konsistensmetadata

Konsistensmetadata is metadata that describes and governs data consistency across data objects, datasets, or systems. It records the rules, constraints, assumptions, and policies used to ensure data remains accurate, coherent, and usable over time. By capturing how data should align with other data and with business expectations, konsistensmetadata supports validation, reconciliation, and auditability.

Core components include constraints and validation rules (such as primary keys, referential integrity, or business logic), state and version information (for example, current vs. historical versions, timestamps, and update status), provenance and lineage (where data came from and how it has been transformed), and integrity checks (checksums or hashes to detect tampering or corruption). In distributed or multi-system environments, konsistensmetadata may also describe conflict resolution policies, synchronization status, and reconciliation procedures.

Applications of konsistensmetadata span data governance, data integration, and data pipelines. It aids quality assurance by making consistency rules explicit, supports data lineage and impact analysis, and facilitates automated checks during ingestion, processing, and distribution. In practice, konsistensmetadata can complement data quality metadata and metadata standards by embedding constraints and state information within data management workflows, processes, and catalogs.

Standards and implementation vary; there is no single universal standard for konsistensmetadata. Organizations often represent it using a combination of existing metadata schemas and practices, such as provenance models, schema validation descriptions, and integrity or versioning metadata. The concept aligns with broader efforts in data governance, data quality, and digital preservation to ensure reliable, auditable, and interoperable data systems.