Résumé
The recent technological advancements and emergence of the open data in environmental and life sciences areopening new research opportunities while creating new challenges around data management. They makeavailable an unprecedented amount of data that can be exploited for studying complex phenomena. However,new challenges related to data management need to be addressed to ensure effective data sharing, discovery andreuse, especially when dealing with interdisciplinary research contexts. These issues are magnified in interdisciplinarycontext, by the fact that each discipline has its practices, e.g., specific formats and metadata standards.Moreover, the majority of current data management practices do not consider semantic heterogeneity existingamong disciplines. For this reason, we introduce a flexible metadata model that describes the datasets of variousdisciplines using a common paradigm based on the observation concept. It provides a key vision for articulatingthe user point of view and underlying scientific domains. In this study, we therefore decide to mainly reuse theSOSA lightweight ontology (Sensor, Observation, Sample, and Actuator) to efficiently leverage others existingontologies to improve datasets discovery and reuse coming from Earth and life observation. The main benefit ofthe proposed metadata model is that it extends the technical description, usually provided by existing metadatamodels, with the observation context description enabling the need of a user viewpoint. Moreover, following theFAIR principles, the metadata model specifies the semantics of its elements using ontologies and vocabularies,and reuses as much as possible ontological and terminological existing resources. We show the benefit andapplicability of the model through a case study we identified as representative after interviewing researchers inenvironmental and life sciences.