How to make research information FAIR: DSpace-CRIS and best practices in open research information

Abstract

In 2014, a group of scientists and stakeholders in the Data Science community created the FAIR Data Publishing Group in the context of Force11 (a community of scholars, librarians, archivists, publishers and research funders that facilitates the change toward improved knowledge creation and sharing), to debate about how to enhance the ecosystem of research data. The output was a set of guiding principles and practices to make users able to more easily discover, access, interoperate, and reuse, the vast amount of data generated by research. These principles should enable implementation of compliant tools that support FAIRness of data management.

Since the publication of these principles in 2016, initiatives have multiplied to define what FAIR (Findable, Accessible, Interoperable, Reusable) means in a variety of contexts, for human interpretation and machine-to-machine action, particularly in the repositories ecosystem, representing the place where research data should be deposited, indexed, preserved and made available to the scholarly community.