PROVframework

PROVframework is a modular software framework designed to manage data provenance within data processing pipelines. It provides tools to capture, store, and query provenance information so that data products can be traced from their inputs, through transformations, to final results. The framework is aligned with the W3C PROV family of specifications, including the PROV Data Model (PROV-DM) and the PROV ontology, to represent entities, activities, agents, and their relationships.

Architecture and features: PROVframework consists of a provenance producer interface for recording events, a persistent store for provenance graphs, and a query layer for exploring lineage. It includes adapters to popular workflow engines and data-processing systems, allowing automatic provenance capture without intrusive changes to pipelines. The graph engine supports incremental updates, versioning, and stable identifiers for entities and activities. Export components enable serialization to PROV-JSON, PROV-XML, or PROV-N, and there are visualization tools for graph rendering and analysis.

Interoperability: By adhering to PROV-DM and PROV-O mappings, PROVframework can interoperate with other provenance tools and repositories. It supports standard provenance queries and can integrate with access-control and audit mechanisms to support governance and compliance needs.

History and usage: The concept of provenance frameworks traces to the W3C PROV specifications published in the early 2010s; PROVframework emerged as an implementation reflecting these standards, with ongoing development by an international developer community. The project emphasizes reproducibility, data quality, and transparency in research and production settings.

Applications: Scientific research, data science, data governance, regulatory compliance, reproducibility studies, and pipeline auditing.