OneWater FAIR Data Platform: towards a national FAIR water data platform and community

In France, the national research and innovation program ‘OneWater - Eau Bien Commun’ (2022-2032) addresses a wide range of key scientific issues to help protect and manage water as a common good. This 10-year program is made up of several projects that will generate a large amount of highly heterogeneous data, ranging from sensor data to social science data, samples and model-based data. It will also draw on existing data documenting the state of water resources, produced by observatories and research infrastructures (e.g. the OZCAR network of critical zones or the Réseau des Zones Ateliers in France), but also by operational public monitoring services run by the French State for its national Water Information System and by regional stakeholders. All the data are not yet fully available according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles (Wilkinson et al. 2016). To process, share and re-use heterogeneous data sets and ultimately generate new knowledge, a dedicated project has been set up within the OneWater program to establish the national ‘OneWater FAIR Water Data Platform’. The ambition of this project is to go beyond a simple data catalog by fostering a FAIR Water Data ecosystem based on international standards and implementing semantic web interoperability in order to enhance data discoverability and use. The proposed approach is to produce, as far as possible, data that is compliant with FAIR principles by DNA. The OneWater data platform will be fully integrated in the national research data ecosystem dealing with research data, which relies on the Data Terra Research Infrastructure and its data hubs. The land surfaces THEIA data hub with its remote and in situ data components (Theia/OZCAR Information System (IS), Braud et al. 2020) are particularly relevant to the OneWater project. Collaboration will also be organized with the services supporting national public policy data and associated monitoring networks (French Ministry of Environment). At the international level, connection with the international community is being established so that the OneWater initiative can contribute to and benefit from the FAIR Water community. This includes the Open Geospatial Consortium Hydrology Domain Working Group (OGC HydroDWG), the Research Data Alliance Global Water Information Interest Group (RDA GWIIG), the World Meteorological Organization (WMO), the Integrated European Long-Term Ecosystem, critical zone and socio-ecological Research Infrastructure (eLTER RI), the Terrestrial Environmental Observatories Network (TERENO) amongst others. The OneWater data project does not only address data and information technology needs, but is also committed to supporting the water community to achieve creating an ecosystem of standards, tools and resource persons. Actions will help identify and overcome barriers that hinder the streamlined exchange of FAIR Water Data and the adoption of best practices. This will be achieved by building up a national overview of water data use practices, tools and obstacles for both researchers and operational stakeholders, then by organizing training sessions and supporting the community so that the tools they traditionally use evolve towards FAIR practices. In order to gather the needs of the platform users, a survey was sent to the water community in order to gather their requirements in terms of the data products and services needed to facilitate their work (data collection, data analysis, model set up, calibration and evaluation). The results of the survey were analysed to define several use cases that will serve as examples to build the OneWater platform iteratively, regularly gathering users' feedback and taking it into account to ensure that the developed platform truly meets their needs. To facilitate interaction with the user community, a public gitlab has been set up. One working group addressed the definition of FAIRness within the OneWater Data community by specifying how the FAIR principles of Wilkinson et al. (2016) are interpreted for Water data in the light of the existing international standards and best practices. It will also propose FAIRness grids analysis for various numerical resources (data sets, software, catalogs, vocabularies) after an analysis of existing on-line tools that often work as black boxes and do not provide enough information on how they have interpreted and evaluated the FAIR principles. The proposed grids were tested with data sets from the national groundwater monitoring system and the Theia/OZCAR IS (Braud et al. 2020) and with the Theia/OZCAR thesaurus that implements the RDA I-ADOPT recommendation for the description of Observable Properties (Coussot et al. 2024). OneWater's FAIR Data platform architecture is defined around well-known and most recent interoperability standards and practices (OGC, W3C, RDA, INSPIRE, etc.). It also takes into account the latest FAIR Open Science prototyping exercises such as the use of platforms like GALAXY and the associated recommendations (Royaux et al. 2024) and the results of pilot projects such as the OGC Open Science Persistent Demonstrator. In order to gather the needs of the platform users, a survey was sent to the water community in order to gather their requirements in terms of the data products and services needed to facilitate their work (data collection, data analysis, model set up, calibration and evaluation). The results of the survey were analysed to define several use cases that will serve as examples to build the OneWater platform iteratively, regularly gathering users' feedback and taking it into account to ensure that the developed platform truly meets their needs. To facilitate interaction with the user community, a public gitlab has been set up. One working group addressed the definition of FAIRness within the OneWater Data community by specifying how the FAIR principles of Wilkinson et al. (2016) are interpreted for Water data in the light of the existing international standards and best practices. It will also propose FAIRness grids analysis for various numerical resources (data sets, software, catalogs, vocabularies) after an analysis of existing on-line tools that often work as black boxes and do not provide enough information on how they have interpreted and evaluated the FAIR principles. The proposed grids were tested with data sets from the national groundwater monitoring system and the Theia/OZCAR IS (Braud et al. 2020) and with the Theia/OZCAR thesaurus that implements the RDA I-ADOPT recommendation for the description of Observable Properties (Coussot et al. 2024). OneWater's FAIR Data platform architecture is defined around well-known and most recent interoperability standards and practices (OGC, W3C, RDA, INSPIRE, etc.). It also takes into account the latest FAIR Open Science prototyping exercises such as the use of platforms like GALAXY and the associated recommendations (Royaux et al. 2024) and the results of pilot projects such as the OGC Open Science Persistent Demonstrator. This communication will present the general approach that is being implemented in the OneWater data project and highlight first results obtained since the beginning of the project.