ISO/IEC 5259-3:2024 Artificial intelligence - Data quality for analytics and machine learning - Part 3: Data quality management requirements and guidelines
- Publisher: ISO
- Status:
final - Version:
1 - Certifiable: False
- Release Date:
2024-07 - Date Added:
2025-11-25 - Source URL: https://www.iso.org/standard/81092.html
Summary
This standard specifies requirements and provides guidance for establishing, implementing, maintaining and continually improving the quality of data used in analytics and machine learning. It does not define detailed processes, methods or metrics, but instead defines the requirements and guidance for a data quality management process (DQMS), including a reference process and methods that can be tailored to meet organizational needs.
Key Takeaways
- Provides a generic, organization-agnostic framework for a DQMS tailored to AI/ML data.
- Addresses horizontal and lifecycle-specific requirements — such as establishing a data quality culture, managing competence and resources, integrating with existing management systems, and documenting work products.
- Supports project-specific tailoring of data quality management, including identification of data quality claims, benchmark setting, and confirmation review of key work products.
Additional Sources
- ISO/IEC 5259-3: Enhance AI Performance with Quality Data — high-level description of the standard
Tags
data-quality, analytics, ml, machine-learning, governance