Data Provenance
Documentation of data origin, collection, and transformations for AI systems.
How the laws define this
Documenting, tracking, or recording where data comes from, how it was collected, and the processing or transformations it undergoes forms the shared core of these definitions, establishing the basis for data reliability, integrity, and trustworthiness in AI systems. The primary divergence lies in what specific data must be tracked and why it is retained. The Artificial Intelligence Technologies and Recordkeeping Policy mandates meticulous documentation covering training data, input data, and data generated during the AI process to evaluate reliability. In contrast, ISO/IEC 5259-1:2024 highlights how tracking the data's journey enables traceability for operational tasks like debugging, auditing, and ensuring accountability. ISO/IEC 5338:2023 broadens this focus further by framing provenance as a key checkpoint in the AI system life cycle processes essential for ensuring compliance alongside general quality.
Synthesised from the 3 statutory definitions below. Each one is quoted in full, with its source.
Definitions (3)
Data provenance refers to the meticulous documentation of the origin, collection methods, processing, and transformation of all data used by AI systems. This includes training data, input data, and any data generated during the AI process, crucial for understanding data reliability.
Data provenance refers to the record of the data's origin, its journey, and all transformations it has undergone. Understanding data provenance is crucial for verifying data integrity, establishing trust in data sources, and enabling traceability, which is vital for debugging, auditing, and ensuring accountability in AI systems.
Data provenance tracks where data comes from, how it was collected, processed, and modified, which is crucial for ensuring data quality, trustworthiness, and compliance in AI systems, and is a key checkpoint in the AI system life cycle.
Related Terms
Dataset Provenance
Traceable metadata on the origin and composition of training data....
data provenance/lineage
Record of data origins and processing history....
Content Provenance
Traceability of content origin and processing history....
Data risk
Risks from data quality, provenance, representativeness, and privacy....
Provenance data
Data used to trace and verify content origin....