Dataset Datasheet

Data artifactGovernance & ComplianceSafety, Security & Governancearc:DatasetDatasheet

A structured document describing a dataset's motivation, composition, collection process, preprocessing, intended and inappropriate uses, distribution terms and maintenance, used for training, validation or testing AI systems.

Responsibility. Documents the provenance, composition and appropriate use of one dataset.

Also known as: Datasheet for datasets, Data card, Dataset sheet

Direct neighbourhood (hover for relationship types)

Relationships

is read by dependency

Model Card Generator Ch9.8

sends data to dynamic

is audited by assurance

Compliance Document Validator Ch9.8 Ref9.06

Design guidance

MUST be maintained even when models are well documented; dataset documentation explains why model behavior patterns emerged.
SHOULD record demographic distribution, collection timing and annotation procedures to surface bias.
SHOULD name a maintainer and version the dataset.

Classification

Patterns: Datasheets for Datasets
Quality attributes: Transparency and accountability (NIST AI RMF: accountable and transparent)Reliability (ISO/IEC 25010 | NIST AI RMF: valid and reliable)
Risks mitigated: Historical discrimination encoded in dataUnder-representation of minority groupsLabeling inconsistenciesCollection biasesImproperly retained PII
Frameworks & regulations: ISO/IEC 42001 Annex A: data controlsNIST AI RMF: MAP

Sources

Ch9.8: T. Nguyen, "Standards and Frameworks for AI Governance," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 9.8. ISBN: 9798244538229.
Ref9.06: "Auditing and Compliance Monitoring for AI Systems," unpublished reference note (references/Chapter 9 - Safety, Ethics, and Compliance/06-Auditing-Compliance-Monitoring.md), Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam supplementary materials, 2026. unpublished note