Connecting the dots: Transparent FAIRification of restricted data

In the age of information technology and Linked Data, the importance of creating transparent infrastructures for management and exchange of data have emerged to play a focal role for the development of new open research. The FAIR guiding principles have been introduced to advise in the improvement of Findable, Accessible, Interoperable and Reusable technical resources, but the literature is still lacking of practical guidelines for the management and digitization of sensitive and restricted data. The purpose of this research is to introduce new insights aimed at the exploration and discovery of restricted data-sets. The methodology sets out by creating a model for FAIR metadata architecture, which will later be used for automatic ingestion of external restricted data-set files, as well metadata enrichment. Quantitatively and qualitatively evaluations will be performed to assess the workflow, which will later be implemented in the data-set’s search engine. Initial results of the metadata ingestion and enrichment are presented as the RML mapper rules and the OPL ontology, respectively.