prEN 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) prEN ISO/IEC 5259-4

General information

40.10 harmonizedStageCodeLabel.40.10   Nov 23, 2024

CEN/CENELEC

CEN/CLC/JTC 21

European Norm

35.020   Information technology (IT) in general

Scope

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.

Life cycle

NOW

IN_DEVELOPMENT
prEN ISO/IEC 5259-4
40.10 harmonizedStageCodeLabel.40.10
Nov 23, 2024

Relations

Adopted from ISO/IEC 5259-4:2024 IDENTICAL