ISO IEC 5259-5-2025 PDF

Full title and description

ISO/IEC 5259-5:2025 — Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 5: Data quality governance framework. This part provides a governance framework to enable governing bodies of organisations to direct and oversee implementation and operation of data quality measures, management and related processes with adequate controls throughout the data life cycle (DLC) in support of analytics and ML initiatives.

Abstract

ISO/IEC 5259-5:2025 defines roles, responsibilities and strategic-level controls for data quality governance so that senior management and boards can ensure data quality requirements are embedded, monitored and aligned with organisational objectives for analytics and ML. The document complements ISO/IEC 5259-1 and does not itself specify detailed management or process requirements (those are addressed in other parts of the 5259 series).

General information

• Status: Published.
• Publication date: February 12, 2025 (published February 2025).
• Publisher: Joint ISO/IEC publication (prepared by ISO/IEC JTC 1/SC 42 — Artificial Intelligence).
• ICS / categories: 35.020 (Information technology — Artificial intelligence).
• Edition / version: Edition 1.0, 2025-02.
• Number of pages: 15 pages (official ISO/IEC published pagination).

Scope

This document provides a governance-level framework for data quality in the context of analytics and machine learning. It is applicable to organisations of any size and sector that use analytics or ML and seeks to establish oversight, accountability and strategic controls across the data life cycle. It does not define detailed management-system or operational process requirements (these are covered in other parts of ISO/IEC 5259).

Key topics and requirements

• Establishing governance structures and accountable roles for data quality (boards, executive sponsors, data governors).
• Aligning data quality objectives with organisational strategy and risk appetite.
• Defining oversight mechanisms and reporting lines for data quality across the data life cycle.
• Setting metrics and performance indicators to monitor data quality for analytics and ML outcomes.
• Integrating controls, assurance and compliance checks relevant to analytics and ML deployments.
• Ensuring coordination between governance, management and operational process activities (complements ISO/IEC 5259-1, -3 and -4).

Typical use and users

Primary users are governing bodies, senior management, board members, data governance officers, chief data officers, compliance officers and other stakeholders responsible for strategic oversight of analytics and ML initiatives. Secondary users include data quality teams, ML program leads and auditors who implement or review governance arrangements. The standard is intended for organisations seeking to formalise accountability and oversight for data quality used in analytics and ML.

Related standards

ISO/IEC 5259-5 is part of the ISO/IEC 5259 series on data quality for analytics and ML. Related parts include ISO/IEC 5259-1 (concepts and lifecycle model), ISO/IEC 5259-3 (management requirements) and ISO/IEC 5259-4 (process requirements). It also aligns with other ISO/IEC JTC 1/SC 42 outputs on AI governance, risk and quality.

Keywords

data quality, governance, data governance, analytics, machine learning, ML, data life cycle, oversight, accountability, ISO/IEC 5259, AI governance.

FAQ

Q: What is this standard?

A: ISO/IEC 5259-5:2025 is an international standard that provides a governance framework for data quality specifically for analytics and machine learning (ML).

Q: What does it cover?

A: It covers strategic-level governance topics such as roles and responsibilities, oversight mechanisms, alignment with organisational objectives, and performance indicators for data quality across the data life cycle. It does not prescribe detailed management-system or operational process steps.

Q: Who typically uses it?

A: Governing bodies and senior management (boards, C-suite), data governance and quality leaders, chief data officers, compliance and risk managers, and others responsible for oversight of analytics and ML programs. Implementation teams and auditors also use it to interpret governance expectations.

Q: Is it current or superseded?

A: Current — ISO/IEC 5259-5 was published in February 2025 (Edition 1.0) and is the active international standard for data quality governance in the ISO/IEC 5259 series.

Q: Is it part of a series?

A: Yes — it is Part 5 of the ISO/IEC 5259 series on data quality for analytics and ML and is intended to be used alongside other parts (for example 5259-1, 5259-3 and 5259-4).

Q: What are the key keywords?

A: Data quality, governance, analytics, machine learning, data lifecycle, oversight, accountability, ISO/IEC 5259.