Datalinjaus

Datalinjaus is a theoretical framework for representing data lineage and provenance within complex information systems. It is described as a formal model intended to document how data assets are created, transformed, and consumed across multiple processes and platforms, with the aim of improving traceability, accountability, and impact analysis.

Core concepts in the model include DataAsset, which denotes data items such as datasets, tables, or files; Process, representing system activities like ETL jobs, analytics tasks, or data exports; and Transformation, a specific operation that modifies data. Lineage edges connect assets and processes, using relation types such as produces, consumes, transforms, or derives. Each DataAsset carries attributes such as id, name, type, schema, owner, version, and quality indicators. Processes record identifiers, owners, start and end times, and input/output characteristics. Transformations capture applied operations and their parameters.

The typical representation is a directed acyclic graph (DAG) that shows how data flows from sources through transformations to outputs. The model supports versioning and branching to reflect lineage changes over time, as well as qualifiers for timestamps, data quality, and lineage confidence. It is designed to be technology-agnostic, with potential mappings to RDF/OWL, property graphs, or other semantic formats, and to integrate with data catalogs, governance tools, and audit systems.

History and use: Datalinjaus has appeared in theoretical and speculative discussions about data governance and lineage, rather than as a standardized, widely adopted specification. See also data lineage, data provenance, data governance.