FAIRifying Clinical Studies Metadata: A Registry for the Biomedical Research.

ABSTRACT

The data produced during a research project are too often collected for the sole purpose of the study, therefore hindering profitable reuse in similar contexts. The growing need to counteract this trend has recently led to the formalization of the FAIR principles that aim to make (meta)data Findable, Accessible, Interoperable and Reusable, for humans and machines. Since their introduction, efforts are ongoing to encourage FAIR principles adoption and to implement solutions based on them. This paper reports on the FAIR-compliant registry we developed to collect and serve metadata describing clinical trials. The design of the registry is based on the FAIR Data Point (FDP) specifications, the state-of-the-art reference for FAIRified metadata sharing. To map the metadata relevant to our use case, we have extended the DCAT-based semantic model of the FDP adopting well-established ontologies in the biomedical and clinical domain, like the Semanticscience Integrated Ontology (SIO). Current implementation is based on the Molgenis software and provides both a user interface and a REST API for metadata discovering. At present the registry is being loaded with the metadata of the 18 clinical studies included in the 'I FAIR Program', a project finalised to the dissemination of FAIR best practices among the clinical researchers in Sardinia (Italy). After a testing phase, the registry will be publicly available, while the new model and the source code will be released open source.