Lessons learned and best practices in developing an information system for interdisciplinary, heterogeneous, multidimensional environmental data: the WIBE (Water Interdisciplinary Biology and Ecology) information system

Research data collected during scientific projects financed by public funds must be reusable not only by the scientific community which produces them, but also by the civil society who finances the projects through taxes. The systematic provision of publicly financed research data is an important condition for the reproducibility of science and the reuse of results and data in the context of other studies. Guiding principles facilitating the sharing and reuse of research data (the FAIR 'Findable Accessible Interoperable Reusable' principles and European initiatives to develop the European Open Science Cloud EOSC) are fostering the conditions of this necessary change at the European scale. It would be tempting to think that the creation of FAIR and open data is a simple, static, and achievable one-step process. Our experience shows that many challenges are paving the way to structure, share and open research data, interdisciplinary. This chapter describes the lessons learned for structuring, sharing, and opening interdisciplinary heterogeneous environmental data from multiple research projects. The WIBE case study involved the curation of biological data (e.g. invertebrate biomarkers), multi-source contextual data (socio-economic data, e.g. port attendance), oceanographic monitoring data (e.g. sea temperature, sea salinity, Chl.a), sea pollution data (e.g. concentration of hydrocarbons). Based on our experience in developing WIBE, an information system respecting the FAIR principles and the “as open as possible as closed as necessary” requirements, this chapter also draws recommendations on developing approval mechanisms for different data producers so that the minimum vocabularies and metadata meet the needs of the entire community and proposes best practices to "create the conditions for reuse" for interdisciplinary data by offering a data architecture enable to welcome data from multidimensional topics, formats and scientific approaches dedicated to marine and freshwater research.