A central challenge within BioFAIR is not whether FAIR matters, but how to begin and navigate an increasingly complex ecosystem of standards, repositories, and guidelines to enable informed decision-making and practical implementation. We present a set of interconnected resources that together form a FAIR knowledge layer, transforming uncertainty into actionable pathways and directly supporting the “end-to-end FAIR journey” that BioFAIR aims to deliver. FAIRsharing acts as the core intelligence and recommendation service, linking policies, standards, and databases to support FAIR compliance across the research data lifecycle, from data management planning to dataset publication. Its curated, structured knowledge graph, enriched and validated through the FAIRsharing Community Champions programme, serves as a trusted source of truth, powering downstream services, most notably the Data Stewardship Wizard (DSW), which delivers FAIR-compliant, machine-actionable Data Management Plans. FAIRassist builds on the FAIRsharing foundation by providing a measurable, generic, and extensible FAIR compliance and assistance backbone. Leveraging FAIRsharing content and community-defined FAIR profiles, it supports generation of evidence of FAIR alignment and offers actionable recommendations for improvements. Complementing and connected to these components is a FAIR literacy layer, delivered through the FAIR Cookbook and RDMkit, which provide practical, community-driven guidance, and are already part of the BioFAIR FAIR-in-action bridge Pathfinder project. These mature, interoperable FAIR-enabling resources are already embedded within the ELIXIR work programme and are increasingly adopted by European and worldwide research infrastructures, as well as in other disciplines. Together, they are well placed to deliver a scalable policy-to-practice framework for operationalising FAIR in BioFAIR.
Lister et al. (Fri,) studied this question.