A family of international standards that sets out how to define, measure, manage, and govern data quality for AI systems — from shared vocabulary to process and governance models.
A family of international standards that sets out how to define, measure, manage, and govern data quality for AI systems — from shared vocabulary to process and governance models.
ISO/IEC 5259 comprises five published or in-development parts, each addressing a distinct layer of data quality for AI: Part 1 (terminology and overview), Part 2 (data quality measures), Part 3 (data quality management requirements), Part 4 (data quality process framework), and Part 5 (data quality governance framework). The series provides the standards infrastructure needed to satisfy EU AI Act data governance requirements for high-risk systems, offering a coherent framework from vocabulary through operational processes to organisational governance. Parts align with and extend ISO/IEC 25000 (SQuaRE) quality concepts for AI-specific needs.
AI data governance programmes can use ISO/IEC 5259 as a comprehensive reference architecture, mapping each part to different governance layers from technical quality measurement to executive accountability frameworks.
Like the ISO 9000 series for quality management — a coherent family of standards addressing vocabulary, requirements, guidance, and specific techniques at different levels of detail.
A family of international standards that sets out how to define, measure, manage, and govern data quality for AI systems — from shared vocabulary to process and governance models.
ISO/IEC 5259 comprises five published or in-development parts, each addressing a distinct layer of data quality for AI: Part 1 (terminology and overview), Part 2 (data quality measures), Part 3 (data quality management requirements), Part 4 (data quality process framework), and Part 5 (data quality governance framework). The series provides the standards infrastructure needed to satisfy EU AI Act data governance requirements for high-risk systems, offering a coherent framework from vocabulary through operational processes to organisational governance. Parts align with and extend ISO/IEC 25000 (SQuaRE) quality concepts for AI-specific needs.
AI data governance programmes can use ISO/IEC 5259 as a comprehensive reference architecture, mapping each part to different governance layers from technical quality measurement to executive accountability frameworks.