metadataset

A metadataset is a dataset whose records describe other datasets. By organizing descriptive information about data collections, a metadataset supports discovery, evaluation, provenance, and reuse of data. It is a foundational component of data catalogs and data governance frameworks.

Typical records in a metadataset include fields such as title, description, publisher, creators, publication date, licensing, access rights, geographic or temporal coverage, data formats, data schemas or data types, size, provenance, version, quality metrics, and relations to related datasets. Identifiers like DOIs or persistent URLs are commonly used to reference datasets. Metadata may also capture usage restrictions, processing history, and quality indicators to help users assess suitability.

Applications include enabling search and discovery in data repositories, documenting datasets used in reproducible research and benchmarking, supporting data integration across studies, and facilitating meta-analyses and data-driven decision making.

Standards and interoperability: metadatasets often conform to metadata standards such as Dublin Core, DCAT, schema.org, or DataCite, which promote machine readability and cross-repository interoperability. They are typically stored in metadata registries or catalog systems and linked with persistent identifiers to support traceability.

Challenges include maintaining up-to-date and complete metadata, handling heterogeneous schemas, ensuring metadata quality, addressing privacy and licensing constraints, and managing versioning and provenance over time. Proper governance and automation can help mitigate these issues.

See also: metadata, metadata registry, data catalog, data repository, DCAT, Dublin Core, DataCite, schema.org.