The FAIR Principles (Findable, Accessible, Interoperable, Reusable) are a set of high-level guidelines for optimizing sharing digital resources in a machine-friendly environment. Their growing global acceptance and adoption by policymakers and organizations compels data professionals, projects, and repositories to demonstrate the level of FAIR-compliance (FAIRness) of their digital data, metadata, and infrastructures.
Despite the straightforward acronym, the FAIR Principles are inherently complex, multi-dimensional, multi-layered, and multi-faceted, involving core concepts with numerous elements (as shown in the figure below). Implementing these principles involves navigating complexities and subjective interpretations. It must also account for domain-specific and application-specific dependencies, such as defining “rich metadata” and its implication to the Copernicus Climate Data catalogue.
This presentation takes a deep dive into the complexity of the FAIR Principles, identifies associated quality measures, and highlights several existing tools for evaluating data FAIRness. Dr. Peng will discuss their relevance to the Copernicus Climate Data catalogue, share the insights gained from assessing the FAIR compliance of NASA Earth science data products, and explore how a data catalogue can facilitate and support FAIR-compliance. This sets the stage for broader discussions on strategies to enhance the FAIRness of data products hosted by the Copernicus Climate Data Store and across ECMWF.