metadatabecome

Metadatabecome is a term used in information science to describe a shift in how metadata is treated within data ecosystems: metadata is not merely descriptive artifacts attached to data, but a central, actively managed asset whose value derives from its quality, provenance, and governance. In metadatabecome, metadata-driven approaches underpin data discovery, interoperability, governance, and even data products, with metadata themselves subjected to life-cycle management, versioning, and evaluation.

Origins and scope: The term has appeared in discussions of metadata-first architectures and data marketplaces, where metadata standards and rich provenance enable automated data integration and trust. It is not a formal standard, but a framing device to emphasize metadata as data.

Core concepts: Metadata becomes actionable data; metadata pipelines ingest, enrich, validate, and publish metadata; provenance and lineage are tracked; quality metrics and semantic enrichment are applied; reuse and interoperability are emphasized; alignment with FAIR and open data principles.

Applications: Data catalogs, discovery layers, data governance, compliance, data sharing, and marketplace ecosystems. Practices leverage standards such as DCAT, Dublin Core, schema.org, and PROV for provenance, while using schema mappings and data quality checks.

Benefits and challenges: Improved discoverability, faster integration, and stronger governance, while risks include governance overhead, metadata bloat, fragmentation of standards, and privacy concerns.

See also: metadata, data governance, data catalog, data lineage, FAIR data.