The FAIR principles have been widely cited, endorsed and adopted by a broad range of stakeholders since their publication in 2016. By intention, the 15 FAIR guiding principles do not dictate specific technological implementations, but provide guidance for improving Findability, Accessibility, Interoperability and Reusability of digital resources. This has likely contributed to the broad adoption of the FAIR principles, because individual stakeholder communities can implement their own FAIR solutions. However, it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations. Thus, while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways, for true interoperability we need to support convergence in implementation choices that are widely accessible and (re)-usable. We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible, robust, widespread and consistent FAIR implementations. Any self-identified stakeholder community may either choose to reuse solutions from existing implementations, or when they spot a gap, accept the challenge to create the needed solution, which, ideally, can be used again by other communities in the future. Here, we provide interpretations and implementation considerations (choices and challenges) for each FAIR principle.

The Chemistry Implementation Network (ChIN) is focused on supporting the FAIR Data needs of the research community regarding chemical related data. An Implementation Network is a consortium drawn from a community, in this case the chemistry discipline, committed to defining and constructing standards, materials and software in the spirit of the FAIR data principles and under the structure of the GO FAIR project. Furthermore, as a core science the ChIN has to reach beyond the chemistry community and support the use of chemical information in other disciplines. This will be facilitated through connections in the GO FAIR ecosystem of Implementation Networks. Examples of the FAIR chemical concepts that need to be supported include molecular and materials structures, chemical reactions, nomenclature and other chemical terminology and conventions. The ChIN aims to drive forward the application of the FAIR Data Principles relating to the full range of chemistry concepts that are key to the transparent and efficient communication of chemical information. Realizing the goal of FAIR chemistry data will require a culture change across the discipline. However this is best addressed once a critical mass of tools and approaches has been developed.