A Comprehensive Definition of Data Provenance

Data provenance is the history of data detailing its origin, transformations, and movement across systems. It ensures data integrity, security, and transparency throughout its life cycle. Key components include data lineage, source, transformation, and destination. Two classes of data provenance are backward (retrospective) and forward (prospective). Techniques for tracking data provenance range from manual documentation to automated systems, blockchain technology, metadata management, and provenance-aware storage systems. Standards and protocols like W3C PROV and ISO standards ensure uniformity and efficiency in tracking data provenance. Benefits include data integrity, regulatory compliance, error detection, and enhanced security. Challenges include scalability, privacy concerns, and complexity. Use cases span industries such as health care, finance, and scientific research where the history of data is crucial for maintaining accuracy, compliance, and transparency.