The governance part of ISO/IEC 5259 — specifying how an organisation should structure its leadership, roles, and oversight to ensure data quality is treated as an enterprise-level responsibility.
The governance part of ISO/IEC 5259 — specifying how an organisation should structure its leadership, roles, and oversight to ensure data quality is treated as an enterprise-level responsibility.
ISO/IEC 5259-5 addresses the governance layer above the management system (Part 3) and operational processes (Part 4). It defines data quality governance objectives, organisational structures (data quality councils, steering committees), role responsibilities (data owners, stewards, custodians), policy hierarchies, and performance reporting for executive accountability. It aligns with ISO/IEC 38507 (governance of AI by organisations) by providing the data-quality-specific governance layer needed for responsible AI at scale. Organisations implementing this part create institutional accountability for data quality alongside technical and process controls.
Chief Data Officers and AI governance leads can use Part 5 to establish the institutional accountability structures that make data quality a board-level concern rather than solely a technical engineering challenge.
Like corporate governance standards for financial reporting — defining the board committees, executive roles, and reporting lines that make financial quality an organisational responsibility rather than just an accounting department concern.
The governance part of ISO/IEC 5259 — specifying how an organisation should structure its leadership, roles, and oversight to ensure data quality is treated as an enterprise-level responsibility.
ISO/IEC 5259-5 addresses the governance layer above the management system (Part 3) and operational processes (Part 4). It defines data quality governance objectives, organisational structures (data quality councils, steering committees), role responsibilities (data owners, stewards, custodians), policy hierarchies, and performance reporting for executive accountability. It aligns with ISO/IEC 38507 (governance of AI by organisations) by providing the data-quality-specific governance layer needed for responsible AI at scale. Organisations implementing this part create institutional accountability for data quality alongside technical and process controls.
Chief Data Officers and AI governance leads can use Part 5 to establish the institutional accountability structures that make data quality a board-level concern rather than solely a technical engineering challenge.