Scientific data repositories in research infrastructure: Adoption of FAIR principles

Abstract

Research infrastructures are implemented by institutions to support the discovery, sharing, exploration, analysis, curation, use, replication and management of data that, line up with the issues discussed in the Open Science context, have the potential accelerate discovery and scientific innovation. FAIR principles for data science are being adopted in connection with research infrastructures such as CLARIN that provide data repositories for data management. The purpose of this paper is to present the CLARIN research infrastructure which adopted the FAIR principles and discuss the relevance of data repositories in this context. The qualitative methodology was used as base the bibliographic survey for the discussion about the themes. To collect data on CLARIN infrastructure data, the Registry of Research Data Repositories (re3data.org) was used. It is concluded that data repositories provide conditions to accord FAIR requirements and that the number of data repositories integrated into the CLARIN infrastructure demonstrates the added value of these repositories.