ISO/IEC 5259-2:2024
2024-11
What is ISO/IEC 5259-2?
ISO/IEC 5259-2 defines a data quality model and a set of measurable characteristics to help organisations assess and report on data quality in the context of analytics and machine learning (ML). It builds on existing standards (such as ISO/IEC 25012 and ISO 8000) and provides a common foundation for ensuring that data used in AI and analytics processes is trustworthy and fit for purpose.
Why is ISO/IEC 5259-2 important?
Poor data quality can distort analytics, bias machine learning models and compromise decision-making. With data increasingly sourced from both structured and unstructured origins, organisations need standardised ways to evaluate and ensure quality across the entire data lifecycle. ISO/IEC 5259-2 equips teams with consistent criteria and practical guidance to manage data quality, ultimately supporting the creation of more reliable, safe and effective AI systems.
Benefits
- Provides measurable indicators for assessing data quality
- Improves the reliability and safety of ML models and analytics
- Supports transparent and standardised data quality reporting
- Enables organisations to meet their data quality objectives
- Aligns with broader AI and data governance frameworks
FAQ
Any organisation that develops or uses data for analytics or machine learning and wants to ensure that data quality is systematically assessed and reported.
ISO/IEC 5259-1 establishes the foundational framework and terminology, while 5259-2 focuses specifically on defining and measuring data quality characteristics.
Yes. It supports both structured (e.g. databases) and unstructured data (e.g. text, images, audio) commonly used in analytics and AI development.
Buy together
AI data quality management bundle
Ensure high-quality data for analytics and machine learning with our comprehensive ISO/IEC 5259 standards bundle.
- ISO 5259-1:2024
- IEC 5259-2:2024
- IEC 5259-3:2024
- IEC 5259-4:2024
- IEC 5259-5:2024
General information
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Status: PublishedPublication date: 2024-11Stage: International Standard published [60.60]
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Edition: 1Number of pages: 38
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Technical Committee :ISO/IEC JTC 1/SC 42ICS :35.020
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