FAIR F2 for database evaluation
This feature and the entire section is in active development.
FAIR Principle F2: Data are described with rich metadata
https://doi.org/10.25504/FAIRsharing.e05e98
FAIR Principle F2 requires that data are described with rich metadata that supports discovery. Within the ARK-based benchmarks, this principle focuses on whether databases themselves are described with sufficient metadata to enable discovery, interpretation, and classification by users and tools/services.
Discovery metadata is an important FAIR-enabling characteristic because it supports search, filtering, indexing, and interoperability across registries and discovery services. Unlike dataset-level interpretations of F2, which evaluate metadata associated with individual digital objects, the ARK-based benchmarks evaluate discovery metadata describing the database itself.
There is some intentional overlap with R1.3. In F2, characteristics such as subject classification and object type are evaluated because they support discovery and identification of appropriate databases. In R1.3, similar characteristics may contribute to assessments of standards adoption, completeness, and community relevance.
The metrics associated with F2 evaluate whether databases provide sufficient discovery metadata describing their scope, purpose, content, and community context.
Database FAIR-Enabling Characteristics
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Database is described with rich discovery metadata
Presence of values for database name, description, country, at least one appropriate subject, and at least one object type.
Future Work
Future versions of the ARK-based benchmarks may distinguish between mandatory discovery metadata and richer optional discovery metadata. However, because the current FAIRsharing curation model requires all discovery metadata fields used by this metric, the present implementation evaluates them collectively as a single FAIR-enabling characteristic.
Additional discovery-oriented characteristics may be incorporated in future.
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