Environmental research Applied sciences Climatology https://fip.fair-wizard.com/wizard/projects/7d647ed2-6698-4be3-ac81-502329066b3c 2025-06-08 17:20:49.943434+00:00 2025-10-14 08:33:10.768008+00:00 FAIR2Adapt DMP generated from DSW questionnaire. FAIR2Adapt living DMP (DSW questionnaire) 2025-06-08 17:20:49.943434+00:00 Anne Fouilloux https://w3id.org/np/RA5lIm2-EGBm0gHlI5kgRI7ZU-cMI1Q06hKVEfPKeOJi8 2025-06-30 19:46:19.391474+00:00 2025-10-14 08:33:11.436980+00:00 FAIR Implementation Profile (FIP) for the case study 1 "Arctic Radio-Isotopes. Case Study 1 - Arctic Radio-Isotopes FIP 2025-06-30 19:46:19.391474+00:00 https://w3id.org/np/RA9-o3xRk7ti6szajJWGi40ieCuZxYZWFs0_-JomvvR6o 2025-06-30 19:55:07.441681+00:00 2025-10-14 08:33:12.670849+00:00 FAIR Implementation Profile (FIP) for the case study 6 "FAIR Climate Risk Assessments". Case Study 6 - FAIR Climate Risk Assessments FIP 2025-06-30 19:55:07.441681+00:00 https://w3id.org/np/RAK3KIGPtDb9iV_j1HTp9YSpFSarZv6fPj3bJq6LBpNyI 2025-06-30 19:51:10.773257+00:00 2025-10-14 08:33:11.958426+00:00 FAIR Implementation Profile (FIP)for the case study 3 and the software developed to create Risk Map for the Hamburg city area. Case Study 3 - Hamburg Risk Map Software FIP 2025-06-30 19:51:10.773257+00:00 https://w3id.org/np/RAKd4AuA3eWKX-NzEj5nVRJCYD088zZx0oxz92BrdZHSA 2025-06-30 19:52:27.634634+00:00 2025-10-14 08:33:12.203443+00:00 FAIR Implementation Profile (FIP) for case study 4 "Climate Adaptation Hub Portugal". Case Study 4 - Climate Adaptation Hub Portugal FIP 2025-06-30 19:52:27.634634+00:00 https://w3id.org/np/RAVgqppDFnLwV3SgHcGS0cv2MOedMKbMlNGvLmvuTttjI 2025-06-30 19:53:38.877790+00:00 2025-10-14 08:33:12.429135+00:00 FAIR Implementation Profile for the weADAPT platform. Case Study 5 - weADAPT FIP 2025-06-30 19:53:38.877790+00:00 https://w3id.org/np/RAs6_kCEos5itKDnH7AXodfNwRCzEN5Gr-MJU6Zwe_kb8 2025-06-30 19:49:15.427555+00:00 2025-10-14 08:33:11.694546+00:00 FAIR Implementation Profile (FIP) for the RiOMar simulation data from the Bay of Biscay. Case Study 2 - RiOMar Bay of Biscay Simulation Data FIP 2025-06-30 19:49:15.427555+00:00 0 https://api.rohub.org/api/ros/5954ce8e-2bbc-469a-b5ba-0d4d1e93195f/crate/download/ 2025-06-08 15:01:57.739189+00:00 2025-10-16 11:35:56.385641+00:00 2025-06-08 15:01:57.739189+00:00 The FAIR2Adapt Data Management Plan will evolve during the lifetime of the project in order to present the status of the project's reflections on data management. Our DMP will be made publicly available on ROHub so that the up to date version can be consulted at any time by everyone. application/ld+json https://w3id.org/ro-id/5954ce8e-2bbc-469a-b5ba-0d4d1e93195f FAIR2Adapt Data Management Plan (Deliverable D1.2) MANUAL Fouilloux, Anne. "FAIR2Adapt Data Management Plan (Deliverable D1.2)." ROHub. Jun 08 ,2025. https://w3id.org/ro-id/5954ce8e-2bbc-469a-b5ba-0d4d1e93195f. This folder contains the links to the FIPs. FIPs 468879 https://api.rohub.org/api/resources/f152dc94-e6c8-4232-b301-951ce2fc37f2/download/ 2025-06-29 18:45:15.257158+00:00 2025-10-14 08:33:11.199235+00:00 Snapshot of the DMP questionnaire (FIP Wizard) from the 29 June 2025. application/pdf FAIR2Adapt_DMP_questionnaire_snapshot_29June2025 2025-06-29 18:45:15.257158+00:00 FAIR2Adapt Data Management Plan 12.629161882893227 11.0 data management 46.61308840413319 40.6 oceanography 100.0 0.5455796718597412 project 13.535911602209945 9.8 project 11.021814006888635 9.6 version 5.248618784530386 3.8 standing 22.23756906077348 16.1 Our DMP will be made publicly available on ROHub so that the up to date version can be consulted at any time by everyone. 8.508508508508507 8.5 status of the project's reflection 17.97979797979798 17.8 social and information sciences 100.0 0.3022623062133789 FAIR2Adapt Data Management Plan (Deliverable D1.2). The FAIR2Adapt Data Management Plan will evolve during the lifetime of the project in order to present the status of the project's reflections on data management. 91.49149149149149 91.4 deliverable D1.2 1.5151515151515151 1.5 status 18.94374282433984 16.5 plan 10.792192881745121 9.4 project's reflection 0.8080808080808081 0.8 data management 51.519337016574575 37.3 earth sciences 100.0 0.5455796718597412 up to date version 6.96969696969697 6.9 data management plan 72.72727272727273 72.0 documentation and information science 100.0 0.3022623062133789 reflection 7.458563535911602 5.4 Applied sciences 00k4n6c32 European Commission Simula Research Laboratory annef@simula.no Anne Fouilloux 0000-0002-1784-2920 barbara@gofair.foundation Barbara Magagna 00k4n6c32::101188256 FAIR to Adapt to Climate Change 2025-06-12 06:29:25.595371+00:00 0 https://api.rohub.org/api/ros/05729783-a960-4fbd-b1f6-f83fb23eb44c/crate/download/ 2025-03-08 16:08:42.827750+00:00 2025-10-16 11:32:54.865261+00:00 2025-03-08 16:08:42.827750+00:00 # Improving data availability for climate risk assessments under the EU taxonomy for sustainable activities ## Vision & Ambitions In this case study, we want to: 1) Provide insights into data used and needed by businesses and consultants to perform climate risk assessments for reporting under the EU taxonomy for sustainable activities; 2) Collect local climate hazard data that is being used in such analyses; 3) improve accessibility to key datasets for climate risk analyses under the EU taxonomy. ## Description Climate risk analyses under the EU taxonomy for sustainable activities (Pan-European) More and more companies in the EU are required to report on how their economic activities are contributing to the six environmental objectives of the EU taxonomy for sustainable activities. In this context, the Commission Delegated Regulation (EU) 2021/2178 requires companies to perform climate risk assessment for two possible purposes: to show that an economic activity is contributing to climate change adaptation (environmental objective #2) or to check whether an activity that contributes to another objective will do so even under a changing climate (do-no-significant-harm check). The regulation has detailed requirements that a climate risk analysis needs to fulfil, e.g. climate projections at the smallest appropriate scale and at least 28 different climate hazards need to be considered. Experience shows that business as well as consultants are struggling with the very demanding requirements and the very parcelled climate hazard data landscape. While there is a lot of data available on the 28 climate-related hazards that businesses need to analyse, data is not tagged / structured in a way that users can easily find it. Many businesses have operations across different EU countries which makes it even more challenging to conduct a harmonised assessment for all relevant locations and at the most appropriate local scale. Furthermore, many businesses will be required to prepare an adaptation plan that includes adaptation measures and is in line with local, regional and national adaptation strategies. ## FAIR2Adapt Contribution By accompanying two businesses in preparing climate risk assessments as part of their EU taxonomy reporting, will provide an overview on the sources that are being used for the assessments, from local to national to European sources. Furthermore, we shall document important data gaps and highlight possible difficulties when combining the different datasets during the assessments, e.g. problems because of different temporal or spatial scales. Guided by approaches from WP 3 to 5, strategies to make the most valuable data FAIR, using a vocabulary that is consistent with the requirements in the EU taxonomy, will be developed. ## Lead Partner ADELPHI ## External Stakeholders involved in CCA Two businesses that have operations in multiple EU countries, and have to report under the EU taxonomy. application/ld+json https://w3id.org/ro-id/05729783-a960-4fbd-b1f6-f83fb23eb44c FAIR Climate Risk Data for Businesses - barbara FAIR Climate Risk Data for Businesses - fork MANUAL Bartsch, Julia, Anne Fouilloux, and Barbara Magagna. "FAIR Climate Risk Data for Businesses - barbara." ROHub. Mar 08 ,2025. https://w3id.org/ro-id/05729783-a960-4fbd-b1f6-f83fb23eb44c. The FAIR2Adapt community is dedicated to advancing climate change adaptation in Europe by promoting FAIR and open data sharing to enhance the accessibility, interoperability, and usability of environmental and socio-economic data in support of climate change adaptation efforts. annef@simula.no FAIR2Adapt http://fair2adapt-eosc.eu risk 10.383064516129032 10.3 hazard datum 10.381355932203391 4.9 datum 7.459677419354838 7.4 meteorology and climatology 100.0 0.8879811763763428 data 3.629032258064516 3.6 the economy 33.587786259541986 4.4 chance 3.629032258064516 3.6 parcelled climate hazard data landscape 21.39830508474576 10.1 European Union 26.456310679611647 10.9 By accompanying two businesses in preparing climate risk assessments as part of their EU taxonomy reporting, will provide an overview on the sources that are being used for the assessments, from local to national to European sources. 34.94423791821561 9.4 climate risk analysis 20.762711864406782 9.8 geosciences 100.0 0.8879811763763428 Weather Weather politics 24.427480916030532 3.2 EU taxonomy 26.483050847457626 12.5 European Union environmental sciences 100.0 0.9975064396858215 Environmental politics Environment/Environmental politics climate 22.572815533980584 9.3 climate risk assessments 15.466101694915253 7.3 trade 21.374045801526716 2.8 Environment Environment datum 15.776699029126213 6.5 companies in the EU 5.508474576271186 2.6 business 5.342741935483871 5.3 In this case study, we want to: 1) Provide insights into data used and needed by businesses and consultants to perform climate risk assessments for reporting under the EU taxonomy for sustainable activities; 34.20074349442379 9.2 risk assessment 21.116504854368927 8.7 database 20.610687022900763 2.7 International organisation Politics/International relations/International organisation European Union 12.903225806451612 12.8 risk assessment 9.97983870967742 9.9 # Improving data availability for climate risk assessments under the EU taxonomy for sustainable activities 30.8550185873606 8.3 environmental science and management 100.0 0.9975064396858215 availability 4.637096774193548 4.6 assessment 5.241935483870968 5.2 economic activity 3.4274193548387095 3.4 taxonomy 4.838709677419355 4.8 dataset 5.141129032258064 5.1 climate 18.044354838709676 17.9 risk 14.07766990291262 5.8 country 5.342741935483871 5.3 bartsch@adelphi.de Julia Bartsch Environmental research Applied sciences Scientific Researcher biroy@ciencias.ulisboa.pt Bishwajit Roy 0000-0001-6976-9297 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 https://w3id.org/ro-id/2cace03a-fa6d-450a-9192-dd17fe85a941 2025-06-27 10:56:43.364977+00:00 2025-10-14 08:33:18.817709+00:00 Research Object of the case study 'Developing and testing a FAIR-by-design national adaptation hub' from the FAIR2Adapt project. Designing a FAIR National Adaptation Hub 2025-06-27 10:56:43.364977+00:00 12.57989480160177 44.068643068110674 POINT (12.57989480160177 44.068643068110674) a0fdfcc9-774d-45c8-ae4c-fe9447377611 POINT (12.57989480160177 44.068643068110674) 0 https://api.rohub.org/api/ros/2f432569-3648-4885-bb84-bc9507c5187a/crate/download/ 2025-06-26 14:52:46.125018+00:00 2025-11-14 10:33:54.487975+00:00 2025-06-26 14:52:46.125018+00:00 **Session at the European Climate Change Adaptation Conference, Rimini - Italy** *16-18 July 2025* This session was part of the HEurope FAIR2Adapt and CLIMATE-ADAPT4EOSC projects that intend to improve the efficiency of the data-to-knowledge supply chain in the field of climate change adaptation (CCA). In line with ECCA’s theme ‘Managing cities to be fit for the future’, the main goal of this session is to demonstrate how an ecosystem of FAIR (Findable, Accessible, Interoperable, and Reusable) technologies and services can support CCA stakeholders (e.g., researchers and practitioners) in their decision-making processes. The panel presentations will feature concrete examples of how FAIR tools and approaches can help CCA researchers and practitioners overcome barriers to accessing, using, and reproducing data and generating interoperable services. In addition, this session aims to gather information on the breadth of knowledge CCA stakeholders work with and how this knowledge is produced, providing key insights for FAIR experts who need a clear understanding of user requirements to design effective FAIR tooling. application/ld+json https://w3id.org/ro-id/2f432569-3648-4885-bb84-bc9507c5187a Presentation FAIR data and Open Science in support of climate change adaptation MANUAL Gomes Marques, Ines, Tiago Capela Lourenço, Bishwajit Roy, and Francisca Simões. "FAIR data and Open Science in support of climate change adaptation." ROHub. Jun 26 ,2025. https://w3id.org/ro-id/2f432569-3648-4885-bb84-bc9507c5187a. POINT (12.57989480160177 44.068643068110674) 138754 https://api.rohub.org/api/resources/0a063ed5-08ef-4c88-b2d7-838001adae71/download/ 2025-06-27 10:52:58.253656+00:00 2025-06-27 10:52:59.109741+00:00 image/png Captura de ecrã 2025-06-26 155444.png 2025-06-27 10:52:58.253656+00:00 10.24424/d8yy-bv20 6805348 https://api.rohub.org/api/resources/447465f2-4083-4d02-a034-ef45bc9455cd/download/ 2025-07-03 12:04:42.527283+00:00 2025-10-14 08:33:19.291465+00:00 Session presentation at the European Climate Change Conference 2025, in Rimini - Italy application/pdf FAIR data and Open Science in support of climate change adaptation 2025-07-03 12:04:42.527283+00:00 404565 https://api.rohub.org/api/resources/9f3afc74-5d13-4b39-826b-719982a3ec01/download/ 2025-06-27 07:17:05.338354+00:00 2025-06-27 07:17:06.067196+00:00 image/png Captura de ecrã 2025-06-27 081651.png 2025-06-27 07:17:05.338354+00:00 44358 https://api.rohub.org/api/resources/bbd1e98c-8c54-4988-8f76-ade0cbbcc4f2/download/ 2025-10-31 11:37:39.814835+00:00 2025-10-31 11:37:41.656394+00:00 image/jpeg F2A Logo 2025-10-31 11:37:39.814835+00:00 The FAIR2Adapt community is dedicated to advancing climate change adaptation in Europe by promoting FAIR and open data sharing to enhance the accessibility, interoperability, and usability of environmental and socio-economic data in support of climate change adaptation efforts. annef@simula.no FAIR2Adapt http://fair2adapt-eosc.eu FAIR2Adapt Case study 4 - Developing and testing a FAIR-by-design national adaptation hub, with the aim to find, extract, curate and make available climate and non-climate knowledge and information (e.g., climate projections, socio-economic, environmental and demographic data, case studies, adaptation measures, cost-benefit analysis, among others) from relevant CCA-related portals, platforms and publications, necessary to support the adaptation decision-making planning cycle. igmarques@fc.ul.pt Climate Adaptation Hub Portugal https://fair2adapt-eosc.eu/index.php/case-study-4-developing-and-testing-a-fair-by-design-national-adaptation-hub/ 16-Jul-18-2025 environmental science and management 100.0 0.9944642186164856 scientific discipline 5.963938973647711 4.3 ecosystem of Fair 12.375533428165006 8.7 Shareholder Economy, business and finance/Business information/Business finance/Shareholder information 9.70873786407767 7.0 This session was part of the HEurope FAIR2Adapt and CLIMATE-ADAPT4EOSC projects that intend to improve the efficiency of the data-to-knowledge supply chain in the field of climate change adaptation (CCA). In line with ECCA’ 36.807817589576544 22.6 Science and technology Science and technology the main goal of this session is to demonstrate how an ecosystem of FAIR (Findable, Accessible, Interoperable, and Reusable) technologies and services can support CCA stakeholders (e.g., researchers and practitioners) in their decision-making processes. 24.755700325732896 15.2 ecology 100.0 7.6 practitioner 12.809917355371901 6.2 Rimini documentation and information science 100.0 0.5052669048309326 climate change adaptation conference 5.2631578947368425 3.7 researcher 16.36615811373093 11.8 field of climate change adaptation 18.207681365576104 12.8 doctor 12.205270457697642 8.8 session 13.037447988904297 9.4 researcher 17.355371900826448 8.4 cca stakeholder 33.99715504978663 23.9 climate change adaptation 25.41322314049587 12.3 session 13.223140495867769 6.4 project 4.2995839112343965 3.1 supply chain 5.547850208044382 4.0 efficiency 4.854368932038835 3.5 environmental sciences 100.0 0.9944642186164856 information 9.917355371900827 4.8 The panel presentations will feature concrete examples of how FAIR tools and approaches can help CCA researchers and practitioners overcome barriers to accessing, using, and reproducing data and generating interoperable services. 38.43648208469055 23.6 Cinema Arts, culture and entertainment/Arts and entertainment/Cinema stakeholder 10.957004160887655 7.9 Italy 6.518723994452149 4.7 Findable, Accessible, Interoperable, and Reusable 9.504132231404958 4.6 cca researcher 30.15647226173542 21.2 Italy ecosystem 6.102635228848821 4.4 social and information sciences 100.0 0.5052669048309326 stakeholder 11.776859504132231 5.7 Rimini 4.438280166435506 3.2 ce3c@ciencias.ulisboa.pt CE3C - Centre for Ecology, Evolution and Environmental Changes francisca.simoes@edu.ulisboa.pt Francisca Simões Chemistry 10.24424/jxpj-vv36 False 2025-07-04 09:08:44.261623+00:00 0 https://api.rohub.org/api/ros/de0b3951-0fa7-4b03-a1fa-d5c4da93a476/crate/download/ 2022-01-12 16:34:39.917729+00:00 2025-10-16 11:15:06.613810+00:00 2022-01-12 16:34:39.917729+00:00 Aromatic compounds are those chemical compounds (most commonly organic) that contain one or more rings with pi electrons delocalized all the way around them. In contrast to compounds that exhibit aromaticity, aliphatic compounds lack this delocalization. The term "aromatic" was assigned before the physical mechanism determining aromaticity was discovered, and referred simply to the fact that many such compounds have a sweet or pleasant odour; however, not all aromatic compounds have a sweet odour, and not all compounds with a sweet odour are aromatic compounds. Aromatic hydrocarbons, or arenes, are aromatic organic compounds containing solely carbon and hydrogen atoms. The configuration of six carbon atoms in aromatic compounds is called a "benzene ring", after the simple aromatic compound benzene, or a phenyl group when part of a larger compound. Not all aromatic compounds are benzene-based; aromaticity can also manifest in heteroarenes, which follow Hückel's rule (for monocyclic rings: when the number of its π electrons equals 4n + 2, where n = 0, 1, 2, 3, ...). In these compounds, at least one carbon atom is replaced by one of the heteroatoms oxygen, nitrogen, or sulfur. Examples of non-benzene compounds with aromatic properties are furan, a heterocyclic compound with a five-membered ring that includes a single oxygen atom, and pyridine, a heterocyclic compound with a six-membered ring containing one nitrogen atom. application/ld+json https://w3id.org/ro-id/de0b3951-0fa7-4b03-a1fa-d5c4da93a476 Aromatic compounds - snapshot Aromatic compounds MANUAL Wolniewicz, Małgorzata. "Aromatic compounds." ROHub. Jan 12 ,2022. https://doi.org/10.24424/jxpj-vv36. arene 7.304347826086956 4.2 aliphatic compound 4.737903225806451 4.7 The term "aromatic" was assigned before the physical mechanism determining aromaticity was discovered, and referred simply to the fact that many such compounds have a sweet or pleasant odour; however, not all aromatic compounds have a sweet odour, and not all compounds with a sweet odour are aromatic compounds. 21.401515151515152 11.3 Jewellery Arts, culture and entertainment/Arts and entertainment/Fashion/Jewellery oxygen atom 4.032258064516129 4.0 nitrogen 3.9314516129032255 3.9 organic chemistry 65.91639871382637 41.0 oxygen atom 17.794486215538846 7.1 benzene 9.274193548387096 9.2 geochemistry 100.0 0.4569866955280304 heterocyclic compound 9.73913043478261 5.6 chemistry and materials 100.0 0.8506659269332886 aromatic 19.657258064516128 19.5 benzene 12.695652173913043 7.3 monocyclic ring 14.285714285714286 5.7 chemistry and materials (general) 100.0 0.8506659269332886 arene 4.939516129032259 4.9 electron 4.435483870967742 4.4 chemistry 34.08360128617363 21.2 scent 4.536290322580645 4.5 aromatic hydrocarbon 5.94758064516129 5.9 chemical compound 15.826086956521738 9.1 nitrogen atom 29.573934837092732 11.8 aromatic hydrocarbon 8.695652173913043 5.0 ring 3.125 3.1 The configuration of six carbon atoms in aromatic compounds is called a "benzene ring", after the simple aromatic compound benzene, or a phenyl group when part of a larger compound. 39.015151515151516 20.6 organic compound 3.8306451612903225 3.8 chemical compound 10.786290322580644 10.7 Aromatic compounds are those chemical compounds (most commonly organic) that contain one or more rings with pi electrons delocalized all the way around them. 39.583333333333336 20.9 carbon atom 15.999999999999998 9.2 aromatic compound benzene 24.81203007518797 9.9 Organic chemical Economy, business and finance/Economic sector/Chemicals/Organic chemical heterocyclic compound 6.451612903225806 6.4 aromatic compound 29.739130434782613 17.1 larger compound 13.533834586466165 5.4 earth sciences 100.0 0.4569866955280304 carbon atom 10.786290322580644 10.7 benzene ring 3.528225806451613 3.5 Chemistry 10.24424/070n-rr14 False 2025-07-05 18:47:59.392957+00:00 0 https://api.rohub.org/api/ros/ba53e480-17bb-466f-b789-3533246d7b43/crate/download/ 2022-01-12 16:34:39.917729+00:00 2025-10-16 11:14:31.884055+00:00 2022-01-12 16:34:39.917729+00:00 Aromatic compounds are those chemical compounds (most commonly organic) that contain one or more rings with pi electrons delocalized all the way around them. In contrast to compounds that exhibit aromaticity, aliphatic compounds lack this delocalization. The term "aromatic" was assigned before the physical mechanism determining aromaticity was discovered, and referred simply to the fact that many such compounds have a sweet or pleasant odour; however, not all aromatic compounds have a sweet odour, and not all compounds with a sweet odour are aromatic compounds. Aromatic hydrocarbons, or arenes, are aromatic organic compounds containing solely carbon and hydrogen atoms. The configuration of six carbon atoms in aromatic compounds is called a "benzene ring", after the simple aromatic compound benzene, or a phenyl group when part of a larger compound. Not all aromatic compounds are benzene-based; aromaticity can also manifest in heteroarenes, which follow Hückel's rule (for monocyclic rings: when the number of its π electrons equals 4n + 2, where n = 0, 1, 2, 3, ...). In these compounds, at least one carbon atom is replaced by one of the heteroatoms oxygen, nitrogen, or sulfur. Examples of non-benzene compounds with aromatic properties are furan, a heterocyclic compound with a five-membered ring that includes a single oxygen atom, and pyridine, a heterocyclic compound with a six-membered ring containing one nitrogen atom. application/ld+json https://w3id.org/ro-id/ba53e480-17bb-466f-b789-3533246d7b43 Aromatic compounds - snapshot Aromatic compounds MANUAL Wolniewicz, Małgorzata. "Aromatic compounds." ROHub. Jan 12 ,2022. https://doi.org/10.24424/070n-rr14. chemistry 34.08360128617363 21.2 scent 4.536290322580645 4.5 aromatic 19.657258064516128 19.5 The term "aromatic" was assigned before the physical mechanism determining aromaticity was discovered, and referred simply to the fact that many such compounds have a sweet or pleasant odour; however, not all aromatic compounds have a sweet odour, and not all compounds with a sweet odour are aromatic compounds. 21.401515151515152 11.3 benzene 9.274193548387096 9.2 carbon atom 10.786290322580644 10.7 geochemistry 100.0 0.4569866955280304 aromatic compound benzene 24.81203007518797 9.9 aromatic compound 29.739130434782613 17.1 larger compound 13.533834586466165 5.4 arene 4.939516129032259 4.9 Jewellery Arts, culture and entertainment/Arts and entertainment/Fashion/Jewellery The configuration of six carbon atoms in aromatic compounds is called a "benzene ring", after the simple aromatic compound benzene, or a phenyl group when part of a larger compound. 39.015151515151516 20.6 arene 7.304347826086956 4.2 oxygen atom 17.794486215538846 7.1 carbon atom 15.999999999999998 9.2 Organic chemical Economy, business and finance/Economic sector/Chemicals/Organic chemical electron 4.435483870967742 4.4 aromatic hydrocarbon 8.695652173913043 5.0 chemical compound 15.826086956521738 9.1 benzene ring 3.528225806451613 3.5 heterocyclic compound 6.451612903225806 6.4 aromatic hydrocarbon 5.94758064516129 5.9 nitrogen 3.9314516129032255 3.9 organic compound 3.8306451612903225 3.8 chemistry and materials (general) 100.0 0.8506659269332886 earth sciences 100.0 0.4569866955280304 monocyclic ring 14.285714285714286 5.7 aliphatic compound 4.737903225806451 4.7 benzene 12.695652173913043 7.3 chemical compound 10.786290322580644 10.7 organic chemistry 65.91639871382637 41.0 chemistry and materials 100.0 0.8506659269332886 heterocyclic compound 9.73913043478261 5.6 Aromatic compounds are those chemical compounds (most commonly organic) that contain one or more rings with pi electrons delocalized all the way around them. 39.583333333333336 20.9 oxygen atom 4.032258064516129 4.0 nitrogen atom 29.573934837092732 11.8 ring 3.125 3.1 Chemistry https://doi.org/10.24424/x0cn-va37 False 2025-07-05 19:04:55.078129+00:00 0 https://api.rohub.org/api/ros/54c22dc5-ace3-4aaa-be62-b5b4dab97be6/crate/download/ 2022-01-12 16:34:39.917729+00:00 2025-10-16 11:14:13.082777+00:00 2022-01-12 16:34:39.917729+00:00 Aromatic compounds are those chemical compounds (most commonly organic) that contain one or more rings with pi electrons delocalized all the way around them. In contrast to compounds that exhibit aromaticity, aliphatic compounds lack this delocalization. The term "aromatic" was assigned before the physical mechanism determining aromaticity was discovered, and referred simply to the fact that many such compounds have a sweet or pleasant odour; however, not all aromatic compounds have a sweet odour, and not all compounds with a sweet odour are aromatic compounds. Aromatic hydrocarbons, or arenes, are aromatic organic compounds containing solely carbon and hydrogen atoms. The configuration of six carbon atoms in aromatic compounds is called a "benzene ring", after the simple aromatic compound benzene, or a phenyl group when part of a larger compound. Not all aromatic compounds are benzene-based; aromaticity can also manifest in heteroarenes, which follow Hückel's rule (for monocyclic rings: when the number of its π electrons equals 4n + 2, where n = 0, 1, 2, 3, ...). In these compounds, at least one carbon atom is replaced by one of the heteroatoms oxygen, nitrogen, or sulfur. Examples of non-benzene compounds with aromatic properties are furan, a heterocyclic compound with a five-membered ring that includes a single oxygen atom, and pyridine, a heterocyclic compound with a six-membered ring containing one nitrogen atom. application/ld+json https://w3id.org/ro-id/54c22dc5-ace3-4aaa-be62-b5b4dab97be6 Aromatic compounds - snapshot Aromatic compounds MANUAL Wolniewicz, Małgorzata. "Aromatic compounds." ROHub. Jan 12 ,2022. https://doi.org/10.24424/x0cn-va37. chemical compound 15.826086956521738 9.1 The configuration of six carbon atoms in aromatic compounds is called a "benzene ring", after the simple aromatic compound benzene, or a phenyl group when part of a larger compound. 39.015151515151516 20.6 aromatic hydrocarbon 5.94758064516129 5.9 benzene 9.274193548387096 9.2 carbon atom 15.999999999999998 9.2 chemical compound 10.786290322580644 10.7 electron 4.435483870967742 4.4 oxygen atom 4.032258064516129 4.0 arene 4.939516129032259 4.9 chemistry 34.08360128617363 21.2 organic chemistry 65.91639871382637 41.0 chemistry and materials 100.0 0.8506659269332886 scent 4.536290322580645 4.5 heterocyclic compound 9.73913043478261 5.6 benzene 12.695652173913043 7.3 earth sciences 100.0 0.4569866955280304 geochemistry 100.0 0.4569866955280304 The term "aromatic" was assigned before the physical mechanism determining aromaticity was discovered, and referred simply to the fact that many such compounds have a sweet or pleasant odour; however, not all aromatic compounds have a sweet odour, and not all compounds with a sweet odour are aromatic compounds. 21.401515151515152 11.3 nitrogen atom 29.573934837092732 11.8 aromatic compound 29.739130434782613 17.1 arene 7.304347826086956 4.2 Jewellery Arts, culture and entertainment/Arts and entertainment/Fashion/Jewellery aliphatic compound 4.737903225806451 4.7 Organic chemical Economy, business and finance/Economic sector/Chemicals/Organic chemical benzene ring 3.528225806451613 3.5 larger compound 13.533834586466165 5.4 nitrogen 3.9314516129032255 3.9 heterocyclic compound 6.451612903225806 6.4 aromatic hydrocarbon 8.695652173913043 5.0 aromatic 19.657258064516128 19.5 organic compound 3.8306451612903225 3.8 carbon atom 10.786290322580644 10.7 monocyclic ring 14.285714285714286 5.7 chemistry and materials (general) 100.0 0.8506659269332886 aromatic compound benzene 24.81203007518797 9.9 Aromatic compounds are those chemical compounds (most commonly organic) that contain one or more rings with pi electrons delocalized all the way around them. 39.583333333333336 20.9 ring 3.125 3.1 oxygen atom 17.794486215538846 7.1 Earth sciences Darwin MacBook-Pro-Raul-2025.local 24.5.0 Darwin Kernel Version 24.5.0: Tue Apr 22 19:53:27 PDT 2025; root:xnu-11417.121.6~2/RELEASE_ARM64_T6041 arm64 2025-05-27T10:25:53+00:00 COMPSs matmul_files.py execution at MacBook-Pro-Raul-2025.local file://MacBook-Pro-Raul-2025.local/Users/rsirvent/COMPSs-DP/matmul_files/C.0.0 file://MacBook-Pro-Raul-2025.local/Users/rsirvent/COMPSs-DP/matmul_files/C.0.1 file://MacBook-Pro-Raul-2025.local/Users/rsirvent/COMPSs-DP/matmul_files/C.1.0 file://MacBook-Pro-Raul-2025.local/Users/rsirvent/COMPSs-DP/matmul_files/C.1.1 2025-05-27T10:25:48+00:00 application_sources/matmul_files.py #compss_home #compss_python_version #localhost.matmul_tasks.multiply.avgTime #localhost.matmul_tasks.multiply.executions #localhost.matmul_tasks.multiply.maxTime #localhost.matmul_tasks.multiply.minTime #overall.matmul_files.py.executionTime #overall.matmul_tasks.multiply.avgTime #overall.matmul_tasks.multiply.executions #overall.matmul_tasks.multiply.maxTime #overall.matmul_tasks.multiply.minTime COMPSs COMPSs Programming Model 3.3.3 COMPSS_HOME /Users/rsirvent/opt/COMPSs/ COMPSS_PYTHON_VERSION 3.10.16 avgTime 68 executions 8 maxTime 106 minTime 34 executionTime 5781 avgTime 68 executions 8 maxTime 106 minTime 34 Lezzi Daniele Daniele Lezzi Vázquez Novoa Fernando Fernando Vázquez Novoa Amela Milian Ramon Ramon Amela Milian Conejero Javier Javier Conejero Iraola de Acevedo Eduardo Eduardo Iraola de Acevedo Vergés Pere Pere Vergés Puigdemunt-Schmolling Gabriel Gabriel Puigdemunt-Schmolling Bertran Marta Marta Bertran Álvarez Vecino Pol Pol Álvarez Vecino francesc.lordan@bsc.es Lordan Francesc Francesc Lordan Foyer Clément Clément Foyer Sirvent Raül Raül Sirvent Mammadli Nihad Nihad Mammadli Małgorzata Wolniewicz Badia Rosa M Rosa M Badia Ramon-Cortes Vilarrodona Cristian Cristian Ramon-Cortes Vilarrodona Ejarque Jorge Jorge Ejarque Tatu Cristian Cătălin Cristian Cătălin Tatu Giacomini Nicolò Nicolò Giacomini Dabral Archit Archit Dabral Indian Institute of Technology BHU Universitat Politècnica de Catalunya Association for Computing Machinery Baku State University Barcelona Supercomputing Center Author francesc.lordan@bsc.es francesc.lordan@bsc.es 9575 https://api.rohub.org/api/ros/cb06ef3d-f6a3-4b79-9f62-59215ec96034/crate/download/ 2025-05-27 10:25:54+00:00 2025-10-16 11:13:28.087902+00:00 2025-05-27 10:25:54+00:00 Hypermatrix size 2x2 blocks, block size 2x2 elements **THIS IS A TEST RO. IT WILL BE DELETED SOON** Hypermatrix size 2x2 blocks, block size 2x2 elements application/ld+json https://w3id.org/ro-id/cb06ef3d-f6a3-4b79-9f62-59215ec96034 application_sources/matmul_files.py #COMPSs_Workflow_Run_Crate_MacBook-Pro-Raul-2025.local_7defb487-c7d1-4c81-b77e-e886b9c7cbdf COMPSs Matrix Multiplication, out-of-core using files Nihad Mammadli, Archit Dabral, Daniele Lezzi, Pere Vergés, Nicolò Giacomini, Ramon Amela Milian, Pol Álvarez Vecino, et al. "COMPSs Matrix Multiplication, out-of-core using files." ROHub. May 27 ,2025. https://w3id.org/ro-id/cb06ef3d-f6a3-4b79-9f62-59215ec96034. A.0.0 A.0.1 A.1.0 A.1.1 B.0.0 B.0.1 B.1.0 B.1.1 C.0.0 C.0.1 C.1.0 C.1.1 application_sources 1549 https://api.rohub.org/api/resources/1dd30e86-6f7a-4cc4-8efc-da2520ac3c25/download/ 2025-07-15 12:49:20.440157+00:00 2025-07-15 12:49:29.023315+00:00 Auxiliary File text/plain matmul_tasks.py 2025-07-15 12:49:20.440157+00:00 154 https://api.rohub.org/api/resources/4ff805d8-632b-4416-ab87-327d8256de07/download/ 2025-07-15 12:49:20.442355+00:00 2025-07-15 12:49:28.797300+00:00 COMPSs submission command line (runcompss / enqueue_compss), including flags and parameters passed to the application text/plain compss_submission_command_line.txt 2025-07-15 12:49:20.442355+00:00 26cfe40aee0664efe823e349544073530f24b8e63852167d255fcc5082dd93ba 2212 https://api.rohub.org/api/resources/73823bef-90ba-4cdb-8d8c-c20c2c83d707/download/ 2025-07-15 12:49:20.440931+00:00 2025-07-15 12:49:29.685001+00:00 Main file of the COMPSs workflow source files text/plain complete_graph.svg matmul_files.py #compss 2025-07-15 12:49:20.440931+00:00 4076 https://api.rohub.org/api/resources/80978d21-476e-4b32-89b9-909a542fc680/download/ 2025-07-15 12:49:20.437431+00:00 2025-07-15 12:49:27.687270+00:00 COMPSs Workflow Provenance YAML configuration file AUTHORS_COMPSS_COMPLETE.yaml 2025-07-15 12:49:20.437431+00:00 46ec0e3f267505f663c4b36d8ef4a0f123bccac284ba75941640dbd27456e66c 338 https://api.rohub.org/api/resources/833784d6-ca80-4012-810d-82c604b5f19f/download/ 2025-07-15 12:49:20.441640+00:00 2025-07-15 12:49:27.901577+00:00 COMPSs application Tasks profile https://www.nationalarchives.gov.uk/PRONOM/fmt/817 App_Profile.json 2025-07-15 12:49:20.441640+00:00 6fdc527f609cad0e6b5ff9dd7f7a7bdfc05fac884d54747fc0d5f5da627e52c7 6313 https://api.rohub.org/api/resources/93767032-ea1f-4c91-ba27-6b28b9d383a6/download/ 2025-07-15 12:49:20.438518+00:00 2025-07-15 12:49:27.480882+00:00 The graph diagram of the workflow, automatically generated by COMPSs runtime complete_graph.svg 2025-07-15 12:49:20.438518+00:00 03fc6c911f447c2465e0d418fce444fdb574a6534fb66e086ff131ea23df414e Hypermatrix size 2x2 blocks, block size 2x2 elements **THIS IS A TEST RO. IT WILL BE DELETED SOON* 85.8858858858859 85.8 matrix multiplication 1.4271151885830784 1.4 COMPSs matrix multiplication 23.955147808358817 23.5 other earth sciences 61.94550662720011 0.7036855816841125 COMPSs Matrix Multiplication, out-of-core using files. 14.114114114114116 14.1 earth sciences 38.05449337279989 0.43228960037231445 matrix 5.148741418764302 4.5 element 15.07823613086771 10.6 earth sciences 61.94550662720011 0.7036855816841125 multiplication 4.462242562929061 3.9 test ro. 59.225280326197755 58.1 matrices 6.970128022759603 4.9 Will Be Deleted Soon 20.938215102974826 18.3 ro. 26.77345537757437 23.4 space sciences 8.603801265945089 0.05067460238933563 mathematics 100.0 1.9 size 2x2 7.339449541284403 7.2 Language Arts, culture and entertainment/Culture/Language oceanography 38.05449337279989 0.43228960037231445 test 22.99771167048055 20.1 using 4.836415362731152 3.4 element 12.814645308924485 11.2 multiplication 6.543385490753911 4.6 mathematical and computer sciences 91.3961987340549 0.5383046269416809 block size 4.694167852062589 3.3 rood 28.87624466571835 20.3 size 5.974395448079659 4.2 out-of-core using file 8.053007135575942 7.9 COMPSs 6.864988558352402 6.0 space sciences (general) 8.603801265945089 0.05067460238933563 test 27.027027027027028 19.0 Disabled Society/Mankind/Disabled computer operations and hardware 91.3961987340549 0.5383046269416809 Process Run Crate 0.5 Provenance Run Crate 0.5 Workflow Run Crate 0.5 Workflow RO-Crate 1.0 JSON Data Interchange Format YAML Scalable Vector Graphics Biology 10.24424/20ms-v465 False 2025-08-12 08:02:25.321821+00:00 0 https://api.rohub.org/api/ros/07b99b7b-a209-44cc-86fd-327339b2599c/crate/download/ 2022-01-19 13:47:59.181939+00:00 2025-10-16 11:12:08.755267+00:00 2022-01-19 13:47:59.181939+00:00 Attention deficit hyperactivity disorder (ADHD) is a behavioral and neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity, which are pervasive, impairing, and otherwise age inappropriate.Some individuals with ADHD also display difficulty regulating emotions, or problems with executive function. For a diagnosis, the symptoms have to be present for more than six months, and cause problems in at least two settings (such as school, home, work, or recreational activities). In children, problems paying attention may result in poor school performance. Additionally, it is associated with other mental disorders and substance use disorders. Although it causes impairment, particularly in modern society, many people with ADHD have sustained attention for tasks they find interesting or rewarding, known as hyperfocus. application/ld+json https://w3id.org/ro-id/07b99b7b-a209-44cc-86fd-327339b2599c Attention deficit hyperactivity disorder - snapshot Attention deficit hyperactivity disorder MANUAL Wolniewicz, Małgorzata. "Attention deficit hyperactivity disorder." ROHub. Jan 19 ,2022. https://doi.org/10.24424/20ms-v465. life sciences 100.0 0.989045262336731 distraction 5.919003115264798 5.7 neurodevelopmental disorder 62.65984654731457 49.0 environmental science and management 100.0 0.6445436477661133 behavioural disorder 7.4766355140186915 7.2 environmental sciences 100.0 0.6445436477661133 inattention 9.515260323159785 5.3 substance use disorder 19.565217391304348 15.3 life sciences (general) 100.0 0.989045262336731 diagnosis 6.645898234683282 6.4 medicine 100.0 12.8 individual 4.7767393561786085 4.6 behavioral disorder 12.208258527827647 6.8 individuals with ADHD 7.416879795396419 5.8 mental disorder 3.426791277258567 3.3 problem 9.345794392523365 9.0 attention 5.815160955347872 5.6 impulsiveness 5.815160955347872 5.6 diagnosis 10.23339317773788 5.7 disorder 10.951526032315979 6.1 symptom 4.569055036344757 4.4 attention deficit hyperactivity disorder 21.599169262720665 20.8 Mental and behavioural disorder Health/Diseases and conditions/Mental and behavioural disorder mental disorders 4.731457800511508 3.7 Attention deficit hyperactivity disorder (ADHD) is a behavioral and neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity, which are pervasive, impairing, and otherwise age inappropriate. 59.31758530183727 45.2 difficulty 10.412926391382404 5.8 disorder 12.772585669781932 12.3 For a diagnosis, the symptoms have to be present for more than six months, and cause problems in at least two settings (such as school, home, work, or recreational activities). In children, problems paying attention may result in poor school performance. 18.11023622047244 13.8 emotions 4.984423676012462 4.8 School Education/School Some individuals with ADHD also display difficulty regulating emotions, or problems with executive function. 22.572178477690287 17.2 difficulty 6.853582554517134 6.6 attention deficit hyperactivity disorder 32.85457809694793 18.3 school performance 5.626598465473147 4.4 problem 13.824057450628365 7.7 Reames B Yang X Accessions (data not in GigaDB) BioProject: PRJNA675370 Additional information Additional information Additional information Additional information Additional information Additional information Additional information Additional information Award ID GNT1195743 Awardee L Coin Dataset type Epigenomic, Bioinformatics, Software, Transcriptomic Github links Github links Github links Github links History Date: July 29, 2025, Action: Dataset publish Extra Information Data Type: Readme, File Attributes: MD5 checksum: 450ef019cf8ba58beb644ef18d1411d0 This dataset contains too many files that are not individually described other files Extra Information Data Type: Tabular data, File Attributes: MD5 checksum: 97ee210d263c783e4ddfe20352831d60 Figure in MS: 3 Extra Information Data Type: GitHub archive, File Attributes: MD5 checksum: 4b4d2ce7259e5045d89b731b7bfcf730 SWH: swh:1:snp:ee789638699e0e33ca3b1d09da5bb1f485ea7c70 license: MPL 2.0 The person who associated a work with this deed has dedicated the work to the public domain by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information below. Creative Commons Zero v1.0 Universal doi:10.5524/102736 database@gigasciencejournal.com GigaDB is a data repository supporting scientific publications in the Life/Biomedical Sciences domain. GigaDB organises and curates data from individually publishable units into datasets, which are provided openly and in as FAIR manner as possible for the global research community. GigaScience DataBase Archival copy of the GitHub repository https://github.com/haotianteng/BoostNano downloaded 18-July-2025. BoostNano, a tool for preprocessing ONT-Nanopore RNA sequencing reads.This project is licensed under the MPL 2.0 license. Please refer to the GitHub repo for most recent updates. #zipExtra BoostNano-master 2025-07-23 oxford nanopore technologies Chang JJ Coin LJM Teng H Corbin V The University of Melbourne Carnegie Mellon University contact of the publisher database@gigasciencejournal.com database@gigasciencejournal.com Funding Body #awardId #awardee National Health and Medical Research Council application/zip https://s3.ap-northeast-1.wasabisys.com/gigadb-datasets/live/pub/10.5524/102001_103000/102736/boostnano_no_dorado_R1_tails.csv 2025-08-28 04:09:14.859328+00:00 2025-08-28 04:09:16.525835+00:00 PolyA tail lengths as found by Boostnano for R1 sequins which were filtered out by Dorado but kept by Boostnano; underlying data for figure 3 text/csv #twoExtra boostnano_no_dorado_R1_tails.csv 2025-08-28 04:09:14.859328+00:00 https://s3.ap-northeast-1.wasabisys.com/gigadb-datasets/live/pub/10.5524/102001_103000/102736/readme_102736.txt 2025-08-28 04:09:14.858721+00:00 2025-08-28 04:09:15.483716+00:00 text/txt #oneExtra readme_102736.txt 2025-08-28 04:09:14.858721+00:00 8266 https://api.rohub.org/api/ros/3543b082-9077-492e-a4c7-a3b7c8bb39e8/crate/download/ 2025-07-29 00:00:00 2025-10-16 11:11:58.719757+00:00 2025-07-29 00:00:00 Polyadenylation is a dynamic process which is important in cellular physiology. Oxford Nanopore Technologies direct RNA-sequencing provides a strategy for sequencing the full-length RNA molecule and analysis of the transcriptome and epi-transcriptome. There are currently several tools available for poly(A) tail-length estimation, including well-established tools such as tailfindr and nanopolish, as well as two more recent deep learning models: Dorado and BoostNano. However, there has been limited benchmarking of the accuracy of these tools against gold-standard datasets. In this paper we evaluate four poly(A) estimation tools using synthetic RNA standards (Sequins), which have known poly(A) tail-lengths and provide a valuable approach to measuring the accuracy of poly(A) tail-length estimation. All four tools generate mean tail-length estimates which lie within 12% of the correct value. Overall, Dorado is recommended as the preferred approach due to its relatively fast run times, low coefficient of variation and ease of use with integration with base-calling. application/ld+json #accessions #additionalInfo1 #additionalInfo2 #additionalInfo3 #additionalInfo4 #additionalInfo5 #additionalInfo6 #additionalInfo7 #additionalInfo8 #datasetTypes #githubLink1 #githubLink2 #githubLink3 #githubLink4 #history https://w3id.org/ro-id/3543b082-9077-492e-a4c7-a3b7c8bb39e8 oxford nanopore technologies, poly(a) tail, estimation, segmentation, direct rna sequencing Supporting data for "Using synthetic RNA to benchmark poly(A) length inference from direct RNA sequencing." Chang JJ, Coin LJM, Teng H, Corbin V, Yang X, and Reames B. "Supporting data for "Using synthetic RNA to benchmark poly(A) length inference from direct RNA sequencing."." ROHub. Jul 29 ,2025. https://w3id.org/ro-id/3543b082-9077-492e-a4c7-a3b7c8bb39e8. polyester 10.658307210031346 10.2 oceanography 100.0 0.4704064726829529 strategy 5.120167189132707 4.9 molecule 9.621993127147766 5.6 estimate 8.986415882967608 8.6 life sciences (general) 100.0 0.8512763977050781 estimation 12.199312714776632 7.1 Oxford Nanopore Technologies direct RNA-sequencing provides a strategy for sequencing the full-length RNA molecule and analysis of the transcriptome and epi-transcriptome. 34.26966292134831 24.4 RNA standard 22.157996146435455 11.5 dataset 4.075235109717868 3.9 gold standard 3.3437826541274815 3.2 Textile and clothing Economy, business and finance/Economic sector/Process industry/Textile and clothing RNA sequencing 21.965317919075144 11.4 ribonucleic acid 17.763845350052247 17.0 transcriptome 11.285266457680251 10.8 RNA 24.570446735395187 14.3 length 3.3437826541274815 3.2 In this paper we evaluate four poly(A) estimation tools using synthetic RNA standards (Sequins), which have known poly(A) tail-lengths and provide a valuable approach to measuring the accuracy of poly(A) tail-length estimation. 17.696629213483146 12.6 estimation tool 17.919075144508675 9.3 genetics 100.0 8.1 transcriptome 15.29209621993127 8.9 Genetics Science and technology/Natural science/Biology/Genetics Supporting data for "Using synthetic RNA to benchmark poly(A) length inference from direct RNA sequencing. 48.033707865168545 34.2 earth sciences 100.0 0.4704064726829529 sequencing 12.027491408934708 7.0 Dorado 8.045977011494253 7.7 tail-length estimation 11.946050096339114 6.2 Dorado 11.512027491408935 6.7 molecule 7.105538140020898 6.8 RNA molecule 26.01156069364162 13.5 life sciences 100.0 0.8512763977050781 sequencing 8.359456635318704 8.0 accuracy 5.015673981191222 4.8 poly 14.776632302405497 8.6 coefficient of variation 3.657262277951933 3.5 tool 3.239289446185998 3.1 alex tsang Environmental research https://doi.org/10.5281/zenodo.17171136 2025-09-22 10:48:24.562016+00:00 2025-09-22 10:48:25.226799+00:00 Contains outputs, (results), generated in the Jupyter notebook of Vehicle-based observation data processing and simple simulation experiments Outputs 2025-09-22 10:48:24.562016+00:00 https://doi.org/10.5281/zenodo.17175792 2025-09-22 10:48:22.888533+00:00 2025-09-22 10:48:23.594034+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 10:48:22.888533+00:00 https://github.com/eds-book/dea59792-5a6d-4633-a74c-eb73edce61b8/blob/main/notebook.ipynb 2025-09-22 10:48:20.987054+00:00 2025-09-22 10:48:21.788847+00:00 Jupyter Notebook hosted by the Environmental Data Science Book Jupyter notebook 2025-09-22 10:48:20.987054+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 Computational notebooks community focused on Environmental Data Science environmental.ds.book@gmail.com Environmental Data Science Book Community https://github.com/alan-turing-institute/environmental-ds-book/issues/new/choose 0 https://api.rohub.org/api/ros/d14c540e-0a98-4c7f-a028-d535535369ac/crate/download/ 2025-09-22 10:47:58.115149+00:00 2025-10-16 11:11:37.969501+00:00 2025-09-22 10:47:58.115149+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/d14c540e-0a98-4c7f-a028-d535535369ac 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. Sep 22 ,2025. https://w3id.org/ro-id/d14c540e-0a98-4c7f-a028-d535535369ac. output biblio tool input 100693 https://api.rohub.org/api/resources/8b27e6dc-ac97-4c73-8d99-d9dea59f1f5a/download/ 2025-09-22 10:48:18.468040+00:00 2025-09-22 10:48:19.978707+00:00 image/png Image showing an example of the vehicle-based observation emissions data 2025-09-22 10:48:18.468040+00:00 simulation 12.0 9.9 Environmental Data Science book 12.727272727272727 11.9 experiment 18.78787878787879 15.5 mathematical and computer sciences 100.0 0.24472567439079285 earth sciences 100.0 0.7707348465919495 research object 22.352941176470587 20.9 Environmental Data Science 12.542759407069555 11.0 atmospheric sciences 100.0 0.7707348465919495 simulation 10.946408209806156 9.6 notebook 11.516533637400228 10.1 Book industry Economy, business and finance/Economic sector/Media/Book industry aim 7.2727272727272725 6.0 Literature Arts, culture and entertainment/Arts and entertainment/Literature notebook 12.0 9.9 observation data processing 33.04812834224599 30.9 computer operations and hardware 100.0 0.24472567439079285 simulation experiments notebook 2.5668449197860963 2.4 Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book. 46.046046046046044 46.0 The research object refers to the Vehicle-based observation data processing and simple simulation experiments notebook published in the Environmental Data Science book. 53.95395395395395 53.9 data processing 28.164196123147093 24.7 research 9.454545454545455 7.8 book 10.376282782212087 9.1 experiment 17.44583808437856 15.3 data processing 28.96969696969697 23.9 simulation experiment 29.3048128342246 27.4 publishing 100.0 4.4 book 11.515151515151516 9.5 research 9.007981755986316 7.9 Language Arts, culture and entertainment/Culture/Language Environmental Data Science Book Community Westlake University yangjianqi@westlake.edu.cn Lucky J. Yang Environmental research https://doi.org/10.5281/zenodo.17171136 2025-09-22 10:49:18.454535+00:00 2025-09-22 10:49:19.122602+00:00 Contains outputs, (results), generated in the Jupyter notebook of Vehicle-based observation data processing and simple simulation experiments Outputs 2025-09-22 10:49:18.454535+00:00 https://doi.org/10.5281/zenodo.17175792 2025-09-22 10:49:16.843742+00:00 2025-09-22 10:49:17.507885+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 10:49:16.843742+00:00 https://github.com/eds-book/dea59792-5a6d-4633-a74c-eb73edce61b8/blob/main/notebook.ipynb 2025-09-22 10:49:14.547747+00:00 2025-09-22 10:49:15.345765+00:00 Jupyter Notebook hosted by the Environmental Data Science Book Jupyter notebook 2025-09-22 10:49:14.547747+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/0b449ecb-dc8f-4ba0-9211-8bb9864ce7e2/crate/download/ 2025-09-22 10:48:52.986447+00:00 2025-10-16 11:11:19.223037+00:00 2025-09-22 10:48:52.986447+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/0b449ecb-dc8f-4ba0-9211-8bb9864ce7e2 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. Sep 22 ,2025. https://w3id.org/ro-id/0b449ecb-dc8f-4ba0-9211-8bb9864ce7e2. output biblio input tool 100693 https://api.rohub.org/api/resources/41e32a87-e2e9-44a8-9317-e1a03e8423bc/download/ 2025-09-22 10:49:12.096244+00:00 2025-09-22 10:49:13.527385+00:00 image/png Image showing an example of the vehicle-based observation emissions data 2025-09-22 10:49:12.096244+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. 53.95395395395395 53.9 aim 7.2727272727272725 6.0 Environmental Data Science book 12.727272727272727 11.9 Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book. 46.046046046046044 46.0 research 9.454545454545455 7.8 Book industry Economy, business and finance/Economic sector/Media/Book industry simulation 12.0 9.9 notebook 11.516533637400228 10.1 data processing 28.96969696969697 23.9 mathematical and computer sciences 100.0 0.24472567439079285 book 10.376282782212087 9.1 earth sciences 100.0 0.7707348465919495 computer operations and hardware 100.0 0.24472567439079285 Literature Arts, culture and entertainment/Arts and entertainment/Literature Language Arts, culture and entertainment/Culture/Language research 9.007981755986316 7.9 publishing 100.0 4.4 simulation experiment 29.3048128342246 27.4 observation data processing 33.04812834224599 30.9 experiment 18.78787878787879 15.5 Environmental Data Science 12.542759407069555 11.0 research object 22.352941176470587 20.9 notebook 12.0 9.9 simulation experiments notebook 2.5668449197860963 2.4 simulation 10.946408209806156 9.6 atmospheric sciences 100.0 0.7707348465919495 book 11.515151515151516 9.5 experiment 17.44583808437856 15.3 data processing 28.164196123147093 24.7 Environmental Data Science Book Community Westlake University yangjianqi@westlake.edu.cn Lucky J. Yang 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. Sep 22 ,2025. https://w3id.org/ro-id/368f9594-6513-4f49-a510-275c07b1c3b6. output tool input biblio 100693 https://api.rohub.org/api/resources/59322158-c890-4018-9316-71e09c41c47f/download/ 2025-09-22 10:50:34.313127+00:00 2025-09-22 10:50:35.343626+00:00 image/png Image showing an example of the vehicle-based observation emissions data 2025-09-22 10:50:34.313127+00:00 Literature Arts, culture and entertainment/Arts and entertainment/Literature Language Arts, culture and entertainment/Culture/Language publishing 100.0 4.4 simulation 10.946408209806156 9.6 data processing 28.164196123147093 24.7 experiment 17.44583808437856 15.3 aim 7.2727272727272725 6.0 experiment 18.78787878787879 15.5 observation data processing 33.04812834224599 30.9 research object 22.352941176470587 20.9 research 9.007981755986316 7.9 research 9.454545454545455 7.8 notebook 11.516533637400228 10.1 simulation experiments notebook 2.5668449197860963 2.4 Environmental Data Science book 12.727272727272727 11.9 atmospheric sciences 100.0 0.7707348465919495 Environmental Data Science 12.542759407069555 11.0 mathematical and computer sciences 100.0 0.24472567439079285 data processing 28.96969696969697 23.9 Vehicle-based observation data processing and simple simulation experiments (Jupyter Notebook) published in the Environmental Data Science book. 46.046046046046044 46.0 simulation experiment 29.3048128342246 27.4 earth sciences 100.0 0.7707348465919495 computer operations and hardware 100.0 0.24472567439079285 book 11.515151515151516 9.5 The research object refers to the Vehicle-based observation data processing and simple simulation experiments notebook published in the Environmental Data Science book. 53.95395395395395 53.9 book 10.376282782212087 9.1 notebook 12.0 9.9 simulation 12.0 9.9 Book industry Economy, business and finance/Economic sector/Media/Book industry Environmental Data Science Book Community Westlake University yangjianqi@westlake.edu.cn Lucky J. 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 2026-01-30 09:59:27.538232+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. Oct 07 ,2025. https://w3id.org/ro-id/ce69f062-5218-46b5-8d8a-2437af6355a2. 21822682 https://api.rohub.org/api/resources/ad4b6c36-5b90-44e1-be83-817abd445362/download/ 2025-11-06 09:46:10.933493+00:00 2025-11-06 09:46:13.577204+00:00 image/gif CityOfHamburg.gif 2025-11-06 09:46:10.933493+00:00 13338612 https://api.rohub.org/api/resources/f7d355b2-953d-448b-8d7a-9e6707be1519/download/ 2025-11-06 09:43:34.390228+00:00 2025-11-06 09:43:35.910807+00:00 image/png cagrilabs.png 2025-11-06 09:43:34.390228+00:00 7863106 https://api.rohub.org/api/resources/fba8a89f-2f31-4565-a2c0-1a02be8abb8c/download/ 2025-11-06 09:44:59.782479+00:00 2025-11-06 09:45:01.504640+00:00 application/zip CGFP.zip 2025-11-06 09:44:59.782479+00:00 RO-Crate is a community effort to establish a lightweight approach to packaging research data with their metadata. It is based on schema.org annotations in JSON-LD, and aims to make best-practice in formal metadata description accessible and practical for use in a wider variety of situations, from an individual researcher working with a folder of data, to large data-intensive computational research environments. info@esciencelab.org.uk RO-crate https://www.researchobject.org/ro-crate/ demo 9.73360655737705 9.5 earth 13.728813559322035 8.1 earth 7.78688524590164 7.6 geology 100.0 0.9927062392234802 resources for the demo 11.534603811434303 11.5 scientist 12.807377049180328 12.5 This Research Object aggregates some relevant resources for the demo 67.36736736736736 67.3 Research Object 23.975409836065577 23.4 workshop 18.305084745762713 10.8 Education Education space sciences 100.0 0.34137117862701416 relevant resource 4.212637913741224 4.2 earth sciences 100.0 0.9927062392234802 RO-Crate workshop 36.40922768304914 36.3 resource 19.15983606557377 18.7 RO-Crate 15.57377049180328 15.2 resource 31.016949152542374 18.3 workshop 10.963114754098362 10.7 space sciences (general) 100.0 0.34137117862701416 demo version 15.932203389830509 9.4 earth scientist 47.7432296890672 47.6 Science and technology Science and technology relevant resources for the demo 0.10030090270812438 0.1 scientist 21.016949152542374 12.4 RO-Crate workshop for earth scientists. 32.63263263263263 32.6 Raul Palma 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 0527eb4e-b7c8-4ac0-9b85-52e0773c3b79 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. 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 Applied sciences Biology Climatology Geographical information system Earth observation 1364570 https://api.rohub.org/api/ros/416a0645-07b8-4c30-99be-a80481dab614/crate/download/ 2025-10-13 11:12:49.327063+00:00 2025-12-17 10:09:09.612910+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/416a0645-07b8-4c30-99be-a80481dab614 FAIR climate change heat Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal MANUAL Gomes Marques, Ines, Francisca Simões, 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/416a0645-07b8-4c30-99be-a80481dab614. 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/046b8c59-bbbf-4a38-ae80-1135d5e267f4/download/ 2025-10-13 11:48:29.771773+00:00 2025-11-13 12:51:59.085534+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 398943 https://api.rohub.org/api/resources/d48caeb1-82d1-4a1a-b25c-2a660fbb70c9/download/ 2025-10-13 11:18:02.624724+00:00 2025-11-13 12:51:58.864576+00:00 image/png NatAdaptHub.png 2025-10-13 11:18:02.624724+00:00 Portugal 14.640522875816993 11.2 metadata 11.924119241192415 4.4 availability 10.569105691056912 3.9 stakeholder 5.228758169934641 4.0 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences data 16.260162601626018 6.0 Information Sciences Institute geosciences 100.0 0.8513408899307251 meteorology and climatology 100.0 0.8513408899307251 sector 7.0588235294117645 5.4 Portugal 20.05420054200542 7.4 from 15 years data 16.260162601626018 6.0 meteorology 20.979020979020977 3.0 meteorology 20.979020979020977 3.0 Climate change Environment/Climate change stakeholder 5.228758169934641 4.0 data 11.895424836601308 9.1 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 climate change adaptation in Portugal 11.780821917808218 4.3 Climate change Environment/Climate change Portugal scientific research 11.924119241192415 4.4 between Jan-2010 and May-2025 Information Sciences Institute between Jan-2010 and May-2025 earth sciences 100.0 0.9895771741867065 climate adaptation community 22.739726027397264 8.3 article 13.279132791327916 4.9 Facing heat extremes: lessons learned from 15 years of climate change adaptation in Portugal. 38.56041131105398 15.0 sector 7.0588235294117645 5.4 ecology 31.468531468531467 4.5 application of fair 14.794520547945206 5.4 10-Oct-12-2025 meteorology and climatology 100.0 0.8513408899307251 computer science 20.27972027972028 2.9 heat extreme 16.438356164383563 6.0 article 13.279132791327916 4.9 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences 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 heat 4.836601307189542 3.7 assessment 4.967320261437909 3.8 heat event 12.602739726027396 4.6 dataset 15.989159891598916 5.9 10-Oct-12-2025 metadata 11.924119241192415 4.4 metadata 8.758169934640524 6.7 since 2010 climate 8.235294117647058 6.3 in 2010 knowledge sector 21.643835616438356 7.9 availability 10.569105691056912 3.9 availability 12.026143790849671 9.2 application of fair 14.794520547945206 5.4 in 2010 availability 12.026143790849671 9.2 climate 8.235294117647058 6.3 Weather Weather data 11.895424836601308 9.1 scientific research 8.627450980392156 6.6 knowledge sector 21.643835616438356 7.9 heat 4.836601307189542 3.7 Science and technology Science and technology database 27.27272727272727 3.9 Science and technology Science and technology climate change adaptation in Portugal 11.780821917808218 4.3 geosciences 100.0 0.8513408899307251 dataset 13.72549019607843 10.5 atmospheric sciences 100.0 0.9895771741867065 metadata 8.758169934640524 6.7 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 climate adaptation community 22.739726027397264 8.3 scientific research 8.627450980392156 6.6 Portugal 20.05420054200542 7.4 ecology 31.468531468531467 4.5 dataset 13.72549019607843 10.5 since 2010 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 dataset 15.989159891598916 5.9 computer science 20.27972027972028 2.9 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 earth sciences 100.0 0.9895771741867065 assessment 4.967320261437909 3.8 Anna Strusińska ce3c@ciencias.ulisboa.pt CE3C - Centre for Ecology, Evolution and Environmental Changes francisca.simoes@edu.ulisboa.pt Francisca Simões Environmental research 0 https://api.rohub.org/api/ros/bc6f13f4-e7d6-4490-ae63-3dff3939f914/crate/download/ 2025-12-07 19:52:04.926440+00:00 2026-04-11 09:47:42.427406+00:00 2025-12-07 19:52:04.926440+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/bc6f13f4-e7d6-4490-ae63-3dff3939f914 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/bc6f13f4-e7d6-4490-ae63-3dff3939f914. output biblio input tool Water management Climate change impacts, risks and adaptation Geographical Scope tool 17.95543905635649 13.7 Institutional: Government policies and programs Weather phenomena Weather/Weather phenomena Climate-ADAPT Adaptation Sectors data pipelining tool 36.442786069651746 29.3 Stakeholders water datum 5.72139303482587 4.6 fact 21.62516382699869 16.5 Academia/ Research Institutions Book industry Economy, business and finance/Economic sector/Media/Book industry European Continent Language Arts, culture and entertainment/Culture/Language book 7.601572739187418 5.8 Storms Key Type Measures User Needs (RAST) data visualization 16.43132220795892 12.8 Funding tool in r 26.74129353233831 21.5 datum 22.0795892169448 17.2 Methodology Geosciences pipeline processing 11.926605504587156 9.1 research 9.82961992136304 7.5 IPCC Climate Hazard research object 22.63681592039801 18.2 data 16.775884665792923 12.8 Engineering Engineering (General) Geosciences (General) Academic/ Institutional Environmental Data Science 9.242618741976893 7.2 Policy Scale Environmental Data Science book 8.45771144278607 6.8 none Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 No policy or regulation Literature Arts, culture and entertainment/Arts and entertainment/Literature Environmental Science and Management Weather Weather research 10.141206675224646 7.9 Preparing the ground pipelining 12.708600770218228 9.9 aim 6.553079947575361 5.0 tool 18.485237483953785 14.4 Environmental Sciences Physical and Technological Knowledge Sector (EEA) notebook 7.732634338138926 5.9 data 10.91142490372272 8.5 computer science 100.0 15.9 Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Environmental research data visualization 16.43132220795892 12.8 water datum 5.72139303482587 4.6 computer science 100.0 15.9 Policy Scale IPCC Weather Weather Environmental Science and Management Climate-ADAPT Adaptation Sectors research 10.141206675224646 7.9 aim 6.553079947575361 5.0 notebook 7.732634338138926 5.9 Environmental Sciences European Continent tool in r 26.74129353233831 21.5 Literature Arts, culture and entertainment/Arts and entertainment/Literature Water management Climate change impacts, risks and adaptation data pipelining tool 36.442786069651746 29.3 tool 18.485237483953785 14.4 Environmental Data Science book 8.45771144278607 6.8 research object 22.63681592039801 18.2 Physical and Technological Environmental Data Science 9.242618741976893 7.2 Institutional: Government policies and programs tool 17.95543905635649 13.7 book 7.601572739187418 5.8 research 9.82961992136304 7.5 Methodology Geosciences (General) none Book industry Economy, business and finance/Economic sector/Media/Book industry No policy or regulation Funding Storms Geographical Scope Language Arts, culture and entertainment/Culture/Language Engineering (General) Weather phenomena Weather/Weather phenomena Knowledge Sector (EEA) Geosciences Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 Engineering Academia/ Research Institutions fact 21.62516382699869 16.5 Key Type Measures Stakeholders Academic/ Institutional data 16.775884665792923 12.8 User Needs (RAST) pipelining 12.708600770218228 9.9 data 10.91142490372272 8.5 Preparing the ground datum 22.0795892169448 17.2 Climate Hazard pipeline processing 11.926605504587156 9.1 0 https://api.rohub.org/api/ros/f4cfe8f4-abcc-41b0-9c8d-8a01bed66730/crate/download/ 2025-12-07 19:52:30.693118+00:00 2026-04-11 09:48:02.572671+00:00 2025-12-07 19:52:30.693118+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/f4cfe8f4-abcc-41b0-9c8d-8a01bed66730 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Community, Environmental Data Science Book. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/f4cfe8f4-abcc-41b0-9c8d-8a01bed66730. input output biblio tool Environmental Data Science Book Community Environmental research 0 https://api.rohub.org/api/ros/3a33645c-7d45-452b-a53d-0133d12e991f/crate/download/ 2025-12-07 19:54:27.990497+00:00 2026-04-11 09:47:22.278061+00:00 2025-12-07 19:54:27.990497+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/3a33645c-7d45-452b-a53d-0133d12e991f Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/3a33645c-7d45-452b-a53d-0133d12e991f. output biblio input tool data 16.775884665792923 12.8 Preparing the ground Academia/ Research Institutions research object 22.63681592039801 18.2 Methodology Physical and Technological IPCC Geographical Scope Water management Institutional: Government policies and programs Climate change impacts, risks and adaptation data visualization 16.43132220795892 12.8 Weather phenomena Weather/Weather phenomena book 7.601572739187418 5.8 pipeline processing 11.926605504587156 9.1 Storms Weather Weather Book industry Economy, business and finance/Economic sector/Media/Book industry fact 21.62516382699869 16.5 aim 6.553079947575361 5.0 Environmental Data Science 9.242618741976893 7.2 Geosciences Academic/ Institutional Engineering (General) Engineering research 10.141206675224646 7.9 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 Knowledge Sector (EEA) Language Arts, culture and entertainment/Culture/Language notebook 7.732634338138926 5.9 Literature Arts, culture and entertainment/Arts and entertainment/Literature data pipelining tool 36.442786069651746 29.3 water datum 5.72139303482587 4.6 tool 17.95543905635649 13.7 Policy Scale Environmental Data Science book 8.45771144278607 6.8 User Needs (RAST) European Continent Climate Hazard computer science 100.0 15.9 No policy or regulation tool in r 26.74129353233831 21.5 pipelining 12.708600770218228 9.9 tool 18.485237483953785 14.4 Climate-ADAPT Adaptation Sectors research 9.82961992136304 7.5 Environmental Sciences data 10.91142490372272 8.5 Environmental Science and Management Geosciences (General) Stakeholders datum 22.0795892169448 17.2 Key Type Measures none Funding Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Environmental research 0 https://api.rohub.org/api/ros/acefb4d3-e320-4df8-a8b1-17cfa1a40ea0/crate/download/ 2025-12-07 19:54:45.553533+00:00 2026-04-11 09:47:32.519324+00:00 2025-12-07 19:54:45.553533+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/acefb4d3-e320-4df8-a8b1-17cfa1a40ea0 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/acefb4d3-e320-4df8-a8b1-17cfa1a40ea0. tool output input biblio none Academia/ Research Institutions Physical and Technological Weather phenomena Weather/Weather phenomena research object 22.63681592039801 18.2 Geosciences (General) Environmental Sciences IPCC Institutional: Government policies and programs Climate change impacts, risks and adaptation Methodology data 10.91142490372272 8.5 Engineering (General) research 9.82961992136304 7.5 Climate-ADAPT Adaptation Sectors Knowledge Sector (EEA) No policy or regulation computer science 100.0 15.9 data visualization 16.43132220795892 12.8 Environmental Science and Management Preparing the ground aim 6.553079947575361 5.0 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 fact 21.62516382699869 16.5 tool 18.485237483953785 14.4 Geographical Scope water datum 5.72139303482587 4.6 data 16.775884665792923 12.8 pipeline processing 11.926605504587156 9.1 Funding Key Type Measures Environmental Data Science 9.242618741976893 7.2 book 7.601572739187418 5.8 Weather Weather Book industry Economy, business and finance/Economic sector/Media/Book industry Engineering Storms tool in r 26.74129353233831 21.5 Environmental Data Science book 8.45771144278607 6.8 notebook 7.732634338138926 5.9 Language Arts, culture and entertainment/Culture/Language Literature Arts, culture and entertainment/Arts and entertainment/Literature User Needs (RAST) Stakeholders pipelining 12.708600770218228 9.9 Water management data pipelining tool 36.442786069651746 29.3 tool 17.95543905635649 13.7 European Continent research 10.141206675224646 7.9 datum 22.0795892169448 17.2 Policy Scale Academic/ Institutional Geosciences Climate Hazard Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Environmental research 0 https://api.rohub.org/api/ros/70040ead-8d3e-4e1d-ab67-2472d302dabd/crate/download/ 2025-12-07 19:55:20.674161+00:00 2026-04-11 09:47:52.885307+00:00 2025-12-07 19:55:20.674161+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/70040ead-8d3e-4e1d-ab67-2472d302dabd Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/70040ead-8d3e-4e1d-ab67-2472d302dabd. input output tool biblio Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 Geographical Scope research 10.141206675224646 7.9 Geosciences aim 6.553079947575361 5.0 fact 21.62516382699869 16.5 data pipelining tool 36.442786069651746 29.3 IPCC none Storms Climate change impacts, risks and adaptation tool 17.95543905635649 13.7 Literature Arts, culture and entertainment/Arts and entertainment/Literature pipeline processing 11.926605504587156 9.1 Preparing the ground data 10.91142490372272 8.5 Book industry Economy, business and finance/Economic sector/Media/Book industry Methodology Climate Hazard Weather Weather datum 22.0795892169448 17.2 Climate-ADAPT Adaptation Sectors Geosciences (General) data 16.775884665792923 12.8 tool 18.485237483953785 14.4 No policy or regulation research object 22.63681592039801 18.2 Weather phenomena Weather/Weather phenomena Funding tool in r 26.74129353233831 21.5 Language Arts, culture and entertainment/Culture/Language water datum 5.72139303482587 4.6 Key Type Measures Environmental Data Science 9.242618741976893 7.2 Stakeholders Environmental Sciences Engineering (General) computer science 100.0 15.9 Policy Scale Academic/ Institutional Academia/ Research Institutions European Continent data visualization 16.43132220795892 12.8 Water management Environmental Data Science book 8.45771144278607 6.8 Environmental Science and Management User Needs (RAST) Knowledge Sector (EEA) Physical and Technological Institutional: Government policies and programs pipelining 12.708600770218228 9.9 book 7.601572739187418 5.8 Engineering notebook 7.732634338138926 5.9 research 9.82961992136304 7.5 Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Environmental research 0 https://api.rohub.org/api/ros/18c1e606-b72e-4971-964a-af90a0503f41/crate/download/ 2025-12-07 19:55:29.829541+00:00 2026-04-11 09:48:22.768026+00:00 2025-12-07 19:55:29.829541+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/18c1e606-b72e-4971-964a-af90a0503f41 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/18c1e606-b72e-4971-964a-af90a0503f41. biblio output tool input Policy Scale water datum 5.72139303482587 4.6 Water management Environmental Science and Management Environmental Data Science book 8.45771144278607 6.8 Stakeholders Climate change impacts, risks and adaptation Physical and Technological Key Type Measures book 7.601572739187418 5.8 Institutional: Government policies and programs Geosciences (General) Environmental Sciences Storms tool 18.485237483953785 14.4 Literature Arts, culture and entertainment/Arts and entertainment/Literature computer science 100.0 15.9 Academia/ Research Institutions aim 6.553079947575361 5.0 User Needs (RAST) Geosciences pipelining 12.708600770218228 9.9 Weather phenomena Weather/Weather phenomena Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 No policy or regulation Climate-ADAPT Adaptation Sectors none Geographical Scope datum 22.0795892169448 17.2 Funding fact 21.62516382699869 16.5 Language Arts, culture and entertainment/Culture/Language pipeline processing 11.926605504587156 9.1 Knowledge Sector (EEA) IPCC European Continent Methodology Engineering (General) research 10.141206675224646 7.9 research object 22.63681592039801 18.2 Academic/ Institutional notebook 7.732634338138926 5.9 Environmental Data Science 9.242618741976893 7.2 Weather Weather data pipelining tool 36.442786069651746 29.3 Engineering data 10.91142490372272 8.5 Preparing the ground tool in r 26.74129353233831 21.5 tool 17.95543905635649 13.7 Book industry Economy, business and finance/Economic sector/Media/Book industry data 16.775884665792923 12.8 Climate Hazard data visualization 16.43132220795892 12.8 research 9.82961992136304 7.5 Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Environmental research Stakeholders Climate Hazard book 7.601572739187418 5.8 User Needs (RAST) tool 18.485237483953785 14.4 Engineering IPCC Environmental Data Science 9.242618741976893 7.2 Environmental Data Science book 8.45771144278607 6.8 research 10.141206675224646 7.9 Weather Weather pipeline processing 11.926605504587156 9.1 European Continent computer science 100.0 15.9 Water management research object 22.63681592039801 18.2 aim 6.553079947575361 5.0 Policy Scale none research 9.82961992136304 7.5 Language Arts, culture and entertainment/Culture/Language notebook 7.732634338138926 5.9 Climate change impacts, risks and adaptation data 10.91142490372272 8.5 Literature Arts, culture and entertainment/Arts and entertainment/Literature Storms Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. 100.0 100.0 Book industry Economy, business and finance/Economic sector/Media/Book industry Academic/ Institutional Physical and Technological Institutional: Government policies and programs Climate-ADAPT Adaptation Sectors Preparing the ground Geosciences No policy or regulation water datum 5.72139303482587 4.6 fact 21.62516382699869 16.5 Geosciences (General) Environmental Science and Management Key Type Measures data 16.775884665792923 12.8 Geographical Scope tool in r 26.74129353233831 21.5 Weather phenomena Weather/Weather phenomena Engineering (General) Knowledge Sector (EEA) pipelining 12.708600770218228 9.9 Academia/ Research Institutions Environmental Sciences data visualization 16.43132220795892 12.8 datum 22.0795892169448 17.2 Methodology data pipelining tool 36.442786069651746 29.3 tool 17.95543905635649 13.7 Funding 0 https://api.rohub.org/api/ros/fa165103-2ad7-426e-baf0-b8f52a130720/crate/download/ 2025-12-07 19:55:45.229974+00:00 2026-04-11 09:48:12.622500+00:00 2025-12-07 19:55:45.229974+00:00 The research object refers to the Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data notebook published in the Environmental Data Science book. application/ld+json https://w3id.org/ro-id/fa165103-2ad7-426e-baf0-b8f52a130720 Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book MANUAL Abner Bogan, and Lindsay Platt. "Using a robust data pipelining tool in R to build a reproducible hurricane data visualization with multi-agency water data (Jupyter Notebook) published in the Environmental Data Science book." ROHub. Dec 07 ,2025. https://w3id.org/ro-id/fa165103-2ad7-426e-baf0-b8f52a130720. input biblio output tool Consortium of Universities for the Advancement of Hydrologic Science, Inc. abogan@cuahsi.org Abner Bogan Environmental Data Science Book Community Consortium of Universities for the Advancement of Hydrologic Science, Inc. lplatt@cuahsi.org Lindsay Platt Earth observation https://github.com/EOPF-Sample-Service/eopf-sample-notebooks 2025-12-21 14:59:18.341013+00:00 2025-12-21 14:59:18.963543+00:00 ESA Earth Observation Processing Framework for Sentinel-1, 2 and 3 data access EOPF Sample Service 2025-12-21 14:59:18.341013+00:00 https://github.com/geojupyter/jupytergis 2025-12-21 14:59:14.270649+00:00 2025-12-21 14:59:14.934927+00:00 Collaborative GIS environment for Jupyter - required to open .jGIS files JupyterGIS 2025-12-21 14:59:14.270649+00:00 Anne Fouilloux https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/../requirements.txt 2025-12-21 14:59:16.320382+00:00 2025-12-21 14:59:16.930237+00:00 Conda environment specification with all Python dependencies text/plain Conda Environment 2025-12-21 14:59:16.320382+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/Wetland_ML_Demo_EOPF.ipynb 2025-12-21 14:59:20.404796+00:00 2025-12-21 14:59:21.070859+00:00 Main Jupyter notebook implementing the wetland classification workflow Wetland ML Demo Notebook 2025-12-21 14:59:20.404796+00:00 0 https://api.rohub.org/api/ros/972ba092-9239-4947-9bf6-495c53e57266/crate/download/ 2025-12-21 14:59:12.328362+00:00 2026-04-11 03:22:47.701619+00:00 2025-12-21 14:59:12.328362+00:00 Human-in-the-loop machine learning workflow for wetland classification using Sentinel-2 data from ESA EOPF. Demonstrates collaborative annotation using JupyterGIS, model retraining with expert corrections, and FAIR research practices. application/ld+json https://w3id.org/ro-id/972ba092-9239-4947-9bf6-495c53e57266 JupyterGIS Wetland Classification Demo - ESA EOPF MANUAL Fouilloux, Anne. "JupyterGIS Wetland Classification Demo - ESA EOPF." ROHub. Dec 21 ,2025. https://w3id.org/ro-id/972ba092-9239-4947-9bf6-495c53e57266. output tool biblio input Geographical Scope annotation 13.086770981507822 9.2 Knowledge Sector (EEA) Physical and Technological Demonstrates collaborative annotation using JupyterGIS, model retraining with expert corrections, and FAIR research practices. 30.93093093093093 30.9 Academic/ Institutional Preparing the ground Aerospace Engineering Climate Hazard Mathematical and computer sciences (general) classification 12.091038406827881 8.5 Policy Scale JupyterGIS Wetland Classification Demo IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences Methodology Academia/ Research Institutions User Needs (RAST) machine learning workflow 29.345372460496613 26.0 Geosciences correction 9.174311926605505 6.0 Geosciences (General) Funding collaborative annotation 13.31828442437923 11.8 Key Type Measures Mathematical and computer sciences practice 7.339449541284403 4.8 Wetlands Environment/Natural resources/Water/Wetlands Retraining Labour/Employment/Employment training/Retraining JupyterGIS Wetland Classification Demo - ESA EOPF Human-in-the-loop machine learning workflow for wetland classification using Sentinel-2 data from ESA EOPF. 69.06906906906906 69.0 computer science 100.0 11.7 European Continent Education Education Computer programming and software data 15.443425076452598 10.1 Other Technology Case Study Engineering Sentinel-2 13.371266002844951 9.4 Climate-ADAPT Adaptation Sectors Data Format Land use planning Engineering (General) Teaching and learning Education/Teaching and learning Esa Eopf 15.07823613086771 10.6 Earth resources and remote sensing Distributed Computing none workflow 11.009174311926605 7.2 IPCC Esa Eopf wetland 7.339449541284403 4.8 wetland classification 29.006772009029344 25.7 research 7.798165137614677 5.1 Stakeholders note 13.608562691131498 8.9 Other Engineering Other Information and Computing Sciences No policy or regulation Information Systems Interdisciplinary Engineering Biodiversity: state of habitats and species category 13.30275229357798 8.7 Computer Software Engineering JupyterGIS Wetland Classification Demo 17.780938833570413 12.5 machine learning 14.22475106685633 10.0 Information and Computing Sciences research practice 20.428893905191874 18.1 data from Esa eopf 7.900677200902933 7.0 machine learning 14.984709480122325 9.8 Technology data 14.366998577524894 10.1 Computer systems none Earth observation https://annefou.github.io/jupytergis-showcases/lab/index.html?path=Wetland_Annotation.jGIS 2025-12-21 16:29:01.808092+00:00 2025-12-21 16:29:02.435279+00:00 Interactive map with expert annotations for model corrections text/html JupyterGIS Annotation Document 2025-12-21 16:29:01.808092+00:00 https://github.com/EOPF-Sample-Service/eopf-sample-notebooks 2025-12-21 16:28:57.399750+00:00 2025-12-21 16:28:58.038982+00:00 ESA Earth Observation Processing Framework for Sentinel-1, 2 and 3 data access EOPF Sample Service 2025-12-21 16:28:57.399750+00:00 https://github.com/annefou/jupytergis-showcases 2025-12-21 16:29:33.240998+00:00 2025-12-21 16:29:33.849049+00:00 Source repository for this demo GitHub Repository 2025-12-21 16:29:33.240998+00:00 https://github.com/geojupyter/jupytergis 2025-12-21 16:28:53.494405+00:00 2025-12-21 16:28:54.119033+00:00 Collaborative GIS environment for Jupyter - required to open .jGIS files JupyterGIS 2025-12-21 16:28:53.494405+00:00 Simula Research Laboratory annef@simula.no Anne Fouilloux 0000-0002-1784-2920 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/../requirements.txt 2025-12-21 16:28:55.442396+00:00 2025-12-21 16:28:56.067960+00:00 Conda environment specification with all Python dependencies text/plain Conda Environment 2025-12-21 16:28:55.442396+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/Wetland_ML_Demo_EOPF.ipynb 2025-12-21 16:28:59.461288+00:00 2025-12-21 16:29:00.096604+00:00 Main Jupyter notebook implementing the wetland classification workflow Wetland ML Demo Notebook 2025-12-21 16:28:59.461288+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/Wetland_ML_ROhub.ipynb 2025-12-21 16:41:18.541514+00:00 2025-12-21 16:41:19.390117+00:00 Jupyter notebook to create a RO-Crate in ROHub Wetland_ML_ROhub 2025-12-21 16:41:18.541514+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/wetland_outputs/corrections.geojson 2025-12-21 16:29:08.929182+00:00 2025-12-21 16:29:13.322705+00:00 Expert corrections extracted from JupyterGIS annotations Expert Corrections (GeoJSON) 2025-12-21 16:29:08.929182+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/wetland_outputs/sentinel2_rgb.tif 2025-12-21 16:29:04.078500+00:00 2025-12-21 16:54:53.937124+00:00 Cloud Optimized GeoTIFF - RGB composite from Sentinel-2 L2A image/tiff Sentinel-2 RGB Composite (COG) 2025-12-21 16:29:04.078500+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/wetland_outputs/wetland_model_v2.joblib 2025-12-21 16:29:27.413086+00:00 2025-12-21 16:29:31.950449+00:00 Serialized Random Forest model retrained with expert corrections Trained Model v2 (joblib) 2025-12-21 16:29:27.413086+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/wetland_outputs/wetland_prediction_v1.tif 2025-12-21 16:29:06.069310+00:00 2025-12-21 16:29:06.645893+00:00 Initial Random Forest classification - before expert corrections image/tiff Wetland Prediction v1 2025-12-21 16:29:06.069310+00:00 https://raw.githubusercontent.com/annefou/jupytergis-showcases/refs/heads/main/content/wetland_outputs/wetland_prediction_v2_corrected.tif 2025-12-21 16:29:16.556974+00:00 2025-12-21 16:29:23.003791+00:00 Improved classification after retraining with expert corrections image/tiff Wetland Prediction v2 (Corrected) 2025-12-21 16:29:16.556974+00:00 0 https://api.rohub.org/api/ros/10dc322d-eedd-43ff-a4af-7adb6281cb6e/crate/download/ 2025-12-21 16:28:47.782517+00:00 2026-04-11 03:23:09.225173+00:00 2025-12-21 16:28:47.782517+00:00 Human-in-the-loop machine learning workflow for wetland classification using Sentinel-2 data from ESA EOPF. Demonstrates collaborative annotation using JupyterGIS, model retraining with expert corrections, and FAIR research practices. application/ld+json https://w3id.org/ro-id/10dc322d-eedd-43ff-a4af-7adb6281cb6e JupyterGIS Wetland ML Classification Demo - ESA EOPF MANUAL Fouilloux, Anne. "JupyterGIS Wetland ML Classification Demo - ESA EOPF." ROHub. Dec 21 ,2025. https://w3id.org/ro-id/10dc322d-eedd-43ff-a4af-7adb6281cb6e. biblio tool input output Biodiversity Methodology IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences machine learning workflow 29.345372460496613 26.0 computer science 100.0 11.7 machine learning 14.22475106685633 10.0 Psychology and Cognitive Sciences data 15.443425076452598 10.1 none Computer Software Engineering (General) Other Physical Sciences Other Mathematical Sciences Wetlands Environment/Natural resources/Water/Wetlands Other History and Archaeology Other Commerce, Management, Tourism and Services Other Engineering JupyterGIS Wetland ML Classification Demo - ESA EOPF Human-in-the-loop machine learning workflow for wetland classification using Sentinel-2 data from ESA EOPF. 69.06906906906906 69.0 research 7.798165137614677 5.1 Other Technology JupyterGIS Wetland ML Classification Demo 17.780938833570413 12.5 Engineering Other Language, Literature and Culture Sentinel-2 13.371266002844951 9.4 Medical and Health Sciences Other Philosophy and Religious Studies Distributed Computing Institutional: Government policies and programs European Continent Other Agricultural and Veterinary Sciences Information and Computing Sciences Technology Education Other Studies in Human Society Other Studies in Creative Arts and Writing Other Medical and Health Sciences Agricultural and Veterinary Sciences Studies in Creative Arts and Writing Mathematical Sciences wetland classification 29.006772009029344 25.7 Preparing the ground wetland 7.339449541284403 4.8 Biodiversity: state of habitats and species Other Psychology and Cognitive Sciences collaborative annotation 13.31828442437923 11.8 Commerce, Management, Tourism and Services classification 12.091038406827881 8.5 Physical Sciences History and Archaeology Teaching and learning Education/Teaching and learning Stakeholders Knowledge Sector (EEA) Key Type Measures Law and Legal Studies Mathematical Physics Climate-ADAPT Adaptation Sectors Physical and Technological Geographical Scope Academic/ Institutional Data Format Artifical Intelligence and Image Processing Case Study annotation 13.086770981507822 9.2 Environmental Science and Management machine learning 14.984709480122325 9.8 Earth resources and remote sensing Philosophy and Religious Studies Geosciences (General) Geosciences Computer systems Astronomical and Space Sciences Computation Theory and Mathematics Studies in Human Society Other Information and Computing Sciences Policy Scale Funding Other Education Retraining Labour/Employment/Employment training/Retraining Demonstrates collaborative annotation using JupyterGIS, model retraining with expert corrections, and FAIR research practices. 30.93093093093093 30.9 note 13.608562691131498 8.9 research practice 20.428893905191874 18.1 data from Esa eopf 7.900677200902933 7.0 User Needs (RAST) Mathematical and computer sciences (general) Other Environmental Sciences Environmental Sciences Esa Eopf workflow 11.009174311926605 7.2 Built Environment and Design Other Law and Legal Studies Computer programming and software Engineering Mathematical and computer sciences IPCC practice 7.339449541284403 4.8 Other Built Environment and Design correction 9.174311926605505 6.0 Economics data 14.366998577524894 10.1 Language, Communication and Culture category 13.30275229357798 8.7 Esa Eopf 15.07823613086771 10.6 Climate Hazard Education Education Academia/ Research Institutions No policy or regulation Other Economics Information Systems JupyterGIS Wetland ML Classification Demo Life sciences https://asreview.nl/ 2025-12-27 20:18:46.006779+00:00 2025-12-27 20:18:46.748331+00:00 AI-assisted systematic review screening tool ASReview LAB v2.2 2025-12-27 20:18:46.006779+00:00 https://doi.org/10.1136/bmj.n71 2025-12-29 13:49:18.378333+00:00 2025-12-29 13:49:19.090463+00:00 The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews 2025-12-29 13:49:18.378333+00:00 https://doi.org/10.5281/zenodo.18070377 2025-12-27 20:19:29.530182+00:00 2025-12-29 20:35:05.913407+00:00 Complete dataset including search results, ASReview project, screening decisions, and nanopub URIs. DOI: 10.5281/zenodo.18070378 Systematic Review Dataset - Zenodo 2025-12-27 20:19:29.530182+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline 2025-12-27 20:19:30.824807+00:00 2025-12-27 20:23:11.216634+00:00 Source code repository containing all Jupyter notebooks, configuration templates, and documentation Systematic Review Pipeline - GitHub Repository 2025-12-27 20:19:30.824807+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/inputs/quantum-biodiversity/pico-quantum-biodiversity.json 2025-12-27 20:18:17.913600+00:00 2025-12-28 15:54:46.796468+00:00 JSON configuration for quantum computing + biodiversity PICO question application/json PICO Configuration 2025-12-27 20:18:17.913600+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/inputs/quantum-biodiversity/search-execution-quantum-biodiversity.json 2025-12-27 20:18:33.107854+00:00 2025-12-28 15:56:06.224813+00:00 JSON configuration with API endpoints and result counts application/json Search Execution Configuration 2025-12-27 20:18:33.107854+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/inputs/quantum-biodiversity/search-strategy-quantum-biodiversity.json 2025-12-27 20:18:24.605191+00:00 2025-12-28 15:55:16.275118+00:00 JSON configuration with search terms, databases, and date ranges application/json Search Strategy Configuration 2025-12-27 20:18:24.605191+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/inputs/quantum-biodiversity/study-assessment-quantum-biodiversity.json 2025-12-27 20:18:54.656235+00:00 2025-12-30 09:17:31.394335+00:00 JSON with study characteristics and quality assessment application/json Study Assessment Configuration 2025-12-27 20:18:54.656235+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/notebooks/asreview-to-nanopub.ipynb 2025-12-27 20:18:39.646664+00:00 2025-12-28 15:56:38.085081+00:00 Extracts screening decisions from ASReview project file ASReview Export to Nanopub 2025-12-27 20:18:39.646664+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/notebooks/database-search-nanopubs.ipynb 2025-12-29 19:42:12.362288+00:00 2025-12-29 19:42:13.080219+00:00 Create of a nanopublication for storing the results of a bibliography search. A nanopublication is created for each database search. PRISMA Database Search Nanopublications 2025-12-29 19:42:12.362288+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/notebooks/pico-nanopub-from-json.ipynb 2025-12-27 20:18:15.715938+00:00 2025-12-28 15:54:20.949348+00:00 Generates PICO research question nanopublication from JSON config PICO Nanopub Generator 2025-12-27 20:18:15.715938+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/notebooks/search-execution-api-queries.ipynb 2025-12-27 20:18:28.872086+00:00 2025-12-28 15:55:33.585290+00:00 Queries OpenAlex, arXiv, PubMed, Europe PMC, Semantic Scholar APIs Search Execution - API Queries 2025-12-27 20:18:28.872086+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/notebooks/search-execution-nanopub-from-json.ipynb 2025-12-27 20:18:30.964263+00:00 2025-12-28 15:55:54.942706+00:00 Generates search execution dataset nanopublication Search Execution Nanopub Generator 2025-12-27 20:18:30.964263+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/notebooks/search-strategy-nanopub-from-json.ipynb 2025-12-27 20:18:22.497310+00:00 2025-12-28 15:55:06.338250+00:00 Generates search strategy nanopublication with Boolean queries Search Strategy Nanopub Generator 2025-12-27 20:18:22.497310+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/notebooks/study-assessment-nanopub-from-json.ipynb 2025-12-27 20:18:52.499249+00:00 2025-12-30 09:17:07.137288+00:00 Generates study assessment dataset nanopublication Study Assessment Nanopub Generator 2025-12-27 20:18:52.499249+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/notebooks/study-inclusion-nanopub-asreview.ipynb 2025-12-27 20:18:48.208829+00:00 2025-12-28 15:57:18.333484+00:00 Generates individual nanopubs for each included/excluded study Study Inclusion Nanopub Generator 2025-12-27 20:18:48.208829+00:00 https://github.com/FAIR2Adapt/systematic-review-pipeline/blob/main/requirements.txt 2025-12-27 20:19:32.004249+00:00 2025-12-27 20:23:28.849828+00:00 Python package dependencies: pandas, numpy, requests, rdflib, nanopub, asreview, jupyter text/plain requirements.txt 2025-12-27 20:19:32.004249+00:00 Simula Research Laboratory annef@simula.no Anne Fouilloux 0000-0002-1784-2920 https://raw.githubusercontent.com/FAIR2Adapt/systematic-review-pipeline/refs/heads/main/Quantum-and-Biodiversity-Perplexity.png 2025-12-29 15:46:22.541340+00:00 2025-12-29 15:57:44.661899+00:00 Illustration of Quantum Computingfor Biodiversity. This illustration was generated by Perplexity.ai on 29th December 2025. image/png ai-generated Quantum Computing applied to Biodiversity 2025-12-29 15:46:22.541340+00:00 04c04g438 LifeWatch ERIC https://w3id.org/np/RAJW9kn9Syx7y_1Okl4HPwqUlUssxi0daadJNM1AT8-PU 2025-12-27 20:18:26.730521+00:00 2025-12-27 20:18:27.450626+00:00 Published nanopub documenting the search strategy Search Strategy Nanopublication 2025-12-27 20:18:26.730521+00:00 https://w3id.org/np/RASr_5SP0NhXfz43auGCrxon4_kUUj0AfA56gW13Yfqak 2025-12-27 20:18:20.280170+00:00 2025-12-29 15:49:50.022727+00:00 Published nanopub defining the research question PICO Nanopublication 2025-12-27 20:18:20.280170+00:00 https://w3id.org/np/RAhFlAUVte1zioZDIBXyg6GdSziwLxgqwxPkDi7v110WU 2025-12-27 20:18:35.263368+00:00 2025-12-29 19:14:15.467721+00:00 Published nanopub with search execution metadata Search Execution Nanopublication 2025-12-27 20:18:35.263368+00:00 https://w3id.org/np/RAlN5rGFTlXawYWAMdSDMm2SfTh8mfsN9Jhx-Oh7yXR-4 2025-12-27 20:18:56.771035+00:00 2025-12-30 09:25:09.003318+00:00 Published nanopub with aggregated study characteristics Study Assessment Nanopublication 2025-12-27 20:18:56.771035+00:00 0 https://api.rohub.org/api/ros/b6e01d7a-9f25-4b37-82df-32ef2e7171e3/crate/download/ 2025-12-27 20:03:25.858398+00:00 2026-01-26 10:09:47.582777+00:00 2025-12-27 20:03:25.858398+00:00 A PRISMA-compliant scoping review investigating applications of quantum computing in biodiversity and ecological research. This Research Object contains the complete reproducible workflow from research question to study assessment, implemented as a pipeline of Jupyter notebooks with nanopublication outputs for transparent, machine-readable documentation. Screening: 1,649 records → 569 screened → 283 included → 238 nanopubs published. application/ld+json https://w3id.org/ro-id/b6e01d7a-9f25-4b37-82df-32ef2e7171e3 ASReview PRISMA active learning biodiversity nanopublications quantum computing reproducible research scoping review systematic review Research Question Quantum Computing Applications in Biodiversity Research - Scoping Review MANUAL Fouilloux, Anne. "Quantum Computing Applications in Biodiversity Research - Scoping Review." ROHub. Dec 27 ,2025. https://w3id.org/ro-id/b6e01d7a-9f25-4b37-82df-32ef2e7171e3. API queries and search result aggregation 3-search-execution biblio Search strategy with Boolean operators and database selection 2-search-strategy AI-assisted screening with ASReview LAB 4-screening Study characteristics and quality assessment 5b-study-assessment Included/excluded study nanopublications 5a-study-inclusion PICO framework research question definition 1-pico-research-question https://zenodo.org/records/18070378/files/included_studies.csv 2025-12-27 20:18:37.421635+00:00 2025-12-27 20:18:38.184563+00:00 Aggregated search results from all databases text/csv Search Results CSV 2025-12-27 20:18:37.421635+00:00 https://zenodo.org/records/18070378/files/search_results_combined.asreview 2025-12-27 20:18:41.777731+00:00 2025-12-27 20:18:42.474928+00:00 ASReview LAB project with screening decisions ASReview Project File 2025-12-27 20:18:41.777731+00:00 https://zenodo.org/records/18070378/files/study_inclusion.json 2025-12-27 20:18:43.877924+00:00 2025-12-27 20:18:44.598993+00:00 Extracted inclusion/exclusion decisions with reasons application/json Screening Decisions JSON 2025-12-27 20:18:43.877924+00:00 https://zenodo.org/records/18070686/files/published_uris_updated.json 2025-12-27 20:18:50.315296+00:00 2025-12-29 20:38:18.771481+00:00 Index of all published study inclusion nanopublications application/json Published Nanopub URIs (238 studies) 2025-12-27 20:18:50.315296+00:00 Earth sciences https://doi.org/10.5281/zenodo.15313672 2025-12-31 10:57:48.638315+00:00 2025-12-31 10:57:49.356851+00:00 This is the version of the corpus used in the paper. Corpus 2025-12-31 10:57:48.638315+00:00 https://github.com/ArvinRastegar/i-adopt-llm-based-service 2025-12-31 10:59:01.841725+00:00 2025-12-31 10:59:02.523867+00:00 This repository contains the source code used to run the experiments and the results obtained. Source code repository for evaluation 2025-12-31 10:59:01.841725+00:00 https://github.com/i-adopt/Corpus/ 2025-12-31 10:54:57.270901+00:00 2025-12-31 10:56:56.694242+00:00 In this repository you can find the TTL files of the corpus. Corpus repository 2025-12-31 10:54:57.270901+00:00 0 https://api.rohub.org/api/ros/52654482-5442-45ea-a4b7-80a9af510c0b/crate/download/ 2025-12-31 10:52:28.470807+00:00 2026-04-11 03:01:43.580973+00:00 2025-12-31 10:52:28.470807+00:00 This Research Objects contains the supplementary material of the paper "From Scientific Variables to Knowledge Graphs: The I-ADOPT Benchmark" sent to the Semantic Web Journal. This paper presents the I-ADOPT benchmark, an expert annotated corpus and task designed to measure the performance of LLMs in the different stages of automatically creating a machine readable scientific variable. Our corpus includes more than 100 scientific variables as structured knowledge graphs You can find in the Research Object the corpus, as well as the source code needed to execute the experiments, and the results of them. application/ld+json https://w3id.org/ro-id/52654482-5442-45ea-a4b7-80a9af510c0b I-ADOPT LLM corpus scientific variables From Scientific Variables to Knowledge Graphs: The I-ADOPT Benchmark MANUAL GONZALEZ GUARDIA, ESTEBAN. "From Scientific Variables to Knowledge Graphs: The I-ADOPT Benchmark." ROHub. Dec 31 ,2025. https://w3id.org/ro-id/52654482-5442-45ea-a4b7-80a9af510c0b. Key Type Measures No policy or regulation Distributed Computing research 8.630952380952381 5.8 Computer systems Climate Hazard benchmark 10.21897810218978 8.4 Engineering (General) Climate-ADAPT Adaptation Sectors graph 17.857142857142858 12.0 Methodology Numerical analysis Academic/ Institutional source code 6.32603406326034 5.2 none Systemic Literature Review Information and Computing Sciences Preparing the ground research object 15.282791817087844 12.7 Knowledge Sector (EEA) European Continent I-ADOPT corpus 8.090024330900244 6.65 newspaper publisher 4.5012165450121655 3.7 variable 17.410714285714285 11.7 I-ADOPT 22.023809523809522 14.8 This paper presents the I-ADOPT benchmark, an expert annotated corpus and task designed to measure the performance of LLMs in the different stages of automatically creating a machine readable scientific variable. 41.458106637649614 38.1 Data Format knowledge 8.333333333333332 5.6 Information Systems Engineering Theoretical mathematics expert annotated corpus 7.099879663056558 5.9 corpus 12.797619047619047 8.6 variable 14.233576642335766 11.7 Social and information sciences none Academia/ Research Institutions research 6.934306569343065 5.7 material of the paper 6.257521058965102 5.2 Documentation and information science Other Mathematical Sciences task 5.231143552311435 4.3 Computer Software aim 5.839416058394161 4.8 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences linguistics 100.0 8.8 Mathematical Sciences none Our corpus includes more than 100 scientific variables as structured knowledge graphs 15.88683351468988 14.6 Geographical Scope I-ADOPT benchmark 44.4043321299639 36.9 knowledge 7.177615571776156 5.9 Computer programming and software Funding Statistics and probability Stakeholders User Needs (RAST) Science and technology Science and technology Physical and Technological none material 4.257907542579075 3.5 Policy Scale knowledge graph 26.955475330926593 22.4 Mathematical and computer sciences (general) benchmark 12.94642857142857 8.7 Mathematical and computer sciences experiment 4.622871046228711 3.8 IPCC From Scientific Variables to Knowledge Graphs: The I-ADOPT Benchmark This Research Objects contains the supplementary material of the paper "From Scientific Variables to Knowledge Graphs: The I-ADOPT Benchmark" sent to the Semantic Web Journal. 42.6550598476605 39.2 graph 14.476885644768856 11.9 Systems analysis and operations research Computation Theory and Mathematics esteban.gonzalez@upm.es ESTEBAN GONZALEZ GUARDIA Historical geography 1cb12e51-a719-48ce-aef8-c82dd4eb52c5 POINT (20.997070278972387 52.23520112180287) 20.997070278972387 52.23520112180287 POINT (20.997070278972387 52.23520112180287) 0 https://api.rohub.org/api/ros/e9de4f85-969b-411f-993b-bbb9178b37a9/crate/download/ 2026-01-15 00:33:56.004323+00:00 2026-04-11 02:35:46.162204+00:00 2026-01-15 00:33:56.004323+00:00 Kino radzieckie lat dwudziestych XX wieku stanowi jeden z najbardziej wyrazistych przykładów instrumentalizacji filmu jako narzędzia ideologicznego. W młodym państwie bolszewickim kinematografia nie była wyłącznie dziedziną sztuki, lecz elementem projektu politycznego – środkiem edukacji mas, narzędziem legitymizacji władzy oraz budowania nowej, rewolucyjnej mitologii. Jednym z najbardziej znanych i wpływowych filmów tego okresu jest Pancernik Potiomkin (1925) w reżyserii Siergieja Michajłowicza Eisensteina. application/ld+json https://w3id.org/ro-id/e9de4f85-969b-411f-993b-bbb9178b37a9 Document Esej "Historia i władza w „Pancerniku Potiomkinie” Siergieja Eisensteina" MANUAL W, Monika. "Esej "Historia i władza w „Pancerniku Potiomkinie” Siergieja Eisensteina"." ROHub. Jan 15 ,2026. https://w3id.org/ro-id/e9de4f85-969b-411f-993b-bbb9178b37a9. POINT (20.997070278972387 52.23520112180287) Physics Structural/physical: Ecosystem-based Individuals or citizens Physical Sciences Astronautics User Needs (RAST) Astronautics (General) none Mathematical Sciences Policy Scale Space sciences (General) Quantum Physics Key Type Measures Portugal Astronomy Geographical Scope Physics (General) Systemic Literature Review Physical and Technological Mathematical Physics IPCC Climate Hazard Local policy Knowledge Sector (EEA) Theoretical and Computational Chemistry Stakeholders Chemical Sciences Identification of risks Funding Space sciences none Other Physical Sciences Climate-ADAPT Adaptation Sectors Aerospace medicine Life sciences Climate change mitigation: reducing emissions Not reported/ Unknown Methodology Monika Wójcikiewicz Meteorology Applied sciences Ecology https://aqicn.org/map/warsaw/pl/ 2026-01-15 09:56:50.534689+00:00 2026-01-15 10:04:04.245960+00:00 Zanieczyszczenie powietrza w Warszawa Mapa wizualna jakości powietrza w czasie rzeczywistym. Zanieczyszczenie powietrza w Warszawa Mapa wizualna jakości powietrza w czasie rzeczywistym. 2026-01-15 09:56:50.534689+00:00 https://iot.warszawa.pl/ 2026-01-15 10:02:54.788955+00:00 2026-01-15 10:03:23.971993+00:00 Indeks Jakości Powietrza Sprawdź poziom jakości powietrza w swojej okolicy. Wskaż na mapie stację pomiarową, przejrzyj aktualne informacje o poziomie stężenia zanieczyszczeń i zapoznaj się z zaleceniami dotyczącymi ochrony Twojego zdrowia. Warszawska Platforma IoT 2026-01-15 10:02:54.788955+00:00 21.007713326253 52.234864715699715 POINT (21.007713326253 52.234864715699715) 912ad5e5-ed9f-46f5-b4d8-491bd4113270 POINT (21.007713326253 52.234864715699715) 0 https://api.rohub.org/api/ros/d006ed2d-2fa9-438d-b830-a7d4aef81469/crate/download/ 2026-01-15 09:36:30.138049+00:00 2026-04-11 03:22:17.313678+00:00 2026-01-15 09:36:30.138049+00:00 Projekt analizuje jakość powietrza w Warszawie, koncentrując się na wartości stężeń pyłów zawieszonych PM2.5 i PM10 oraz ich wpływie na zdrowie ludzi. W ramach projektu gromadzone są raporty i dane pomiarowe z lokalnych narzędzi monitoringu, a następnie są one porównywane z normami Światowej Organizacji Zdrowia (WHO). Badanie uwzględnia różne dni, pory dnia i miejsca pomiarów na terenie całego miasta Warszawy oraz identyfikuje możliwe przyczyny i skutki przekroczenia dopuszczalnych poziomów zanieczyszczeń. application/ld+json https://w3id.org/ro-id/d006ed2d-2fa9-438d-b830-a7d4aef81469 Air Quality Environment Monitoring PM10 PM2.5 Warsaw Dataset Jakość powietrza w Warszawie — analiza stężeń PM2.5 i PM10 oraz ich przekroczeń MANUAL Janek Gębicki Gębicki, Janek, and Janek Gębicki. "Jakość powietrza w Warszawie — analiza stężeń PM2.5 i PM10 oraz ich przekroczeń." ROHub. Jan 15 ,2026. https://w3id.org/ro-id/d006ed2d-2fa9-438d-b830-a7d4aef81469. POINT (21.007713326253 52.234864715699715) biblio data raw data metadata 6205 https://api.rohub.org/api/resources/25295fee-4813-4aaf-ac4b-fb60c693f3a6/download/ 2026-01-15 10:08:30.311996+00:00 2026-01-15 10:08:32.429209+00:00 Dane symulowane, wygenerowane na potrzeby projektu edukacyjnego. Nie przedstawiają rzeczywistych pomiarów, ale odzwierciedlają realistyczne trendy sezonowe i dobowe jakości powietrza w Warszawie. application/vnd.openxmlformats-officedocument.spreadsheetml.sheet Jakość powietrza Warszawa - dane 2026-01-15 10:08:30.311996+00:00 364153 https://api.rohub.org/api/resources/28481e37-3b7d-463e-aa51-da710e432904/download/ 2026-01-15 09:50:01.944724+00:00 2026-01-15 09:50:04.071778+00:00 Ocena jakości powietrza jest bardzo złożonym zagadnieniem, na które wpływa bardzo wiele czynników natury środowiskowej jak i antropogenicznej. Aby określić czy, a jeśli tak to, w jaki sposób pandemia przełożyła się na jakość powietrza w Warszawie, należy wyodrębnić główne czynniki, które przyczyniają się do zmian poziomu zanieczyszczenia powietrza. application/pdf Air Quality PM2.5 Jakość powietrza - raport COVIDOVY 2026-01-15 09:50:01.944724+00:00 36906127 https://api.rohub.org/api/resources/98fe4e3c-4b90-4e25-9752-c314a6cb3938/download/ 2026-01-15 09:51:41.659860+00:00 2026-01-15 09:51:44.977381+00:00 Celem niniejszego raportu jest prezentacja danych z pomiarów stężenia pyłu zawieszonego PM2,5 zebranych w ramach projektu Poszukiwacze Powietrza, zainicjowanego przez Warszawski Alarm Smogowy przy udziale Partnerów w 2019 r. Jego celem jest upowszechnianie wiedzy o skali i źródłach zanieczyszczenia powietrza w Warszawie dzięki rozbudowie sieci obywatelskich czujników smogu Sensor Community (S.C.). Czujniki dokonują pomiarów stężenia pyłu zawieszonego odpowiednio o średnicy nie większej niż 10 i 2,5 mm. Zebrane dane są publicznie dostępne, pozwalając na lepsze zrozumienie problemu zanieczyszczenia powietrza. application/pdf Air Quality PM10 PM2.5 ANALIZA ZANIECZYSZCZENIA POWIETRZA PYŁEM ZAWIESZONYM PM2,5 W WARSZAWIE Z WYKORZYSTANIEM SIECI OBYWATELSKICH CZUJNIKÓW SMOGU 2026-01-15 09:51:41.659860+00:00 43507 https://api.rohub.org/api/resources/e3dd7d26-f36f-4a82-b4f0-f8d1f081502c/download/ 2026-01-15 09:45:53.134501+00:00 2026-01-15 10:04:13.680897+00:00 image/jpeg zanieczyszczenie.jpg 2026-01-15 09:45:53.134501+00:00 Key Type Measures Aerospace medicine Space sciences (General) Geographical Scope Identification of risks Climate Hazard Not reported/ Unknown Astronomy none Physical Sciences Methodology Funding Life sciences Physical and Technological Theoretical and Computational Chemistry Astronautics User Needs (RAST) Stakeholders Physics Mathematical Sciences Systemic Literature Review Portugal Quantum Physics Astronautics (General) Physics (General) none IPCC Local policy Mathematical Physics Policy Scale Structural/physical: Ecosystem-based Knowledge Sector (EEA) Climate-ADAPT Adaptation Sectors Individuals or citizens Chemical Sciences Space sciences Other Physical Sciences Climate change mitigation: reducing emissions j.gebicki@student.uw.edu.pl Janek Gębicki Applied sciences Social sciences uw@edu.pl 111111111 Uniwersytet Warszawski 21.019707014456873 52.24116383984816 POINT (21.019707014456873 52.24116383984816) 7fd3288a-63dc-4653-8eef-09f09ec4607e POINT (21.019707014456873 52.24116383984816) 0 https://api.rohub.org/api/ros/49a44dd4-efc3-45a0-8dd3-790081990133/crate/download/ 2026-01-15 12:53:40.702912+00:00 2026-04-11 09:59:15.083441+00:00 2026-01-15 12:53:40.702912+00:00 Badanie analizuje, w jaki sposób wykorzystanie cyfrowych narzędzi do zarządzania informacją (takich jak repozytoria danych, systemy notatek i platformy współpracy online) wpływa na efektywność pracy zespołów badawczych w środowisku akademickim. W ramach projektu przeprowadzono analizę porównawczą zespołów korzystających z różnych modeli organizacji wiedzy, z uwzględnieniem takich czynników jak czas realizacji projektów, jakość dokumentacji oraz subiektywna ocena obciążenia poznawczego badaczy. Celem badania jest identyfikacja dobrych praktyk wspierających procesy badawcze w warunkach rosnącej ilości informacji. application/ld+json https://w3id.org/ro-id/49a44dd4-efc3-45a0-8dd3-790081990133 narzędzia cyfrowe organizacja informacji zarządzanie wiedzą Hypothesis Wpływ cyfrowych narzędzi organizacji wiedzy na efektywność pracy badawczej zespołów akademickich MANUAL student I, J, and Agata Połatyńska. "Wpływ cyfrowych narzędzi organizacji wiedzy na efektywność pracy badawczej zespołów akademickich." ROHub. Jan 15 ,2026. https://w3id.org/ro-id/49a44dd4-efc3-45a0-8dd3-790081990133. POINT (21.019707014456873 52.24116383984816) ddd 1099582 https://api.rohub.org/api/resources/2c338402-4d50-4ef4-921c-2a1d9303391a/download/ 2026-01-15 13:17:11.072437+00:00 2026-01-15 13:17:11.919072+00:00 image/png sustainability-17-07823-g001.png 2026-01-15 13:17:11.072437+00:00 33001 https://api.rohub.org/api/resources/41f43e61-4c4d-4427-85be-fbd3df9fc3b9/download/ 2026-02-14 01:07:36.917025+00:00 2026-02-14 01:07:38.055018+00:00 image/png Crystal_Project_Atlantik.png 2026-02-14 01:07:36.917025+00:00 153 https://api.rohub.org/api/resources/beaad2c4-c479-485d-b123-cf6fc5146bfe/download/ 2026-01-15 13:22:56.497659+00:00 2026-01-15 13:22:58.753316+00:00 lorem ipsum text/plain Opis badania 2026-01-15 13:22:56.497659+00:00 IPCC Astronautics User Needs (RAST) Key Type Measures Policy Scale Systemic Literature Review Aerospace medicine Astronautics (General) Physical and Technological Climate change mitigation: reducing emissions Climate Hazard Physics (General) none Not reported/ Unknown Individuals or citizens Physics Quantum Physics Physical Sciences Stakeholders Structural/physical: Ecosystem-based Chemical Sciences Local policy Life sciences Space sciences Portugal Space sciences (General) Mathematical Sciences Theoretical and Computational Chemistry Other Physical Sciences Knowledge Sector (EEA) Mathematical Physics none Geographical Scope Climate-ADAPT Adaptation Sectors Funding Astronomy Methodology Identification of risks a.polatynsk2@student.uw.edu.pl Agata Połatyńska j.iwicka@student.uw.edu.pl Joanna Iwicka Applied sciences Social sciences POINT (21.019707014456873 52.24116383984816) uw@edu.pl 111111111 Uniwersytet Warszawski 815d63ec-d9fd-4c80-b574-062ad537e465 POINT (21.019707014456873 52.24116383984816) POINT (21.019707014456873 52.24116383984816) 21.019707014456873 52.24116383984816 POINT (21.019707014456873 52.24116383984816) e859e521-c01f-445d-a496-eea7e9c352f1 POINT (21.019707014456873 52.24116383984816) 1126898 https://api.rohub.org/api/ros/7c0fe5d9-6901-411b-b377-c8516f42058e/crate/download/ 2026-01-15 12:53:40.702912+00:00 2026-04-11 09:59:25.033637+00:00 2026-01-15 12:53:40.702912+00:00 Badanie analizuje, w jaki sposób wykorzystanie cyfrowych narzędzi do zarządzania informacją (takich jak repozytoria danych, systemy notatek i platformy współpracy online) wpływa na efektywność pracy zespołów badawczych w środowisku akademickim. W ramach projektu przeprowadzono analizę porównawczą zespołów korzystających z różnych modeli organizacji wiedzy, z uwzględnieniem takich czynników jak czas realizacji projektów, jakość dokumentacji oraz subiektywna ocena obciążenia poznawczego badaczy. Celem badania jest identyfikacja dobrych praktyk wspierających procesy badawcze w warunkach rosnącej ilości informacji. application/ld+json https://w3id.org/ro-id/7c0fe5d9-6901-411b-b377-c8516f42058e narzędzia cyfrowe organizacja informacji Hypothesis Wpływ cyfrowych narzędzi organizacji wiedzy na efektywność pracy badawczej zespołów akademickich MANUAL student I, J, and Agata Połatyńska. "Wpływ cyfrowych narzędzi organizacji wiedzy na efektywność pracy badawczej zespołów akademickich." ROHub. Jan 15 ,2026. https://w3id.org/ro-id/7c0fe5d9-6901-411b-b377-c8516f42058e. ddd 153 https://api.rohub.org/api/resources/177216b1-4df6-44bb-a4d1-8cacf0801105/download/ 2026-01-15 13:22:56.497659+00:00 2026-02-14 01:40:32.554610+00:00 lorem ipsum text/plain Opis badania 2026-01-15 13:22:56.497659+00:00 33001 https://api.rohub.org/api/resources/766f82ce-c5b9-4e20-b582-c431d0c7841e/download/ 2026-02-14 01:07:36.917025+00:00 2026-02-14 01:40:33.033725+00:00 image/png Crystal_Project_Atlantik.png 2026-02-14 01:07:36.917025+00:00 1099582 https://api.rohub.org/api/resources/abd4263f-566e-4982-bd99-1ac487f2033c/download/ 2026-01-15 13:17:11.072437+00:00 2026-02-14 01:40:32.180624+00:00 image/png sustainability-17-07823-g001.png 2026-01-15 13:17:11.072437+00:00 Systemic Literature Review Aerospace medicine Other Physical Sciences Funding Not reported/ Unknown Space sciences Portugal IPCC Physics Key Type Measures Mathematical Physics Individuals or citizens Policy Scale Astronautics Climate-ADAPT Adaptation Sectors Local policy Structural/physical: Ecosystem-based Stakeholders Physical and Technological User Needs (RAST) Astronomy Climate change mitigation: reducing emissions Physical Sciences Geographical Scope Climate Hazard none Life sciences Chemical Sciences Methodology Knowledge Sector (EEA) Space sciences (General) Astronautics (General) Identification of risks Mathematical Sciences Physics (General) Quantum Physics none Theoretical and Computational Chemistry a.polatynsk2@student.uw.edu.pl Agata Połatyńska j.iwicka@student.uw.edu.pl J I Joanna Iwicka Environmental research Góral Dariusz Dariusz Góral RepOD datacite Uniwersytet Przyrodniczy w Lublinie https://doi.org/10.18150/KKG1CN 2026-05-06 10:55:50.653097+00:00 2026-05-06 10:55:52.631543+00:00 The samples were examined using a transmission electron microscope (Zeiss LIBRA, Oberkochen, Germany). The examinations were conducted on Formvar-coated grids at an accelerating voltage of 80 kV and a magnification of 50,000×. Obrazy z transmisyjnego mikroskopu elektronowego (TEM) nanocząstek NiFe₂O₄ otrzymywanych metodą zielonej syntezy 2026-05-06 10:55:50.653097+00:00 Góral Dariusz Dariusz Góral Uniwersytet Przyrodniczy w Lublinie 0 https://api.rohub.org/api/ros/ea792c69-9037-4d06-84a8-6fded7356e12/crate/download/ 2026-02-25 14:28:09.653062+00:00 2026-05-06 14:13:26.439990+00:00 2026-02-25 14:28:09.653062+00:00 This Research Object aggregates the research resources related to sea surface observations application/ld+json https://w3id.org/ro-id/ea792c69-9037-4d06-84a8-6fded7356e12 Arctic Radioisotopes - Sea surface observations MANUAL Palma, Raul. "Arctic Radioisotopes - Sea surface observations." ROHub. Feb 25 ,2026. https://w3id.org/ro-id/ea792c69-9037-4d06-84a8-6fded7356e12. 1 degree 2010/2018 JRAOC20TRNRPv2 812165 https://api.rohub.org/api/resources/56dfa02d-4a58-4a78-8e8f-77e7c7e2cabd/download/ 2026-03-19 10:13:57.954583+00:00 2026-03-19 10:13:59.868037+00:00 application/pdf wiad-1183742-Zaproszenie_na_spektakl_muzyczny_o_Janie_Nowaku-Jezioranskim.pdf 2026-03-19 10:13:57.954583+00:00 Earth Sea surface salinity (SSS) Sea surface temperature (SST) Arctic radioisotope 10.030090270812437 10.0 Methodology Marine and fisheries Funding Arctic Radioisotopes - Sea surface observations This Research Object aggregates the research resources related to sea surface observations 100.0 100.0 Research Object surface 20.585267406659938 20.4 research resource 21.865596790371114 21.8 Stakeholders Oceanography radioisotope 12.108980827447024 12.0 Key Type Measures resource 12.083847102342787 9.8 Academia/ Research Institutions Earth Sciences aggregate the research 4.513540621865596 4.5 Geographical Scope radioisotope 14.180024660912451 11.5 Seas and coasts surface 25.893958076448826 21.0 surface observation 4.212637913741224 4.2 none Atomic, Molecular, Nuclear, Particle and Plasma Physics none Data on climate Knowledge Sector (EEA) IPCC Climate-ADAPT Adaptation Sectors Climate Hazard sea surface observation 59.37813440320963 59.2 Nuclear accident and incident Disaster, accident and emergency incident/Accident and emergency incident/Explosion accident and incident/Industrial accident and incident/Nuclear accident and incident sea 18.163471241170537 18.0 Geosciences (General) none Physical and Technological research 18.002466091245374 14.6 Geosciences Research Object 19.87891019172553 19.7 observation 4.540867810292634 4.5 observation 7.274969173859432 5.9 Oceanography research 14.732593340060546 14.6 none sea 22.56473489519112 18.3 resource 9.989909182643794 9.9 none Policy Scale Physical Sciences Other Earth Sciences User Needs (RAST) none Raul Palma Environmental research 0 https://api.rohub.org/api/ros/82e51b26-cc4e-4271-9bb0-5881ae8d7c73/crate/download/ 2026-03-18 11:28:47.536714+00:00 2026-04-11 01:30:21.150444+00:00 2026-03-18 11:28:47.536714+00:00 Climatic database about Portugal, Madeira and Azores. application/ld+json https://w3id.org/ro-id/82e51b26-cc4e-4271-9bb0-5881ae8d7c73 Climatic database about Portugal MANUAL Pantazi, Despina. "Climatic database about Portugal." ROHub. Mar 18 ,2026. https://w3id.org/ro-id/82e51b26-cc4e-4271-9bb0-5881ae8d7c73. http://rna2100.portaldoclima.pt/pt/ RCP2.6, RCP4.5, RCP8.5 Azores Madeira Minimum air temperature Maximum air temperature Mean air temperature Number of heatwave days Number of tropical nights Thermic amplitudes Geosciences Madeira Policy Scale database 30.27806385169928 29.4 Knowledge Sector (EEA) Stakeholders Weather Weather Earth Sciences Climate-ADAPT Adaptation Sectors none Funding Climate change impacts, risks and adaptation Portugal 31.513903192584966 30.6 Azores User Needs (RAST) Physical and Technological Methodology Azores 19.567456230690013 19.0 Meteorology Science and technology/Natural science/Meteorology Geosciences (General) IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences climatic database about Portugal 0.9009009009009008 0.9 Portugal Systemic Literature Review Madeira 18.12564366632338 17.6 Data on climate Geographical Scope Climatology National policy Azores 19.979402677651905 19.4 database about Portugal 35.93593593593594 35.9 Madeira 18.022657054582904 17.5 Oceanography IPCC database 30.48403707518023 29.6 Portugal Other Earth Sciences Climatic database about Portugal Climatic database about Portugal, Madeira and Azores. 100.0 100.0 Key Type Measures Meteorology and climatology Structural/physical: Ecosystem-based Government/ Public Sector Climate Hazard climatic database 63.16316316316316 63.1 Portugal 32.02883625128734 31.1 EU Despina Pantazi Earth sciences Climatology https://doi.org/10.5281/zenodo.19112545 2026-03-20 13:30:17.698601+00:00 2026-03-20 13:30:20.023982+00:00 Floodlevels in increments of 10 cm ranging from 30 cm to 100cm. Hamburg Floodlevels 2026-03-20 13:30:17.698601+00:00 0 https://api.rohub.org/api/ros/24165a93-ac0d-46ef-98a7-046e6d5a287e/crate/download/ 2026-03-20 13:26:33.130248+00:00 2026-03-27 10:38:55.226794+00:00 2026-03-20 13:26:33.130248+00:00 Floodlevels in increments of 10 cm ranging from 30 cm to 100cm. application/ld+json https://w3id.org/ro-id/24165a93-ac0d-46ef-98a7-046e6d5a287e Hamburg flood levels pluvial flood risk Hamburg Floodlevels MANUAL GONZALEZ GUARDIA, ESTEBAN. "Hamburg Floodlevels." ROHub. Mar 20 ,2026. https://w3id.org/ro-id/24165a93-ac0d-46ef-98a7-046e6d5a287e. biblio data metadata raw data Flooding increase 100.0 85.1 Key Type Measures Data on climate-relate hazards Local policy Physics Water management Government/ Public Sector IPCC Extreme weather: floods, droughts, heatwaves Stakeholders increment 87.18718718718719 87.1 Fluid mechanics and thermodynamics Knowledge Sector (EEA) Structural/physical: Engineered and built environments Climate Hazard Climate-ADAPT Adaptation Sectors Engineering National government agencies User Needs (RAST) European Continent Geographical Scope Methodology Mathematical Physics Mathematical Sciences Physical and Technological Scenario Analysis Policy Scale Hamburg Floodlevels Floodlevels in increments of 10 cm ranging from 30 cm to 100cm. 100.0 100.0 Hamburg Floodlevels Floodlevels in increment 100.0 100.0 Funding Physics (General) Other Mathematical Sciences Hamburg Floodlevels Floodlevels 12.812812812812814 12.8 ESTEBAN GONZALEZ GUARDIA Environmental research 0 https://api.rohub.org/api/ros/ed5942f9-4d46-441b-96c1-46f50db5ff29/crate/download/ 2026-03-20 16:10:37.682205+00:00 2026-03-20 17:44:58.341204+00:00 2026-03-20 16:10:37.682205+00:00 Climatic database about Portugal, Madeira and Azores. application/ld+json https://w3id.org/ro-id/ed5942f9-4d46-441b-96c1-46f50db5ff29 Test CS4 MANUAL Gonzalez, Esteban. "Test CS4." ROHub. Mar 20 ,2026. https://w3id.org/ro-id/ed5942f9-4d46-441b-96c1-46f50db5ff29. http://rna2100.portaldoclima.pt/pt/ test 12.06030150753769 9.6 Funding Climate Hazard Policy Scale Climate-ADAPT Adaptation Sectors CS4 20.5050505050505 20.3 Other Earth Sciences Portugal 23.366834170854275 18.6 Portugal Azores 18.58585858585858 18.4 Government/ Public Sector Madeira 22.864321608040203 18.2 Earth Sciences Structural/physical: Ecosystem-based User Needs (RAST) Geosciences (General) Data on climate test CS4 9.40940940940941 9.4 database 18.592964824120603 14.8 Stakeholders Meteorology Science and technology/Natural science/Meteorology Oceanography Wildfires test 8.989898989898988 8.9 Meteorology and climatology National policy IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences climatic database 90.59059059059058 90.5 Madeira Geosciences Portugal database 15.353535353535351 15.2 Other Environmental Sciences Test CS4 Climatic database about Portugal, Madeira and Azores. 100.0 100.0 Weather Weather Methodology Systemic Literature Review Key Type Measures Portugal 18.58585858585858 18.4 Physical and Technological Madeira 17.979797979797976 17.8 IPCC Environmental Sciences EU Azores Climate change impacts, risks and adaptation Climatology Azores 23.115577889447234 18.4 Knowledge Sector (EEA) Geographical Scope Esteban Gonzalez Environmental research 0 https://api.rohub.org/api/ros/4fdb4e5d-e51d-4f22-936f-1db447c87ddc/crate/download/ 2026-03-20 17:41:42.485581+00:00 2026-03-20 17:44:52.858872+00:00 2026-03-20 17:41:42.485581+00:00 This deliverable summarises FAIR2Adapt activities and governance during its first reporting period (M1–M12, 2025), reviewing progress across all seven work packages and defining priorities for Year 2. Year 1 built a strong foundation for FAIR implementation across six case studies through targeted capacity building, transforming initial uncertainty into readiness. While FAIR understanding is now in place, communities do not yet clearly see the practical value of FAIR Digital Objects, as technical developments progressed in parallel with onboarding. Year 2 will therefore focus on FAIR in practice, demonstrating concrete benefits through co-design, demonstrators, dashboards, and solution pathways linking stakeholder needs to technical services. application/ld+json https://w3id.org/ro-id/4fdb4e5d-e51d-4f22-936f-1db447c87ddc D1.3 - First Project activity, including Governance report MANUAL Gonzalez, Esteban. "D1.3 - First Project activity, including Governance report." ROHub. Mar 20 ,2026. https://w3id.org/ro-id/4fdb4e5d-e51d-4f22-936f-1db447c87ddc. Geographical Scope Information and Computing Sciences General Preparing the ground administration 5.317769130998703 4.1 summarise FAIR2Adapt activity 8.09968847352025 5.2 uncertainty 11.18143459915612 5.3 M1-M12 15.822784810126585 7.5 doubt 8.560311284046692 6.6 Documentation and information science Engineering (General) Knowledge Sector (EEA) FAIR2Adapt 11.814345991561183 5.6 Project activity 52.80373831775701 33.9 FAIR2Adapt foundation 15.189873417721522 7.2 implementation 7.522697795071337 5.8 community 8.041504539559014 6.2 Demonstration Conflicts, war and peace/Civil unrest/Demonstration Key Type Measures Other Engineering class 15.82360570687419 12.2 Methodology Engineering stakeholder 5.706874189364463 4.4 European Continent foundation 12.062256809338523 9.3 User Needs (RAST) fair understanding 8.566978193146417 5.5 Information Systems construction industry 76.08695652173914 3.5 Computer systems Stakeholders community 10.126582278481015 4.8 Engineering M1-M12 IPCC building 5.836575875486382 4.5 Climate Hazard Climate change impacts, risks and adaptation Data Format Year 2 will therefore focus on FAIR in practice, demonstrating concrete benefits through co-design, demonstrators, dashboards, and solution pathways linking stakeholder needs to technical services. 13.024282560706403 11.8 Governance and Institutional D1.3 - First Project activity, including Governance report This deliverable summarises FAIR2Adapt activities and governance during its first reporting period (M1–M12, 2025), reviewing progress across all seven work packages and defining priorities for Year 2. 52.53863134657837 47.6 activity 16.033755274261605 7.6 Mathematical and computer sciences (general) Space sciences case study 6.614785992217898 5.1 Computation Theory and Mathematics none Policy Scale Year 1 built a strong foundation for FAIR implementation across six case studies through targeted capacity building, transforming initial uncertainty into readiness. 34.437086092715234 31.2 year 19.831223628691987 9.4 Social and information sciences parcel 5.706874189364463 4.4 Academia/ Research Institutions No policy or regulation work package 7.943925233644858 5.1 Space sciences (General) trade 23.913043478260875 1.1 Climate-ADAPT Adaptation Sectors Case Study Mathematical and computer sciences Computer Software General solution pathway 22.585669781931465 14.5 progress 6.22568093385214 4.8 activity 12.5810635538262 9.7 Distributed Computing Funding Institutional: Government policies and programs none EU Esteban Gonzalez Environmental research 0 https://api.rohub.org/api/ros/7c349915-a90b-4113-a16d-74d8a0e9d068/crate/download/ 2026-03-20 17:43:21.033013+00:00 2026-03-20 17:44:58.297286+00:00 2026-03-20 17:43:21.033013+00:00 This deliverable summarises FAIR2Adapt activities and governance during its first reporting period (M1–M12, 2025), reviewing progress across all seven work packages and defining priorities for Year 2. Year 1 built a strong foundation for FAIR implementation across six case studies through targeted capacity building, transforming initial uncertainty into readiness. While FAIR understanding is now in place, communities do not yet clearly see the practical value of FAIR Digital Objects, as technical developments progressed in parallel with onboarding. Year 2 will therefore focus on FAIR in practice, demonstrating concrete benefits through co-design, demonstrators, dashboards, and solution pathways linking stakeholder needs to technical services. application/ld+json https://w3id.org/ro-id/7c349915-a90b-4113-a16d-74d8a0e9d068 D1.3 - First Project activity, including Governance report MANUAL Gonzalez, Esteban. "D1.3 - First Project activity, including Governance report." ROHub. Mar 20 ,2026. https://w3id.org/ro-id/7c349915-a90b-4113-a16d-74d8a0e9d068. Year 1 built a strong foundation for FAIR implementation across six case studies through targeted capacity building, transforming initial uncertainty into readiness. 34.437086092715234 31.2 Academia/ Research Institutions Space sciences (General) Mathematical and computer sciences (general) implementation 7.522697795071337 5.8 Institutional: Government policies and programs foundation 12.062256809338523 9.3 administration 5.317769130998703 4.1 foundation 15.189873417721522 7.2 Climate Hazard Project activity 52.80373831775701 33.9 case study 6.614785992217898 5.1 Key Type Measures uncertainty 11.18143459915612 5.3 Computation Theory and Mathematics work package 7.943925233644858 5.1 progress 6.22568093385214 4.8 none Space sciences year 19.831223628691987 9.4 IPCC Geographical Scope Governance and Institutional solution pathway 22.585669781931465 14.5 General M1-M12 parcel 5.706874189364463 4.4 building 5.836575875486382 4.5 community 8.041504539559014 6.2 Documentation and information science Engineering stakeholder 5.706874189364463 4.4 Climate change impacts, risks and adaptation Policy Scale Demonstration Conflicts, war and peace/Civil unrest/Demonstration Stakeholders FAIR2Adapt 11.814345991561183 5.6 trade 23.913043478260875 1.1 Other Engineering EU none European Continent No policy or regulation M1-M12 15.822784810126585 7.5 User Needs (RAST) Knowledge Sector (EEA) summarise FAIR2Adapt activity 8.09968847352025 5.2 Climate-ADAPT Adaptation Sectors Mathematical and computer sciences activity 12.5810635538262 9.7 Data Format Social and information sciences fair understanding 8.566978193146417 5.5 General D1.3 - First Project activity, including Governance report This deliverable summarises FAIR2Adapt activities and governance during its first reporting period (M1–M12, 2025), reviewing progress across all seven work packages and defining priorities for Year 2. 52.53863134657837 47.6 Methodology class 15.82360570687419 12.2 construction industry 76.08695652173914 3.5 FAIR2Adapt community 10.126582278481015 4.8 Computer Software Distributed Computing Engineering Preparing the ground activity 16.033755274261605 7.6 Engineering (General) Computer systems Information and Computing Sciences Case Study doubt 8.560311284046692 6.6 Year 2 will therefore focus on FAIR in practice, demonstrating concrete benefits through co-design, demonstrators, dashboards, and solution pathways linking stakeholder needs to technical services. 13.024282560706403 11.8 Funding Information Systems Esteban Gonzalez Applied sciences https://fair2adapt.github.io/riomar-dashboard/ 2026-03-20 15:22:58.427334+00:00 2026-03-20 18:12:17.330524+00:00 Dashboard Dashboard 2026-03-20 15:22:58.427334+00:00 https://pangeo-eosc-minioapi.vm.fedcloud.eu/afouilloux-dggs/sentinel_bbox_l20_pyramid.zarr/7 2026-03-20 18:13:34.399299+00:00 2026-03-20 19:26:14.441919+00:00 sentinel_bbox_l20_pyramid.zarr 2026-03-20 18:13:34.399299+00:00 https://pangeo-eosc-minioapi.vm.fedcloud.eu/afouilloux-dggs/sentinel_bbox_l20_pyramid.zarr/7 Academia/ Research Institutions HEALPix DGGS 15.098468271334792 6.9 Monitoring, evaluating and learning HEALPix DGGS approach 23.11046511627907 15.9 Climate-ADAPT Adaptation Sectors Rouen Climate Hazard database 28.448275862068968 3.3 Information Systems Mathematical Sciences Funding Geographical Scope Computer Software Stakeholders France Mathematical and computer sciences France 10.48951048951049 7.5 Methodology none Computer systems pyramid 14.879649890590809 6.8 satellite 8.251748251748252 5.9 Paris HEALPix Discrete Global Grid System 26.744186046511626 18.4 visualization 6.013986013986014 4.3 Normandie Mathematical Physics Social and information sciences Physics Case Study Key Type Measures computer science 30.17241379310345 3.5 Structural/physical: Ecosystem-based Discrete Global Grid System 12.472647702407002 5.7 geometry 13.793103448275863 1.6 Information and Computing Sciences Mathematical and computer sciences (general) metadata 6.293706293706293 4.5 EU pyramid 12.167832167832167 8.7 nested HEALPix 15.116279069767442 10.4 Geosciences (General) collection 4.895104895104895 3.5 Engineering (General) ### FAIRification - Satellite imagery converted to DGGS using [xhealpixify](https://github.com/IAOCEA/xhealpixify) - Machine-actionable: `schema:ViewAction` links the dataset to the [FAIR2Adapt dashboard](https://fair2adapt.github.io/riomar-dashboard/) for interactive visualization at any zoom level - Metadata enriched with [I-ADOPT](https://i-adopt.github.io/) variable decomposition 23.014804845222073 17.1 ### Dataset - **Variable**: Band 02 (Blue, 490nm) top-of-atmosphere reflectance - **Spatial coverage**: Normandy, France (~48.5°N–49.5°N, 0.5°E–1.5°E) - **Grid**: HEALPix multiscale pyramid (11 levels) - Finest: level 20 (nside=1,048,576, ~10m resolution, 208M cells) - Coarsest: level 10 (nside=1,024, ~10km resolution) - Resampling: mean aggregation between levels - **Format**: Cloud-optimized Zarr with nested HEALPix indexing on WGS84 ellipsoid 26.514131897711973 19.7 User Needs (RAST) Nanotechnology Science and technology/Technology and engineering/Micro science/Nanotechnology Physics (General) http 13.426573426573427 9.6 Knowledge Sector (EEA) IPCC European Continent Geosciences reflectivity 7.972027972027972 5.7 Documentation and information science dataset 13.006993006993008 9.3 Numerical and Computational Mathematics Policy Scale Normandie 10.48951048951049 7.5 FAIR2Adapt — Sentinel-2 B02 reflectance on HEALPix DGGS (multiscale pyramid) Sentinel-2 Level-1C satellite observation converted to a HEALPix Discrete Global Grid System (DGGS) multiscale pyramid, covering a region in **Normandy, France** (Seine Valley, between Rouen and Paris) 50.47106325706594 37.5 Statistics information technology 27.586206896551726 3.2 Engineering France 12.691466083150983 5.8 Earth resources and remote sensing Climate change impacts, risks and adaptation Physical and Technological Physical Sciences http 16.192560175054705 7.4 spirit level 6.993006993006993 5.0 Agriculture Astronomical and Space Sciences Regional policy FAIR2Adapt 12.910284463894966 5.9 multiscale pyramid 10.755813953488373 7.4 IT-computer sciences Science and technology/Technology and engineering/IT-computer sciences dataset 15.754923413566738 7.2 satellite observation 24.27325581395349 16.7 Seine Valley Data Format 2026-03-20 18:12:17.997118+00:00 0 https://api.rohub.org/api/ros/fdc1c071-76d7-44df-a565-8217ebcc59fe/crate/download/ 2026-02-20 22:03:58.321018+00:00 2026-04-11 02:51:16.533696+00:00 2026-02-20 22:03:58.321018+00:00 Sentinel-2 Level-1C satellite observation converted to a HEALPix Discrete Global Grid System (DGGS) multiscale pyramid, covering a region in **Normandy, France** (Seine Valley, between Rouen and Paris). ### Dataset - **Variable**: Band 02 (Blue, 490nm) top-of-atmosphere reflectance - **Spatial coverage**: Normandy, France (~48.5°N–49.5°N, 0.5°E–1.5°E) - **Grid**: HEALPix multiscale pyramid (11 levels) - Finest: level 20 (nside=1,048,576, ~10m resolution, 208M cells) - Coarsest: level 10 (nside=1,024, ~10km resolution) - Resampling: mean aggregation between levels - **Format**: Cloud-optimized Zarr with nested HEALPix indexing on WGS84 ellipsoid ### FAIRification - Satellite imagery converted to DGGS using [xhealpixify](https://github.com/IAOCEA/xhealpixify) - Machine-actionable: `schema:ViewAction` links the dataset to the [FAIR2Adapt dashboard](https://fair2adapt.github.io/riomar-dashboard/) for interactive visualization at any zoom level - Metadata enriched with [I-ADOPT](https://i-adopt.github.io/) variable decomposition ### Context Part of the [FAIR2Adapt](https://fair2adapt.eu) project, demonstrating that the HEALPix DGGS approach works for both ocean model outputs and Earth observation data. The multiscale pyramid enables efficient visualization from global overview to full 10m resolution. application/ld+json https://w3id.org/ro-id/fdc1c071-76d7-44df-a565-8217ebcc59fe FAIR2Adapt — Sentinel-2 B02 reflectance on HEALPix DGGS (multiscale pyramid) MANUAL Fouilloux, Anne. "FAIR2Adapt — Sentinel-2 B02 reflectance on HEALPix DGGS (multiscale pyramid)." ROHub. Feb 20 ,2026. https://w3id.org/ro-id/fdc1c071-76d7-44df-a565-8217ebcc59fe. View Sentinel-2 data in FAIR2Adapt Dashboard