WorkflowProvenienz

WorkflowProvenienz refers to the systematic recording and management of provenance information for workflows. It documents the history of a workflow run, including the data objects produced or transformed, the processes that acted upon them, the agents responsible, the timestamps, and the relationships among inputs, outputs, and intermediate results. This provenance information supports reproducibility, auditability, debugging, and governance in automated pipelines and scientific workflows.

Core concepts typically include artifacts (data items), activities (process steps), and agents (humans or software). Relationships such as wasGeneratedBy, used, and wasInformedBy capture how data flows through a workflow. The W3C PROV family, including PROV-DM and PROV-O, provides a widely adopted model and ontology to represent provenance across heterogeneous systems. Provenance data can be stored in metadata stores or embedded in datasets and can be captured through workflow engine instrumentation, logging, or post hoc extraction from logs and version control systems.

Applications of workflow provenance span data science pipelines, ETL processes, computational experiments, and regulated domains such as healthcare or finance where audit trails are required. Benefits include enabling reproducibility of results, facilitating error diagnosis, supporting impact analysis when inputs or parameters change, and aiding governance and compliance efforts.

Challenges involve managing large provenance volumes, potential performance overhead, privacy and security concerns for sensitive information, and interoperability across diverse tools and standards. Ongoing work seeks scalable storage and querying solutions and broader adoption of domain-specific provenance extensions to improve interoperability and practical utility.