FAIR EVA: Bringing institutional multidisciplinary repositories into the FAIR picture

TL;DR

FAIR EVA is a scalable, adaptable tool designed to evaluate and enhance the FAIRness of digital objects in multidisciplinary repositories, addressing the limitations of high-level indicators.

Contribution

It introduces FAIR EVA, a customizable, automatic tool tailored for specific data management systems within the European Open Science Cloud.

Findings

Successfully applied to DIGITAL.CSIC repository

Addresses variability in repository environments

Enhances FAIRness assessment accuracy

Abstract

The FAIR Principles are a set of good practices to improve the reproducibility and quality of data in an Open Science context. Different sets of indicators have been proposed to evaluate the FAIRness of digital objects, including datasets that are usually stored in repositories or data portals. However, indicators like those proposed by the Research Data Alliance are provided from a high-level perspective that can be interpreted and they are not always realistic to particular environments like multidisciplinary repositories. This paper describes FAIR EVA, a new tool developed within the European Open Science Cloud context that is oriented to particular data management systems like open repositories, which can be customized to a specific case in a scalable and automatic environment. It aims to be adaptive enough to work for different environments, repository software and disciplines, taking into account the flexibility of the FAIR Principles. As an example, we present DIGITAL.CSIC repository as the first target of the tool, gathering the particular needs of a multidisciplinary institution as well as its institutional repository.