2025-10-07 20:14:05.823700+00:00 This resource has this description image/png Image - updated 2025-10-07 20:09:06.171136+00:00 04jcwf484 Nordic e-Infrastructure Collaboration 101188256 FAIR2Adapt POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1 3b1616f2-fc35-4333-b3e8-bbfcd86cf0a7 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 0 https://api.rohub.org/api/ros/55a1b422-f279-4765-9ba7-d27268059844/crate/download/ 2025-10-07 20:07:57.245814+00:00 2025-10-16 11:10:27.079384+00:00 2025-10-07 20:07:57.245814+00:00 This Research Object is an example for FAIR2Adapt Case Study 2 application/ld+json https://w3id.org/ro-id/55a1b422-f279-4765-9ba7-d27268059844 FAIR2Adapt RO-Crate with Jupyter Notebook MANUAL Fouilloux, Anne. "FAIR2Adapt RO-Crate with Jupyter Notebook." ROHub. Oct 07 ,2025. https://w3id.org/ro-id/55a1b422-f279-4765-9ba7-d27268059844. POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) biblio output input tool 907 https://api.rohub.org/api/resources/814cf173-b4c3-4f46-a7e8-d6edae4cf14f/download/ 2025-10-07 20:08:57.775768+00:00 2025-10-07 20:08:59.321734+00:00 image/png Image to illustrate my case study 2025-10-07 20:08:57.775768+00:00 case study 13.456090651558075 9.5 example for FAIR2Adapt case study 2 8.316633266533067 8.3 earth resources and remote sensing 100.0 0.8493164777755737 This Research Object is an example for FAIR2Adapt Case Study 2 65.76576576576576 65.7 object 15.59536354056902 14.8 research 17.91359325605901 17.0 Ro-crate with Jupyter Notebook 17.935871743486974 17.9 geosciences 100.0 0.8493164777755737 Language Arts, culture and entertainment/Culture/Language Food and drink Lifestyle and leisure/Lifestyle/Food and drink crate 20.538243626062325 14.5 Ro 10.326659641728135 9.8 research 24.36260623229462 17.2 atmospheric sciences 100.0 0.9335481524467468 FAIR2Adapt 21.390937829293993 20.3 Food Economy, business and finance/Economic sector/Consumer goods/Food research object 73.44689378757515 73.3 crate 15.700737618545837 14.9 case study 2 0.30060120240480964 0.3 FAIR2Adapt RO-Crate with Jupyter Notebook. 34.234234234234236 34.2 example 7.36543909348442 5.2 Ro 13.597733711048159 9.6 earth sciences 100.0 0.9335481524467468 case study 10.010537407797681 9.5 aim 20.67988668555241 14.6 Jupyter notebook 9.062170706006322 8.6 Instytut Chemii Bioorganicznej PAN, Poznanskie Centrum Superkomputerowo-Sieciowe PSNC Environmental research 10.3030/101188256 European Commission 10.3030/101188256 European Commission Anne Fouilloux https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Hamburg_urban_data_portal_WFS.ipynb 2025-10-07 20:09:09.230244+00:00 2025-10-07 20:14:08.069536+00:00 Visualizing Generalized Flood Areas for HQ100 Event and relate to an existing flooding event. Flood analysis with JupterGIS 2025-10-07 20:09:09.230244+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/static/flood_in_saarland_with_jqgis.png 2025-10-07 20:09:06.171136+00:00 2025-10-07 20:14:05.823700+00:00 This resource has this description image/png Image - updated 2025-10-07 20:09:06.171136+00:00 04jcwf484 Nordic e-Infrastructure Collaboration 101188256 FAIR2Adapt POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1 b9dc9ee5-9e9f-4a3e-a0a5-5f29660998c6 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 0 https://api.rohub.org/api/ros/55a1b422-f279-4765-9ba7-d27268059844/crate/download/ 2025-10-07 20:07:57.245814+00:00 2025-10-16 11:10:27.079384+00:00 2025-10-07 20:07:57.245814+00:00 This Research Object is an example for FAIR2Adapt Case Study 2 application/ld+json https://w3id.org/ro-id/55a1b422-f279-4765-9ba7-d27268059844 FAIR2Adapt RO-Crate with Jupyter Notebook MANUAL Fouilloux, Anne. "FAIR2Adapt RO-Crate with Jupyter Notebook." ROHub. Oct 07 ,2025. https://w3id.org/ro-id/55a1b422-f279-4765-9ba7-d27268059844. POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) biblio output input tool 907 https://api.rohub.org/api/resources/814cf173-b4c3-4f46-a7e8-d6edae4cf14f/download/ 2025-10-07 20:08:57.775768+00:00 2025-10-07 20:08:59.321734+00:00 image/png Image to illustrate my case study 2025-10-07 20:08:57.775768+00:00 case study 13.456090651558075 9.5 example for FAIR2Adapt case study 2 8.316633266533067 8.3 earth resources and remote sensing 100.0 0.8493164777755737 This Research Object is an example for FAIR2Adapt Case Study 2 65.76576576576576 65.7 object 15.59536354056902 14.8 research 17.91359325605901 17.0 Ro-crate with Jupyter Notebook 17.935871743486974 17.9 geosciences 100.0 0.8493164777755737 Language Arts, culture and entertainment/Culture/Language Food and drink Lifestyle and leisure/Lifestyle/Food and drink crate 20.538243626062325 14.5 Ro 10.326659641728135 9.8 research 24.36260623229462 17.2 atmospheric sciences 100.0 0.9335481524467468 FAIR2Adapt 21.390937829293993 20.3 Food Economy, business and finance/Economic sector/Consumer goods/Food research object 73.44689378757515 73.3 crate 15.700737618545837 14.9 case study 2 0.30060120240480964 0.3 FAIR2Adapt RO-Crate with Jupyter Notebook. 34.234234234234236 34.2 example 7.36543909348442 5.2 Ro 13.597733711048159 9.6 earth sciences 100.0 0.9335481524467468 case study 10.010537407797681 9.5 aim 20.67988668555241 14.6 Jupyter notebook 9.062170706006322 8.6 Instytut Chemii Bioorganicznej PAN, Poznanskie Centrum Superkomputerowo-Sieciowe PSNC Environmental research 0d2805a5-008a-41aa-9c5d-53fed3395b45 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1 0 https://api.rohub.org/api/ros/8a351029-86a8-4e90-a9d1-a67d45d63656/crate/download/ 2025-10-08 08:39:21.885634+00:00 2025-10-16 11:10:21.642786+00:00 2025-10-08 08:39:21.885634+00:00 This Research Object is an example for FAIR2Adapt Case Study 2 application/ld+json https://w3id.org/ro-id/8a351029-86a8-4e90-a9d1-a67d45d63656 FAIR2Adapt RO-Crate with Jupyter Notebook MANUAL Fouilloux, Anne. "FAIR2Adapt RO-Crate with Jupyter Notebook." ROHub. Oct 08 ,2025. https://w3id.org/ro-id/8a351029-86a8-4e90-a9d1-a67d45d63656. Anne Fouilloux https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Flood_protection_line_Saarland.ipynb 2025-10-08 08:47:29.592762+00:00 2025-10-08 08:47:30.239969+00:00 Visualizing Generalized Flood Areas for HQ100 Event and relate to an existing flooding event. Flood analysis with JupterGIS 2025-10-08 08:47:29.592762+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/static/flood_in_saarland_with_jqgis.png 2025-10-08 08:46:18.994606+00:00 2025-10-08 08:46:19.636455+00:00 Example for FAIR2Adapt training on RO-Crate and ROHub image/png flood in saarland with JupyterGIS 2025-10-08 08:46:18.994606+00:00 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) biblio tool input output 907 https://api.rohub.org/api/resources/4d1eee3a-9631-4d76-a15a-ab1de329fde1/download/ 2025-10-08 08:44:48.739835+00:00 2025-10-08 08:44:50.121842+00:00 image/png Image to illustrate my case study 2025-10-08 08:44:48.739835+00:00 earth sciences 100.0 0.9335481524467468 geosciences 100.0 0.8493164777755737 This Research Object is an example for FAIR2Adapt Case Study 2 65.76576576576576 65.7 case study 13.456090651558075 9.5 crate 15.700737618545837 14.9 research 17.91359325605901 17.0 FAIR2Adapt RO-Crate with Jupyter Notebook. 34.234234234234236 34.2 Ro-crate with Jupyter Notebook 17.935871743486974 17.9 object 15.59536354056902 14.8 FAIR2Adapt 21.390937829293993 20.3 example for FAIR2Adapt case study 2 8.316633266533067 8.3 earth resources and remote sensing 100.0 0.8493164777755737 Ro 10.326659641728135 9.8 crate 20.538243626062325 14.5 case study 2 0.30060120240480964 0.3 Ro 13.597733711048159 9.6 research object 73.44689378757515 73.3 Jupyter notebook 9.062170706006322 8.6 case study 10.010537407797681 9.5 example 7.36543909348442 5.2 research 24.36260623229462 17.2 atmospheric sciences 100.0 0.9335481524467468 aim 20.67988668555241 14.6 Food and drink Lifestyle and leisure/Lifestyle/Food and drink Language Arts, culture and entertainment/Culture/Language Food Economy, business and finance/Economic sector/Consumer goods/Food Environmental research POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1 801ae61a-b7ce-4de8-8fbe-58fbe5517256 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 0 https://api.rohub.org/api/ros/8a351029-86a8-4e90-a9d1-a67d45d63656/crate/download/ 2025-10-08 08:39:21.885634+00:00 2025-10-16 11:10:21.642786+00:00 2025-10-08 08:39:21.885634+00:00 This Research Object is an example for FAIR2Adapt Case Study 2 application/ld+json https://w3id.org/ro-id/8a351029-86a8-4e90-a9d1-a67d45d63656 FAIR2Adapt RO-Crate with Jupyter Notebook MANUAL Fouilloux, Anne. "FAIR2Adapt RO-Crate with Jupyter Notebook." ROHub. Oct 08 ,2025. https://w3id.org/ro-id/8a351029-86a8-4e90-a9d1-a67d45d63656. Anne Fouilloux https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Flood_protection_line_Saarland.ipynb 2025-10-08 08:47:29.592762+00:00 2025-10-08 08:47:30.239969+00:00 Visualizing Generalized Flood Areas for HQ100 Event and relate to an existing flooding event. Flood analysis with JupterGIS 2025-10-08 08:47:29.592762+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/static/flood_in_saarland_with_jqgis.png 2025-10-08 08:46:18.994606+00:00 2025-10-08 08:46:19.636455+00:00 Example for FAIR2Adapt training on RO-Crate and ROHub image/png flood in saarland with JupyterGIS 2025-10-08 08:46:18.994606+00:00 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) biblio tool input output 907 https://api.rohub.org/api/resources/4d1eee3a-9631-4d76-a15a-ab1de329fde1/download/ 2025-10-08 08:44:48.739835+00:00 2025-10-08 08:44:50.121842+00:00 image/png Image to illustrate my case study 2025-10-08 08:44:48.739835+00:00 earth sciences 100.0 0.9335481524467468 geosciences 100.0 0.8493164777755737 This Research Object is an example for FAIR2Adapt Case Study 2 65.76576576576576 65.7 case study 13.456090651558075 9.5 crate 15.700737618545837 14.9 research 17.91359325605901 17.0 FAIR2Adapt RO-Crate with Jupyter Notebook. 34.234234234234236 34.2 Ro-crate with Jupyter Notebook 17.935871743486974 17.9 object 15.59536354056902 14.8 FAIR2Adapt 21.390937829293993 20.3 example for FAIR2Adapt case study 2 8.316633266533067 8.3 earth resources and remote sensing 100.0 0.8493164777755737 Ro 10.326659641728135 9.8 crate 20.538243626062325 14.5 case study 2 0.30060120240480964 0.3 Ro 13.597733711048159 9.6 research object 73.44689378757515 73.3 Jupyter notebook 9.062170706006322 8.6 case study 10.010537407797681 9.5 example 7.36543909348442 5.2 research 24.36260623229462 17.2 atmospheric sciences 100.0 0.9335481524467468 aim 20.67988668555241 14.6 Food and drink Lifestyle and leisure/Lifestyle/Food and drink Language Arts, culture and entertainment/Culture/Language Food Economy, business and finance/Economic sector/Consumer goods/Food Environmental research POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1 66e5b4a5-7a20-4ca9-b3e4-68a761b785ec POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) 0 https://api.rohub.org/api/ros/8a351029-86a8-4e90-a9d1-a67d45d63656/crate/download/ 2025-10-08 08:39:21.885634+00:00 2025-10-16 11:10:21.642786+00:00 2025-10-08 08:39:21.885634+00:00 This Research Object is an example for FAIR2Adapt Case Study 2 application/ld+json https://w3id.org/ro-id/8a351029-86a8-4e90-a9d1-a67d45d63656 FAIR2Adapt RO-Crate with Jupyter Notebook MANUAL Fouilloux, Anne. "FAIR2Adapt RO-Crate with Jupyter Notebook." ROHub. Oct 08 ,2025. https://w3id.org/ro-id/8a351029-86a8-4e90-a9d1-a67d45d63656. Anne Fouilloux https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Flood_protection_line_Saarland.ipynb 2025-10-08 08:47:29.592762+00:00 2025-10-08 08:47:30.239969+00:00 Visualizing Generalized Flood Areas for HQ100 Event and relate to an existing flooding event. Flood analysis with JupterGIS 2025-10-08 08:47:29.592762+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/static/flood_in_saarland_with_jqgis.png 2025-10-08 08:46:18.994606+00:00 2025-10-08 08:46:19.636455+00:00 Example for FAIR2Adapt training on RO-Crate and ROHub image/png flood in saarland with JupyterGIS 2025-10-08 08:46:18.994606+00:00 POLYGON ((6.31 49.1, 6.31 49.64, 7.41 49.64, 7.41 49.1, 6.31 49.1)) biblio tool input output 907 https://api.rohub.org/api/resources/4d1eee3a-9631-4d76-a15a-ab1de329fde1/download/ 2025-10-08 08:44:48.739835+00:00 2025-10-08 08:44:50.121842+00:00 image/png Image to illustrate my case study 2025-10-08 08:44:48.739835+00:00 earth sciences 100.0 0.9335481524467468 geosciences 100.0 0.8493164777755737 This Research Object is an example for FAIR2Adapt Case Study 2 65.76576576576576 65.7 case study 13.456090651558075 9.5 crate 15.700737618545837 14.9 research 17.91359325605901 17.0 FAIR2Adapt RO-Crate with Jupyter Notebook. 34.234234234234236 34.2 Ro-crate with Jupyter Notebook 17.935871743486974 17.9 object 15.59536354056902 14.8 FAIR2Adapt 21.390937829293993 20.3 example for FAIR2Adapt case study 2 8.316633266533067 8.3 earth resources and remote sensing 100.0 0.8493164777755737 Ro 10.326659641728135 9.8 crate 20.538243626062325 14.5 case study 2 0.30060120240480964 0.3 Ro 13.597733711048159 9.6 research object 73.44689378757515 73.3 Jupyter notebook 9.062170706006322 8.6 case study 10.010537407797681 9.5 example 7.36543909348442 5.2 research 24.36260623229462 17.2 atmospheric sciences 100.0 0.9335481524467468 aim 20.67988668555241 14.6 Food and drink Lifestyle and leisure/Lifestyle/Food and drink Language Arts, culture and entertainment/Culture/Language Food Economy, business and finance/Economic sector/Consumer goods/Food Applied sciences Biology Climatology Geographical information system Earth observation 0 https://api.rohub.org/api/ros/302b4ebf-db38-49d5-8ab4-4561181f4e94/crate/download/ 2025-10-13 11:12:49.327063+00:00 2025-10-20 13:33:34.491167+00:00 2025-10-13 11:12:49.327063+00:00 Presentation at the CE3C Annual Meeting, Azores - Portugal *10-12 October 2025* The first Portuguese National Strategy for Adaptation to Climate Change was adopted in 2010, aiming to adjust climate and other sectoral policies, and to increase the countries’ resilience to observed and projected climate change impacts. Since then, many resources (e.g. policy documents, scientific articles, data sets) relevant for national adaptation have been published, yet often remain unknown to, or inaccessible, for the multiple stakeholders that comprise the climate adaptation community (CCA) in Portugal. The application of FAIR (findability, accessibility, interoperability and reusability) principles to these resources has the potential to improve their discoverability, accessibility, and usability and ultimately promote a more effective climate adaptation planning in Portugal. This study explores the state of the art of scientific research on climate change adaptation in Portugal since 2010, to assess strengths and limitations of knowledge, identifying key priority areas for future research and the “FAIRification” of these resources. As the frequency and intensity of extreme heat events in Portugal increases, this study focused on heat-related hazards, and associated impacts. A systematic search was performed across Scopus and ISI Web of Science to identify relevant peer-reviewed articles between January 2010 and May 2025. The resulting publications were analysed by geographical scope, adaptation sectorial focus, knowledge sector, climate hazard and CCA needs. Alignment of the current scientific outputs with FAIR principles was also analysed. A total of 217 articles were reviewed. Research was mostly performed at the city or national level (37% each) and the majority of adaptation actions were done under the agricultural or urban sectors (19% and 26%, respectively). Research was multidisciplinary, covering different knowledge sectors, from health impacts to biodiversity, buildings and construction, and often included several knowledge sectors in the same article. All articles presented accessible metadata but only one made its scripts and data available for further replication. Results show that scientific research on heat-related climate change adaptation in Portugal is diverse and covers many knowledge areas, but the availability of its data needs improvement. Further work will include policy FAIR assessment of policy documents and datasets. This work was developed under the Horizon Europe project FAIR2ADAPT. application/ld+json https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94 FAIR adaptation climate change heat Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal MANUAL Simões, Francisca, Ines Gomes Marques, and Tiago Capela Lourenço. "Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal." ROHub. Oct 13 ,2025. https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94. Centre for Ecology, Evolution and Environmental Changes, University of Lisbon igmarques@fc.ul.pt Ines Gomes Marques 0000-0002-2104-3187 ClimRisk, CE3C, Faculty of Sciences, U Lisbon tcapela@fc.ul.pt Tiago Capela Lourenço 0000-0002-8796-5993 10.24424/xq9z-p873 1057305 https://api.rohub.org/api/resources/a6c04f4c-0a9f-4b8d-8492-96a06dba7808/download/ 2025-10-13 11:48:29.771773+00:00 2025-10-14 08:33:10.492170+00:00 application/pdf Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal 2025-10-13 11:48:29.771773+00:00 203263 https://api.rohub.org/api/resources/b1a0d3cc-179c-4077-9d29-f14b8bada1d7/download/ 2025-10-13 11:20:07.788069+00:00 2025-10-13 11:20:08.689183+00:00 image/png Captura de ecrã 2025-10-13 121949.png 2025-10-13 11:20:07.788069+00:00 398943 https://api.rohub.org/api/resources/ebc84d30-9700-471e-ae2f-d04486f18c8d/download/ 2025-10-13 11:18:02.624724+00:00 2025-10-13 11:18:03.764253+00:00 image/png NatAdaptHub.png 2025-10-13 11:18:02.624724+00:00 metadata 11.924119241192415 4.4 availability 10.569105691056912 3.9 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences Portugal 20.05420054200542 7.4 data 16.260162601626018 6.0 meteorology 20.979020979020977 3.0 Climate change Environment/Climate change stakeholder 5.228758169934641 4.0 Portugal heat event 12.602739726027396 4.6 Since then, many resources (e.g. policy documents, scientific articles, data sets) relevant for national adaptation have been published, yet often remain unknown to, or inaccessible, for the multiple stakeholders that comprise the climate adaptation community (CCA) in Portugal. 31.362467866323907 12.2 Weather Weather Portugal 14.640522875816993 11.2 from 15 years scientific research 11.924119241192415 4.4 between Jan-2010 and May-2025 Information Sciences Institute earth sciences 100.0 0.9895771741867065 article 13.279132791327916 4.9 sector 7.0588235294117645 5.4 application of fair 14.794520547945206 5.4 10-Oct-12-2025 meteorology and climatology 100.0 0.8513408899307251 computer science 20.27972027972028 2.9 Results show that scientific research on heat-related climate change adaptation in Portugal is diverse and covers many knowledge areas, but the availability of its data needs improvement. 30.07712082262211 11.7 assessment 4.967320261437909 3.8 climate 8.235294117647058 6.3 knowledge sector 21.643835616438356 7.9 availability 12.026143790849671 9.2 in 2010 data 11.895424836601308 9.1 heat 4.836601307189542 3.7 Science and technology Science and technology climate change adaptation in Portugal 11.780821917808218 4.3 geosciences 100.0 0.8513408899307251 metadata 8.758169934640524 6.7 climate adaptation community 22.739726027397264 8.3 scientific research 8.627450980392156 6.6 ecology 31.468531468531467 4.5 dataset 13.72549019607843 10.5 since 2010 dataset 15.989159891598916 5.9 heat extreme 16.438356164383563 6.0 database 27.27272727272727 3.9 atmospheric sciences 100.0 0.9895771741867065 Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal. 38.56041131105398 15.0 ce3c@ciencias.ulisboa.pt CE3C - Centre for Ecology, Evolution and Environmental Changes francisca.simoes@edu.ulisboa.pt Francisca Simões Applied sciences Biology Climatology Geographical information system Earth observation 0 https://api.rohub.org/api/ros/302b4ebf-db38-49d5-8ab4-4561181f4e94/crate/download/ 2025-10-13 11:12:49.327063+00:00 2025-10-20 13:33:34.491167+00:00 2025-10-13 11:12:49.327063+00:00 Presentation at the CE3C Annual Meeting, Azores - Portugal *10-12 October 2025* The first Portuguese National Strategy for Adaptation to Climate Change was adopted in 2010, aiming to adjust climate and other sectoral policies, and to increase the countries’ resilience to observed and projected climate change impacts. Since then, many resources (e.g. policy documents, scientific articles, data sets) relevant for national adaptation have been published, yet often remain unknown to, or inaccessible, for the multiple stakeholders that comprise the climate adaptation community (CCA) in Portugal. The application of FAIR (findability, accessibility, interoperability and reusability) principles to these resources has the potential to improve their discoverability, accessibility, and usability and ultimately promote a more effective climate adaptation planning in Portugal. This study explores the state of the art of scientific research on climate change adaptation in Portugal since 2010, to assess strengths and limitations of knowledge, identifying key priority areas for future research and the “FAIRification” of these resources. As the frequency and intensity of extreme heat events in Portugal increases, this study focused on heat-related hazards, and associated impacts. A systematic search was performed across Scopus and ISI Web of Science to identify relevant peer-reviewed articles between January 2010 and May 2025. The resulting publications were analysed by geographical scope, adaptation sectorial focus, knowledge sector, climate hazard and CCA needs. Alignment of the current scientific outputs with FAIR principles was also analysed. A total of 217 articles were reviewed. Research was mostly performed at the city or national level (37% each) and the majority of adaptation actions were done under the agricultural or urban sectors (19% and 26%, respectively). Research was multidisciplinary, covering different knowledge sectors, from health impacts to biodiversity, buildings and construction, and often included several knowledge sectors in the same article. All articles presented accessible metadata but only one made its scripts and data available for further replication. Results show that scientific research on heat-related climate change adaptation in Portugal is diverse and covers many knowledge areas, but the availability of its data needs improvement. Further work will include policy FAIR assessment of policy documents and datasets. This work was developed under the Horizon Europe project FAIR2ADAPT. application/ld+json https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94 FAIR adaptation climate change heat Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal MANUAL Simões, Francisca, Ines Gomes Marques, and Tiago Capela Lourenço. "Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal." ROHub. Oct 13 ,2025. https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94. Centre for Ecology, Evolution and Environmental Changes, University of Lisbon igmarques@fc.ul.pt Ines Gomes Marques 0000-0002-2104-3187 ClimRisk, CE3C, Faculty of Sciences, U Lisbon tcapela@fc.ul.pt Tiago Capela Lourenço 0000-0002-8796-5993 10.24424/xq9z-p873 1057305 https://api.rohub.org/api/resources/a6c04f4c-0a9f-4b8d-8492-96a06dba7808/download/ 2025-10-13 11:48:29.771773+00:00 2025-10-14 08:33:10.492170+00:00 application/pdf Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal 2025-10-13 11:48:29.771773+00:00 203263 https://api.rohub.org/api/resources/b1a0d3cc-179c-4077-9d29-f14b8bada1d7/download/ 2025-10-13 11:20:07.788069+00:00 2025-10-13 11:20:08.689183+00:00 image/png Captura de ecrã 2025-10-13 121949.png 2025-10-13 11:20:07.788069+00:00 398943 https://api.rohub.org/api/resources/ebc84d30-9700-471e-ae2f-d04486f18c8d/download/ 2025-10-13 11:18:02.624724+00:00 2025-10-13 11:18:03.764253+00:00 image/png NatAdaptHub.png 2025-10-13 11:18:02.624724+00:00 metadata 11.924119241192415 4.4 availability 10.569105691056912 3.9 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences Portugal 20.05420054200542 7.4 data 16.260162601626018 6.0 meteorology 20.979020979020977 3.0 Climate change Environment/Climate change stakeholder 5.228758169934641 4.0 Portugal heat event 12.602739726027396 4.6 Since then, many resources (e.g. policy documents, scientific articles, data sets) relevant for national adaptation have been published, yet often remain unknown to, or inaccessible, for the multiple stakeholders that comprise the climate adaptation community (CCA) in Portugal. 31.362467866323907 12.2 Weather Weather Portugal 14.640522875816993 11.2 from 15 years scientific research 11.924119241192415 4.4 between Jan-2010 and May-2025 Information Sciences Institute earth sciences 100.0 0.9895771741867065 article 13.279132791327916 4.9 sector 7.0588235294117645 5.4 application of fair 14.794520547945206 5.4 10-Oct-12-2025 meteorology and climatology 100.0 0.8513408899307251 computer science 20.27972027972028 2.9 Results show that scientific research on heat-related climate change adaptation in Portugal is diverse and covers many knowledge areas, but the availability of its data needs improvement. 30.07712082262211 11.7 assessment 4.967320261437909 3.8 climate 8.235294117647058 6.3 knowledge sector 21.643835616438356 7.9 availability 12.026143790849671 9.2 in 2010 data 11.895424836601308 9.1 heat 4.836601307189542 3.7 Science and technology Science and technology climate change adaptation in Portugal 11.780821917808218 4.3 geosciences 100.0 0.8513408899307251 metadata 8.758169934640524 6.7 climate adaptation community 22.739726027397264 8.3 scientific research 8.627450980392156 6.6 ecology 31.468531468531467 4.5 dataset 13.72549019607843 10.5 since 2010 dataset 15.989159891598916 5.9 heat extreme 16.438356164383563 6.0 database 27.27272727272727 3.9 atmospheric sciences 100.0 0.9895771741867065 Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal. 38.56041131105398 15.0 ce3c@ciencias.ulisboa.pt CE3C - Centre for Ecology, Evolution and Environmental Changes francisca.simoes@edu.ulisboa.pt Francisca Simões Applied sciences Biology Climatology Geographical information system Earth observation 0 https://api.rohub.org/api/ros/302b4ebf-db38-49d5-8ab4-4561181f4e94/crate/download/ 2025-10-13 11:12:49.327063+00:00 2025-10-20 13:33:34.491167+00:00 2025-10-13 11:12:49.327063+00:00 Presentation at the CE3C Annual Meeting, Azores - Portugal *10-12 October 2025* The first Portuguese National Strategy for Adaptation to Climate Change was adopted in 2010, aiming to adjust climate and other sectoral policies, and to increase the countries’ resilience to observed and projected climate change impacts. Since then, many resources (e.g. policy documents, scientific articles, data sets) relevant for national adaptation have been published, yet often remain unknown to, or inaccessible, for the multiple stakeholders that comprise the climate adaptation community (CCA) in Portugal. The application of FAIR (findability, accessibility, interoperability and reusability) principles to these resources has the potential to improve their discoverability, accessibility, and usability and ultimately promote a more effective climate adaptation planning in Portugal. This study explores the state of the art of scientific research on climate change adaptation in Portugal since 2010, to assess strengths and limitations of knowledge, identifying key priority areas for future research and the “FAIRification” of these resources. As the frequency and intensity of extreme heat events in Portugal increases, this study focused on heat-related hazards, and associated impacts. A systematic search was performed across Scopus and ISI Web of Science to identify relevant peer-reviewed articles between January 2010 and May 2025. The resulting publications were analysed by geographical scope, adaptation sectorial focus, knowledge sector, climate hazard and CCA needs. Alignment of the current scientific outputs with FAIR principles was also analysed. A total of 217 articles were reviewed. Research was mostly performed at the city or national level (37% each) and the majority of adaptation actions were done under the agricultural or urban sectors (19% and 26%, respectively). Research was multidisciplinary, covering different knowledge sectors, from health impacts to biodiversity, buildings and construction, and often included several knowledge sectors in the same article. All articles presented accessible metadata but only one made its scripts and data available for further replication. Results show that scientific research on heat-related climate change adaptation in Portugal is diverse and covers many knowledge areas, but the availability of its data needs improvement. Further work will include policy FAIR assessment of policy documents and datasets. This work was developed under the Horizon Europe project FAIR2ADAPT. application/ld+json https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94 FAIR adaptation climate change heat Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal MANUAL Simões, Francisca, Ines Gomes Marques, and Tiago Capela Lourenço. "Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal." ROHub. Oct 13 ,2025. https://w3id.org/ro-id/302b4ebf-db38-49d5-8ab4-4561181f4e94. Centre for Ecology, Evolution and Environmental Changes, University of Lisbon igmarques@fc.ul.pt Ines Gomes Marques 0000-0002-2104-3187 ClimRisk, CE3C, Faculty of Sciences, U Lisbon tcapela@fc.ul.pt Tiago Capela Lourenço 0000-0002-8796-5993 10.24424/xq9z-p873 1057305 https://api.rohub.org/api/resources/a6c04f4c-0a9f-4b8d-8492-96a06dba7808/download/ 2025-10-13 11:48:29.771773+00:00 2025-10-14 08:33:10.492170+00:00 application/pdf Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal 2025-10-13 11:48:29.771773+00:00 203263 https://api.rohub.org/api/resources/b1a0d3cc-179c-4077-9d29-f14b8bada1d7/download/ 2025-10-13 11:20:07.788069+00:00 2025-10-13 11:20:08.689183+00:00 image/png Captura de ecrã 2025-10-13 121949.png 2025-10-13 11:20:07.788069+00:00 398943 https://api.rohub.org/api/resources/ebc84d30-9700-471e-ae2f-d04486f18c8d/download/ 2025-10-13 11:18:02.624724+00:00 2025-10-13 11:18:03.764253+00:00 image/png NatAdaptHub.png 2025-10-13 11:18:02.624724+00:00 metadata 11.924119241192415 4.4 availability 10.569105691056912 3.9 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences Portugal 20.05420054200542 7.4 data 16.260162601626018 6.0 meteorology 20.979020979020977 3.0 Climate change Environment/Climate change stakeholder 5.228758169934641 4.0 Portugal heat event 12.602739726027396 4.6 Since then, many resources (e.g. policy documents, scientific articles, data sets) relevant for national adaptation have been published, yet often remain unknown to, or inaccessible, for the multiple stakeholders that comprise the climate adaptation community (CCA) in Portugal. 31.362467866323907 12.2 Weather Weather Portugal 14.640522875816993 11.2 from 15 years scientific research 11.924119241192415 4.4 between Jan-2010 and May-2025 Information Sciences Institute earth sciences 100.0 0.9895771741867065 article 13.279132791327916 4.9 sector 7.0588235294117645 5.4 application of fair 14.794520547945206 5.4 10-Oct-12-2025 meteorology and climatology 100.0 0.8513408899307251 computer science 20.27972027972028 2.9 Results show that scientific research on heat-related climate change adaptation in Portugal is diverse and covers many knowledge areas, but the availability of its data needs improvement. 30.07712082262211 11.7 assessment 4.967320261437909 3.8 climate 8.235294117647058 6.3 knowledge sector 21.643835616438356 7.9 availability 12.026143790849671 9.2 in 2010 data 11.895424836601308 9.1 heat 4.836601307189542 3.7 Science and technology Science and technology climate change adaptation in Portugal 11.780821917808218 4.3 geosciences 100.0 0.8513408899307251 metadata 8.758169934640524 6.7 climate adaptation community 22.739726027397264 8.3 scientific research 8.627450980392156 6.6 ecology 31.468531468531467 4.5 dataset 13.72549019607843 10.5 since 2010 dataset 15.989159891598916 5.9 heat extreme 16.438356164383563 6.0 database 27.27272727272727 3.9 atmospheric sciences 100.0 0.9895771741867065 Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal. 38.56041131105398 15.0 ce3c@ciencias.ulisboa.pt CE3C - Centre for Ecology, Evolution and Environmental Changes francisca.simoes@edu.ulisboa.pt Francisca Simões Applied sciences 00k4n6c32 European Commission Simula Research Laboratory annef@simula.no Anne Fouilloux 0000-0002-1784-2920 00k4n6c32::101188256 FAIR to Adapt to Climate Change post@simula.no 00vn06n10 Simula Research Laboratory Germany 4.342273307790549 3.4 edit 7.407407407407407 5.8 publishing 100.0 0.8 drug addict 4.597701149425288 3.6 http 20.777027027027025 12.3 notebook 8.045977011494253 6.3 earth resources and remote sensing 100.0 0.9689354300498962 tutorial 12.132822477650064 9.5 map 8.277027027027028 4.9 zones in Saarland 12.794612794612794 7.6 zone 5.874840357598978 4.6 editing 8.783783783783784 5.2 real-time editing 23.737373737373737 14.1 JupyterGIS in Galaxy Europe 25.084175084175083 14.9 We showcase the usage of JupyterGIS for creating geographical maps showing the HQ 100 flooding zones in Saarland along with images from Wikimedia Commons. 29.9618320610687 15.7 We use JupyterGIS on the UseGalaxy.eu. The tool can be launched from [JupyterGIS in Galaxy Europe](https://usegalaxy.eu/root?tool_id=interactive_tool_jupytergis_notebook). Please prior to use it, register to [usegalaxy.eu](https://usegalaxy.eu/login/start) and authenticate yourself before starting it. 36.83206106870229 19.3 usage of JupyterGIS 21.043771043771045 12.5 4a9c340c-3f55-4473-8ebc-9798b38b791a POINT (7.0017099363030875 49.229107487031975) 7.0017099363030875 49.229107487031975 POINT (7.0017099363030875 49.229107487031975) 2025-05-28 12:08:14.740275+00:00 https://orcid.org/0000-0002-1784-2920 0 https://api.rohub.org/api/ros/588ada8d-a185-402e-8b60-3c17435110ee/crate/download/ 2025-05-17 17:15:18.830605+00:00 2025-05-28 12:41:54.042079+00:00 2025-05-17 17:15:18.830605+00:00 ## Flooding in Saarland We showcase the usage of JupyterGIS for creating geographical maps showing the HQ 100 flooding zones in Saarland along with images from Wikimedia Commons. These notebooks showcase how to use JupyterGIS. We use JupyterGIS on the UseGalaxy.eu. The tool can be launched from [JupyterGIS in Galaxy Europe](https://usegalaxy.eu/root?tool_id=interactive_tool_jupytergis_notebook). Please prior to use it, register to [usegalaxy.eu](https://usegalaxy.eu/login/start) and authenticate yourself before starting it. To help new users get started, there are two tutorials available: - [Intro to JupyterGIS](https://jupytergis.readthedocs.io/en/latest/user_guide/tutorials/01-intro/index.html) a step-by-step guide for new users. - [Collaborative Features Tutorial](https://training.galaxyproject.org/training-material/topics/climate/tutorials/jupytergis_collaboration/tutorial.html) — a guide for exploring real-time editing and shared annotations.  application/ld+json https://w3id.org/ro-id/588ada8d-a185-402e-8b60-3c17435110ee flooding saarland Flooding in Saarland (Germany) with JupyterGIS - fork Flooding in Saarland (Germany) with JupyterGIS MANUAL https://w3id.org/ro-id/588ada8d-a185-402e-8b60-3c17435110ee/24ad51f6-d7b4-4695-b93c-6de4f9a7aabe https://w3id.org/ro-id/15e54fde-611f-49cc-8951-e15c650f0cb2 https://w3id.org/ro-id/12fea67b-4679-4543-9d57-44440a7620c6 https://w3id.org/ro-id/d26768e8-b368-4ad2-9d32-dca81dce9e2b https://w3id.org/ro-id/f1474448-73d6-4d7e-919e-0134246ed966 https://w3id.org/ro-id/0540cebe-9b10-45af-9db4-604e7a64ed60 https://w3id.org/ro-id/0567f806-00e3-4120-9e01-229e58a87f26 https://w3id.org/ro-id/1d1be42a-f453-4705-82e3-e10d610807d5 https://w3id.org/ro-id/246eb18d-bf7f-4521-b47f-b88e24ece2d7 https://w3id.org/ro-id/2e473be3-ac4f-4804-a05f-395a06f0c30f https://w3id.org/ro-id/3d07f69d-a2cb-4a97-8b2f-24c1f5946691 https://w3id.org/ro-id/67a0f1a1-ee4c-4c41-b064-6fa4355a9792 https://w3id.org/ro-id/7ec7d31a-cfc7-412e-9e5a-1e6145094ab3 https://w3id.org/ro-id/a5af6ff5-a513-4ceb-9c10-942d1c6b6b38 https://w3id.org/ro-id/b172b4b1-fafb-4774-82bd-06d1b46dc290 https://w3id.org/ro-id/b8426843-c9aa-40de-bf19-934feb77f475 https://w3id.org/ro-id/c84eae9f-3b68-453e-8301-a561c19ae1c9 https://w3id.org/ro-id/fbd83c19-edd6-4933-a434-2c5bf9aaea6d https://w3id.org/ro-id/c32fb828-0fb1-4761-a71e-b79058f885d1 https://w3id.org/ro-id/e80f74dd-9268-4215-85d5-210bf3b4eaad https://w3id.org/ro-id/1d39b6ad-25f6-4b03-8aca-fc77c1ed5330 https://w3id.org/ro-id/35deaca0-ec97-468c-8c2c-4dab85ee0fd8 https://w3id.org/ro-id/4186caba-311c-4fe7-b9a5-7bedfaa9333d https://w3id.org/ro-id/637a6d26-e7ec-4001-90f6-aa42a4f6a943 https://w3id.org/ro-id/76ca8190-4c71-4c02-b5d9-51aabcfcf912 https://w3id.org/ro-id/941022ff-01b0-4e3a-83d0-054f39ad6bc2 https://w3id.org/ro-id/a246196d-8e26-4342-b638-15f1663bfb07 https://w3id.org/ro-id/2dc852b1-ee72-4e32-8770-baeddd6ee513 https://w3id.org/ro-id/8c2959e5-d5d3-4ffa-954f-db48cc009558 https://w3id.org/ro-id/3b2b42dd-d686-49fa-bd25-a3e8ec0bbd82 https://w3id.org/ro-id/47e46601-34db-4ed2-a16c-c7e63e3ff817 https://w3id.org/ro-id/4baa42ad-b336-483a-bc75-9c2cf6ed7640 https://w3id.org/ro-id/572c411e-83d9-4fd8-b581-9724b2674243 https://w3id.org/ro-id/d825b7f9-7b4c-4086-9946-a9230dbb2155 https://w3id.org/ro-id/500e0dba-c679-42fe-8afe-b8f8e1349831 https://w3id.org/ro-id/51f2e644-1083-4bc8-8184-ee7a7fe0a1e6 https://w3id.org/ro-id/de2ddebf-664e-4694-bd50-106d0429f112 Fouilloux, Anne, and ELİFSU FİLİZ. "Flooding in Saarland (Germany) with JupyterGIS." ROHub. May 17 ,2025. https://w3id.org/ro-id/588ada8d-a185-402e-8b60-3c17435110ee. POINT (7.0017099363030875 49.229107487031975) https://fair2adapt.github.io/saarland-flooding/ 2025-05-17 17:25:04.424197+00:00 2025-05-28 12:08:08.625385+00:00 Jupyter Book (HTML rendered version) to showcase JupyterGiS in action using flooding event data from Saarland, Germany, available via the Urban Data Portal. Saarland flooding Jupyter Book (rendered HTML) 2025-05-17 17:25:04.424197+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/environment.yml 2025-05-28 06:22:48.754139+00:00 2025-05-28 12:08:06.376487+00:00 environment.yml (Conda environment for Python JupyterGIS) environment.yml (JupyterGIS environment) 2025-05-28 06:22:48.754139+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/environment.lock.yml 2025-05-28 06:07:06.113808+00:00 2025-05-28 12:08:09.102494+00:00 Python environment for executing the associated Jupyter notebook. environment.lock.yml (conda environment) 2025-05-28 06:07:06.113808+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Flood_protection_line_Saarland.ipynb 2025-05-28 06:08:36.012998+00:00 2025-05-28 12:08:06.812992+00:00 Flood_protection_line_Saarland.ipynb is a Jupyter Notebook . Flood_protection_line_Saarland.ipynb (Jupyter Notebook) 2025-05-28 06:08:36.012998+00:00 https://w3id.org/ro-id/588ada8d-a185-402e-8b60-3c17435110ee/resources/85ba47e2-3608-40f7-ade8-bfd40a8fc19d https://github.com/FAIR2Adapt/saarland-flooding.git 2025-05-17 17:23:09.941511+00:00 2025-05-28 12:08:09.818748+00:00 This Github repository contains the latest version of the jupyter notebooks showcasing JupyterGIS. Saarland-flooding (Github repository) 2025-05-17 17:23:09.941511+00:00 2788165 https://api.rohub.org/api/resources/67c0cbcb-4067-4ad1-ad2c-06e98aff714b/download/ 2025-05-17 17:20:36.705228+00:00 2025-05-28 12:08:08.186162+00:00 Flood in Saarland with JupyterGIS. image/png flood_in_saarland_with_jqgis.png 2025-05-17 17:20:36.705228+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/get_typename_from_WFS.ipynb 2025-05-28 06:10:42.644758+00:00 2025-05-28 12:08:04.665895+00:00 ## Get data layer names from WFS service URL **Learn how to get the typename (e.g. data layers) which are requested for querying WFS services** get_typename_from_WFS.ipynb (Jupyter Notebook) 2025-05-28 06:10:42.644758+00:00 https://raw.githubusercontent.com/FAIR2Adapt/saarland-flooding/refs/heads/main/notebooks/Hamburg_urban_data_portal_WFS.ipynb 2025-05-28 06:12:02.439269+00:00 2025-05-28 12:08:14.693939+00:00 ## Get data from the Hamburg Urban Data Portal using WFS **Learn how to access vector data from the Hamburg Urban Data Portal with WFS** Hamburg_urban_data_portal_WFS.ipynb (Jupyter Notebook) 2025-05-28 06:12:02.439269+00:00 https://doi.org/10.5281/zenodo.15470110 2025-05-20 08:44:57.687928+00:00 2025-05-28 12:08:07.043396+00:00 Saarland flooding (Galaxy History) with outputs and executed notebooks. Saarland flooding (Galaxy History) 2025-05-20 08:44:57.687928+00:00 tutorial 14.020270270270272 8.3 annotation 5.874840357598978 4.6 notebook 9.628378378378377 5.7 real time 4.725415070242657 3.7 geosciences 100.0 0.9689354300498962 JupyterGIS 24.155405405405403 14.3 Saarland 14.358108108108107 8.5 headquarters 4.725415070242657 3.7 usage 6.257982120051087 4.9 map 7.0242656449553005 5.5 atmospheric sciences 100.0 0.571331262588501 http 17.11366538952746 13.4 Germany https://www.wikidata.org/wiki/Q183 features tutorial 17.34006734006734 10.3 Flooding in Saarland (Germany) with JupyterGIS. 33.20610687022901 17.4 earth sciences 100.0 0.571331262588501 Saarland https://www.wikidata.org/wiki/Q1201 Saarland 11.877394636015328 9.3 elifsu@simula.no ELİFSU FİLİZ Environmental research University of Florida ethanwhite@ufl.edu Ethan P. White 0000-0001-6728-7745 The Alan Turing Institute lvanzeeland@turing.ac.uk Louisa Van Zeeland 0009-0005-0392-4377 DeepForest notebook 34.64249748237664 34.4 earth sciences 100.0 0.7395366430282593 Environmental Data Science book 15.609264853977846 15.5 detection 11.345939933259174 10.2 geophysics 100.0 0.4561961591243744 notebook 19.120135363790187 11.3 research 19.4585448392555 11.5 object 14.571746384872078 13.1 geosciences 100.0 0.4561961591243744 Environmental Data Science 17.575083426028918 15.8 2025-05-27 16:35:09.245985+00:00 https://w3id.org/ro-id/users/annef%40simula.no https://w3id.org/ro-id/7ad44bec-6784-437f-b5f3-2199b43a5303 research 13.348164627363737 12.0 aim 21.489001692047378 12.7 Livestock detection 15.105740181268883 15.0 geology 100.0 0.7395366430282593 Book industry Economy, business and finance/Economic sector/Media/Book industry https://w3id.org/ro-id/5784402a-b47e-4560-b6ef-c9fecfef2115 0 https://api.rohub.org/api/ros/7ad44bec-6784-437f-b5f3-2199b43a5303/crate/download/ 2024-12-04 22:59:05.987316+00:00 2025-05-27 17:13:45.833609+00:00 2024-12-04 22:59:05.987316+00:00 The research object refers to the Livestock detection using DeepForest notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/7ad44bec-6784-437f-b5f3-2199b43a5303 Livestock detection using DeepForest (Jupyter Notebook) published in the Environmental Data Science book MANUAL https://w3id.org/ro-id/f48250c4-c494-456a-9b6e-f4e6357a38c3 https://w3id.org/ro-id/18f88f96-891f-4283-bca6-96e5b5790a9f https://w3id.org/ro-id/25b882de-d196-406b-bb10-3e3d9144e703 https://w3id.org/ro-id/6f7d2e05-5259-4e8e-b0e1-f32803318c16 https://w3id.org/ro-id/fc4c7bbf-fd88-4614-b0a2-ee4d42cdb14f https://w3id.org/ro-id/fd30f53e-5736-4cfe-8f87-c830284b2eb0 https://w3id.org/ro-id/0524d334-9343-4da9-97e1-3bf548ec43a4 https://w3id.org/ro-id/763687ae-23cf-4cdd-9cd2-5abdc64a0292 https://w3id.org/ro-id/79e08be3-7b6f-4e45-8b22-c7601981149f https://w3id.org/ro-id/8729e151-1755-45c5-bc96-984df50473fd https://w3id.org/ro-id/8d0c7987-45ed-4898-a75c-99b4bdc79a95 https://w3id.org/ro-id/122efe44-26a9-4b91-a5d3-eb01213346bb https://w3id.org/ro-id/39837817-242b-44c5-96d7-14c471898391 https://w3id.org/ro-id/4db6da95-285e-42db-932c-1fd23e6fcdd2 https://w3id.org/ro-id/5ab77465-cf90-426c-ae7f-ffbb76d7a775 https://w3id.org/ro-id/83560376-2acb-4676-8468-48db185146f6 https://w3id.org/ro-id/a0692c42-42b4-4787-8e33-d8efbb6d7ad1 https://w3id.org/ro-id/e23cfbb6-9d20-440a-8cba-3c2cec67c0e0 https://w3id.org/ro-id/13e7bc1d-6788-4671-a6b0-6775f1b35c66 https://w3id.org/ro-id/45e6be16-1a7d-4b5d-9df8-110c40627fc6 https://w3id.org/ro-id/0368b491-8ec4-486a-ac1c-05f586f55612 https://w3id.org/ro-id/111854d7-7863-4e42-84cd-92fadc504e8c https://w3id.org/ro-id/72028dbc-cc0c-4df0-a402-1fbfdc212361 https://w3id.org/ro-id/a6a10782-a94e-4c0d-8b1a-f55dd52f35c9 https://w3id.org/ro-id/c1f82fab-b31e-4415-a94d-264d91ae82de https://w3id.org/ro-id/cbf391bc-8a89-4faa-80a3-45105c7864b2 https://w3id.org/ro-id/de5f84e2-2c7a-4242-9750-a9913493a6ca Cameron Appel, Ethan P. White, and Louisa Van Zeeland. "Livestock detection using DeepForest (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 04 ,2024. https://w3id.org/ro-id/7ad44bec-6784-437f-b5f3-2199b43a5303. output tool input biblio https://github.com/eds-book-gallery/95199651-9e81-4cae-a3a7-66398a9a5f62/blob/main/notebook.ipynb 2024-12-04 23:00:20.603543+00:00 2024-12-04 23:00:21.556504+00:00 Jupyter Notebook hosted by the Environmental Data Science Book Jupyter notebook 2024-12-04 23:00:20.603543+00:00 https://doi.org/https://doi.org/10.1111/2041-210X.13472 2024-12-04 23:00:33.471709+00:00 2024-12-04 23:00:34.525430+00:00 Related publication of the modelling presented in the Jupyter notebook Deepforest: a python package for rgb deep learning tree crown delineation 2024-12-04 23:00:33.471709+00:00 https://doi.org/10.7910/DVN/N7GJYU 2024-12-04 23:00:24.659570+00:00 2024-12-04 23:00:25.667439+00:00 Contains input Input dataset for the fine-tuned model used in the Jupyter notebook of Livestock detection using DeepForest Input Input dataset for the fine-tuned model 2024-12-04 23:00:24.659570+00:00 https://edsbook.org/notebooks/gallery/95199651-9e81-4cae-a3a7-66398a9a5f62/notebook.html 2024-12-04 23:00:46.367365+00:00 2024-12-04 23:00:47.573187+00:00 Rendered version of the Jupyter Notebook hosted by the Environmental Data Science Book text/html Online rendered version of the Jupyter notebook 2024-12-04 23:00:46.367365+00:00 457238 https://api.rohub.org/api/resources/832ec27f-3faf-4051-9a42-dfa6d421a6ed/download/ 2024-12-04 23:00:16.094540+00:00 2024-12-04 23:00:17.222084+00:00 image/png Image showing an example of the finetuned model predictions to detect livestock 2024-12-04 23:00:16.094540+00:00 https://doi.org/10.5281/zenodo.14279111 2024-12-04 23:00:28.915134+00:00 2024-12-04 23:00:30.048350+00:00 Contains outputs, (results), generated in the Jupyter notebook of Livestock detection using DeepForest Outputs 2024-12-04 23:00:28.915134+00:00 https://github.com/eds-book-gallery/95199651-9e81-4cae-a3a7-66398a9a5f62/tree/main/.lock/conda-lock.yml 2024-12-04 23:00:37.727861+00:00 2024-12-04 23:00:38.784747+00:00 Lock conda file of the Jupyter notebook hosted by the Environmental Data Science Book Lock conda file 2024-12-04 23:00:37.727861+00:00 https://github.com/eds-book-gallery/95199651-9e81-4cae-a3a7-66398a9a5f62/tree/main/.binder/environment.yml 2024-12-04 23:00:41.963542+00:00 2024-12-04 23:00:43.056070+00:00 Conda environment when user want to have the same libraries installed without concerns of package versions Conda environment 2024-12-04 23:00:41.963542+00:00 book 12.235817575083425 11.0 Literature Arts, culture and entertainment/Arts and entertainment/Literature Language Arts, culture and entertainment/Culture/Language notebook 13.125695216907674 11.8 use DeepForest notebook 0.6042296072507553 0.6 research object 34.038267875125875 33.8 The research object refers to the Livestock detection using DeepForest notebook published in the Environmental Data Science book. 60.76076076076076 60.7 Livestock detection using DeepForest (Jupyter Notebook) published in the Environmental Data Science book. 39.23923923923924 39.2 DeepForest 17.797552836484982 16.0 publishing 100.0 6.9 detection 17.089678510998308 10.1 book 22.84263959390863 13.5 Queen Mary University London c.appel@qmul.ac.uk Cameron Appel Environmental Data Science Book Community ./ 2020-10-29T02:56:21.632Z 2020-10-29T02:56:21.632Z To study the flow field around a circular bridge pier with an upstream flow diversion structure (FDS), Particle Image Velocimetry (PIV) technique was employed. Velocity components at a vicinity of a pier with an upstream FDS under different submergence ratio were measured. The measurements were made with a single pier case, and a single pier with the FDS at the upstream with H/y = 0.25, 0.5, 0.75, and >1. The streamwise (u) and vertical (w) velocity components were determined from analysis of the PIV images collected during the individual experiments. Further analyses were carried out by a developed code in MATLAB and the results were stored in txt files. The outcomes include: Normalised Streamwise Velocity Component (u/V) Normalised Vertical Velocity Component (w/V) Normalised Turbulence Intensity Components (TIu/V and TIw/V) Normalised Turbulent Kinetic Energy (TKE/V2) Normalised Reynolds Shear Stress (u^' w^' ) / V^2 79d6e45f218b99f5dfe4e432e05abb0b Circular pier Flow Diversion Structure Flow field Flow field around a circular bridge pier with an upstream triangular prism using Particle Image Velocimetry 2020 2020 This is the UTS Research Data Portal. For any questions, please get in touch with us at eResearch-it@uts.edu.au UTS Research Data Portal Oni ocfl tools git+https://github.com/Arkisto-Platform/oni-ocfl.git Fiona.Tweedie@uts.edu.au Hadi.Khabbaz@uts.edu.au Khabbaz Mohammad Hadi.Khabbaz@uts.edu.au Mohammad Khabbaz James.Ball@uts.edu.au Ball James James.Ball@uts.edu.au James Ball _:contact/Mohsen.Ranjbarzahedani@student.uts.edu.au Mohsen.Ranjbarzahedani@student.uts.edu.au Ranjbarzahedani Mohsen Mohsen.Ranjbarzahedani@student.uts.edu.au Mohsen Ranjbarzahedani application/pdf Description.pdf Data record created 2020-10-29T02:56:21.632Z Create