Standard
AI Data Quality and Readiness Validation Standard
This standard sets the measurable data-quality requirements and the readiness sign-off gate that a dataset must satisfy before it is used to train, fine-tune, evaluate, or operate an AI system at scale. It owns the data-quality model, the measures and targets, and the data-use approval that the training-data governance procedure, the dataset datasheet, and the AI System Register reference.
- Type
- Standard
- Version
- 0.0.4
- Date
- 2026-09-13
- Owner
- AI Data Steward
- Approving authority
- Governance Library Maintainer
- Classification
- Public
- Confidentiality
- Public
- Category
- AI Governance
- Review frequency
- 6 to 12 months and upon material data, model, or regulatory change
- Licence
- CC BY-SA 4.0
Read the full text on GitHub (opens in a new tab)
Outline
- 1. Purpose
- 2. Applicability
- 3. Requirements
- 4. Evidence requirements
- 5. Framework alignment
- 6. Limitations
Frameworks it maps to
- ISO/IEC 5259-2:2024
- ISO/IEC 5259-3:2024
- ISO/IEC 5259-4:2024
- ISO/IEC 8183:2023
- ISO/IEC 42005:2025
- ISO 2859-1
- EU AI Act (2024)
- ISO/IEC 42001:2023
Related documents
- Training Data Governance Procedureai
- Dataset Datasheet Templateai
- AI System Register Templateai
- AI System Impact Assessment Procedureai
- AI Testing, Validation and Documentation Standardai
- AI Governance and Risk Frameworkai
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