Scientific context
Scientific communities produce a valuable amount of data as a direct or side product of their research, which can be potentially explored in many different applications. However, making data open and accessible requires considerable efforts in order to guarantee the data quality and compliance to the FAIR principles (Findability, Accessibility, Interoperability, and Reusability).
Semantics4FAIR is one of the projects selected by the French National Research Agency (ANR) on the FLASH CALL Open Science entitled "research practices and open research data". It aims at facilitating the tasks of finding and accessing scientific data that results from both research and production by a scientific community, in order to support the development of new usages by other scientific communities. The originality of the proposed approach is twofold: (i) a human factor method to capture user’s needs and vocabularies; and (ii) a semantic approach takes up the findability challenge.
We plan to build and reuse several ontologies to account for the various points of view on the data and the relations between these views: one ontology will account for the data producers’ view, and the users’ vocabulary refers to a different ontology. These ontologies will be then used to describe the data, its provenance and usages, and will be the basis for the development of services querying and consuming data.
This work will rely on the collaboration of a computer science lab (IRIT) and a human-factor institute (MSH-T) with scientific communities that want to make their datasets FAIR, and scientific communities that want to reuse this data for their own research projects. We propose to test the approach thanks to a joint work with the atmospheric scientific community (OMP and CNRM) as meteorology data providers, and the Palynologist community (GET) and meteorology data exploitation (MeteoFrance) services as two data user communities.
