Recommendations for Services in a FAIR DataEcosystem

This article puts forward recommendations for data and infrastructure service providers to support Findable, Accessible, Interoperable, and Reusable (FAIR) research data within the scholarly ecosystem. Such recommendations are important to coordinate progress in realising a FAIR data ecosystem in which research data can be easily shared and optimally reused, with the aim of driving down inefficiencies in the current academic system and enabling new forms of data-driven discovery.

Key recommendations - ranked by their perceived urgency  - resulting from an extensive community consultation process include:

• Funders and institutions should consider FAIR alignment and data sharing as part of research assessment, among other criteria.

• Services should support domain-specific ontologies by identifying disciplines that lack ontologies and enriching existing registries of ontologies.

• Repositories should support FAIR data by developing tools such as APIs, sharing best practices and undergoing FAIR aligned certification.

• Institutions should support FAIR awareness and implementation by establishing data stewardship programmes providing simple and intuitive training for researchers.

The recommendations outlined in this article are meant to help guide the way forward to putting into practice the FAIR guiding principles for data management. They sharpen and improve  the recommendations formulated in the Turning FAIR into reality report1 which explicitly states that “More work is needed to extend the FAIR data principles for application to a wide range of data services...”. The work presented here supports that objective by highlighting areas of focus and priority from various stakeholder groups - in particular within the context of the European Open Science Cloud (EOSC) - as well as the formulation of additional recommendations.