ÖVE/ÖNORM EN ISO/IEC 5259-4

Issue date: 2025 09 15

Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 4: Data quality process framework (ISO/IEC 5259-4:2024)

This document establishes general common organizational approaches, regardless of the type, size or nature of the applying organization, to ensure data quality for training and evaluation in analytics and machine learning (ML). It includes guidance on the data quality process for: — supervised ML with regard to the labelling of data used for training ML systems, including common organizational approaches for training data labelling; — unsupervised ML; — semi-supervised ML; — reinforcement learning; — analytics. This document is applicable to training and evaluation data that come from different sources, including data acquisition and data composition, data preparation, data labelling, evaluation and data use. This document does not define specific services, platforms or tools.

General information on ÖVE/ÖNORM EN ISO/IEC 5259-4

Format

Digital | 40 Pages

Language

German | English | Download GER/ENG

Publisher

Austrian Standards International

Committee 001 Information technology

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ÖVE/ÖNORM EN ISO/IEC 5259-4 - Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 4: Data quality process framework (ISO/IEC 5259-4:2024)

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