ProvenanceGraph

ProvenanceGraph is a formal representation and software construct for capturing the provenance of digital objects as a graph of interrelated entities, activities, and agents. In this model, nodes typically denote artifacts (data products, documents, files), activities (process steps, computation, transformations), and agents (people or organizations) with edges that encode provenance relations such as wasGeneratedBy, used, wasAssociatedWith, and wasAttributedTo. The structure naturally forms a directed graph and is often implemented as a graph database or an in-memory graph to support lineage queries and visual inspection. Applications center on reproducibility, auditing, and data governance by enabling reconstruction of how a given artifact was produced and by whom.

The design is aligned with the W3C PROV family of standards. ProvenanceGraph can be mapped to PROV-DM for conceptual modeling, PROV-O for RDF-based representations, and PROV-XML for serializations. This interoperability supports integration across tools and domains and allows provenance to be shared between systems.

Typical features include immutability of provenance records, versioning of artifacts, time stamps, and support for lineage queries such as tracing ancestry, identifying responsible agents, or describing transformation steps. Implementations vary; some store provenance in a dedicated graph database with labeled relationships, while others annotate existing workflow systems or data catalogs with provenance metadata. Challenges include scalability for large data sets, privacy and access control, and the evolving nature of provenance schemas.

Use cases include scientific workflows to reproduce experiments, data integration pipelines, digital archiving, compliance auditing, and provenance-aware data analytics. See also PROV, data lineage, graph databases.