Metric and Benchmark Commons

In the context of FAIR assessment and assistance, metrics are clearly defined, narrative descriptions of community-specific implementations of individual FAIR Principles. Benchmarks are structured groupings of these metrics that articulate how a specific research community interprets FAIR in ways that are meaningful for particular domains, object types, or use cases.

Benchmarks provide a narrative that captures a community’s priorities and expectations for FAIRness, enabling consistency and comparability in assessment while preserving contextual relevance.⁤ Community-defined metrics and benchmarks are critical because they ensure that FAIR assessment is open, transparent, and adaptable: they allow researchers and domain experts to collaboratively define what FAIR means for their specific objects and workflows, support reuse of definitions across projects and tools, and enable FAIR assessments that are both machine-actionable and aligned with shared interpretations of FAIR. By anchoring assessments in community consensus and making these definitions discoverable and interoperable, research groups can drive more meaningful evaluation, reduce ambiguity in FAIR interpretation, and foster trust and reuse within and across disciplines.

The FAIRassist registry (https://fairassist.org/registry), powered by FAIRsharing (https://fairsharing.org/) provides a trusted, community-facing commons for FAIR metrics and benchmarks used within OSTrails and by the wider research community adopting the Assess-IF. By offering a single, curated point of access, the registry helps researchers, infrastructure providers, funders, and publishers identify, compare, and reuse assessment components in a transparent and interoperable way.

FAIRassist (for conceptual components such as metrics and benchmarks) and the FDP Index (for software-based assessment services) act as complementary exemplar services that demonstrate how Assess-IF components can be:

• Registered and shared using community-agreed descriptions,

• Discovered efficiently, based on digital object type, disciplinary relevance, or generic applicability, and

• Understood and reused, through clear documentation that supports consistent and responsible FAIR assessments.

Registering metrics and benchmarks in FAIRassist and FDP is strongly recommended to promote transparency, reuse, and FAIR-aligned assessment practices. Once a metric or benchmark is considered mature by its maintainer, it can be assigned a DOI, enabling citation, credit, and long-term reference within assessment workflows and policy contexts. Through FAIRsharing’s APIs and content negotiation, the registry exposes rich, human-curated descriptions in machine-actionable formats (including DCAT and JSON). This allows FAIR assessments to move beyond bespoke or opaque implementations, supporting automation, comparability, and interoperability across tools, communities, and infrastructures. For further details, see the sections on FAIRsharing and FAIRassist in the documentation (FAIRsharing Registry, FAIRassist Registry).