‘WorldFAIR: Global cooperation on FAIR data policy and practice’ was a two-year project to advance implementation of the FAIR principles, particularly in relation to interoperability and reusability of data within and across research domains. The project was conceived as responding to Recommendation 4 of the Turning FAIR into Reality report, which identified the need to ‘Develop interoperability frameworks for FAIR sharing within disciplines and for interdisciplinary research’. The Recommendation states that ‘Research communities need to be supported to develop interoperability frameworks that define their practices for data sharing, data formats, metadata standards, tools and infrastructure. To support interdisciplinary research, these interoperability frameworks should be articulated in common ways and adopt global standards where relevant.’ It is this vision of enabling community agreements around interoperability, and encouraging the identification and adoption of common standards that drove the WorldFAIR project.
WorldFAIR worked with a set of eleven domain and cross-domain case studies. Each case study developed an interoperability framework, recommendations and/or a FAIR implementation for their discipline or interdisciplinary research area. Led by CODATA, a coordinating and synthesis activity supported each Case Study in understanding their requirements through the completion of FAIR Implementation Profiles (FIPs). This work was summarised in a report on WorldFAIR's experience with FIPs and fed into recommendations FAIR Assessment within (and across) disciplines. Most importantly, the insights from close engagement with each of the Case Studies were incorporated into the development of the Cross-Domain Interoperability Framework (CDIF), which provides recommendations and guidance for five core functional requirements for interoperability and data combination. Further profiles are discussed and work will continue beyond the WorldFAIR project. Finally, the final ‘Policy Brief’ which summarises the project’s most important policy relevant recommendations and calls for a shift from a bibliographic approach to an engineering approach to data stewardship.
