SIST EN ISO/IEC 5259-1:2025
(Main)Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 1: Overview, terminology, and examples (ISO/IEC 5259-1:2024)
Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 1: Overview, terminology, and examples (ISO/IEC 5259-1:2024)
This document provides the means for understanding and associating the individual documents of the ISO/IEC 5259 series and is the foundation for conceptual understanding of data quality for analytics and machine learning. It also discusses associated technologies and examples (e.g. use cases and usage scenarios).
Künstliche Intelligenz - Datenqualität für Analytik und maschinelles Lernen (ML) - Teil 1: Überblick, Terminologie und Beispiele (ISO/IEC 5259-1:2024)
Intelligence artificielle - Qualité des données pour les analyses de données et l’apprentissage automatique - Partie 1: Vue d'ensemble, terminologie et exemples (ISO/IEC 5259-1:2024)
Umetna inteligenca - Kakovost podatkov za analizo in strojno učenje - 1. del: Pregled, terminologija in primeri (ISO/IEC 5259-1:2024)
General Information
Standards Content (Sample)
SLOVENSKI STANDARD
01-julij-2025
Umetna inteligenca - Kakovost podatkov za analizo in strojno učenje - 1. del:
Pregled, terminologija in primeri (ISO/IEC 5259-1:2024)
Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 1:
Overview, terminology, and examples (ISO/IEC 5259-1:2024)
Künstliche Intelligenz - Datenqualität für Analytik und maschinelles Lernen (ML) - Teil 1:
Überblick, Terminologie und Beispiele (ISO/IEC 5259-1:2024)
Intelligence artificielle - Qualité des données pour les analyses de données et
l’apprentissage automatique - Partie 1: Vue d'ensemble, terminologie et exemples
(ISO/IEC 5259-1:2024)
Ta slovenski standard je istoveten z: EN ISO/IEC 5259-1:2025
ICS:
01.040.35 Informacijska tehnologija. Information technology
(Slovarji) (Vocabularies)
35.020 Informacijska tehnika in Information technology (IT) in
tehnologija na splošno general
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.
EUROPEAN STANDARD EN ISO/IEC 5259-1
NORME EUROPÉENNE
EUROPÄISCHE NORM
May 2025
ICS 35.020; 01.040.35
English version
Artificial intelligence - Data quality for analytics and
machine learning (ML) - Part 1: Overview, terminology,
and examples (ISO/IEC 5259-1:2024)
Intelligence artificielle - Qualité des données pour les Künstliche Intelligenz - Datenqualität für Analytik und
analyses de données et l'apprentissage automatique - maschinelles Lernen (ML) - Teil 1: Überblick,
Partie 1: Vue d'ensemble, terminologie et exemples Terminologie und Beispiele (ISO/IEC 5259-1:2024)
(ISO/IEC 5259-1:2024)
This European Standard was approved by CEN on 18 May 2025.
CEN and CENELEC members are bound to comply with the CEN/CENELEC Internal Regulations which stipulate the conditions for
giving this European Standard the status of a national standard without any alteration. Up-to-date lists and bibliographical
references concerning such national standards may be obtained on application to the CEN-CENELEC Management Centre or to
any CEN and CENELEC member.
This European Standard exists in three official versions (English, French, German). A version in any other language made by
translation under the responsibility of a CEN and CENELEC member into its own language and notified to the CEN-CENELEC
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© 2025 CEN/CENELEC All rights of exploitation in any form and by any means
Ref. No. EN ISO/IEC 5259-1:2025 E
reserved worldwide for CEN national Members and for
CENELEC Members.
Contents Page
European foreword . 3
European foreword
The text of ISO/IEC 5259-1:2024 has been prepared by Technical Committee ISO/IEC JTC 1
"Information technology” of the International Organization for Standardization (ISO) and has been
taken over as EN ISO/IEC 5259-1:2025 by Technical Committee CEN-CENELEC/ JTC 21 “Artificial
Intelligence” the secretariat of which is held by DS.
This European Standard shall be given the status of a national standard, either by publication of an
identical text or by endorsement, at the latest by November 2025, and conflicting national standards
shall be withdrawn at the latest by November 2025.
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. CEN-CENELEC shall not be held responsible for identifying any or all such patent rights.
Any feedback and questions on this document should be directed to the users’ national standards body.
A complete listing of these bodies can be found on the CEN and CENELEC websites.
According to the CEN-CENELEC Internal Regulations, the national standards organizations of the
following countries are bound to implement this European Standard: Austria, Belgium, Bulgaria,
Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland,
Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Republic of
North Macedonia, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Türkiye and the
United Kingdom.
Endorsement notice
The text of ISO/IEC 5259-1:2024 has been approved by CEN-CENELEC as EN ISO/IEC 5259-1:2025
without any modification.
International
Standard
ISO/IEC 5259-1
First edition
Artificial intelligence — Data
2024-07
quality for analytics and machine
learning (ML) —
Part 1:
Overview, terminology, and
examples
Intelligence artificielle — Qualité des données pour les analyses
de données et l’apprentissage automatique —
Partie 1: Vue d'ensemble, terminologie et exemples
Reference number
ISO/IEC 5259-1:2024(en) © ISO/IEC 2024
ISO/IEC 5259-1:2024(en)
© ISO/IEC 2024
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting on
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or ISO’s member body in the country of the requester.
ISO copyright office
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Phone: +41 22 749 01 11
Email: copyright@iso.org
Website: www.iso.org
Published in Switzerland
© ISO/IEC 2024 – All rights reserved
ii
ISO/IEC 5259-1:2024(en)
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms. 5
5 Data quality concepts for analytics and machine learning . 5
5.1 Data quality considerations for analytics and machine learning .5
5.1.1 General .5
5.1.2 Machine learning and data quality .5
5.1.3 Data characteristics that pose quality challenges for analytics and machine
learning .6
5.1.4 Data sharing, data re-use and data quality for analytics and machine learning .6
5.2 Data quality concept framework for analytics and machine learning .6
5.2.1 Overview .6
5.2.2 Data quality management .7
5.2.3 Data quality governance .10
5.2.4 Data provenance .10
5.3 Data life cycle for analytics and ML .10
5.3.1 Overview .10
5.3.2 Data life cycle model .10
5.3.3 Processes across the multiple stages . 13
Annex A (informative) Examples and scenarios .15
Bibliography .18
© ISO/IEC 2024 – All rights reserved
iii
ISO/IEC 5259-1:2024(en)
Foreword
ISO (the International Organization for Standardization) and IEC (the International Electrotechnical
Commission) form the specialized system for worldwide standardization. National bodies that are
members of ISO or IEC participate in the development of International Standards through technical
committees established by the respective organization to deal with particular fields of technical activity.
ISO and IEC technical committees collaborate in fields of mutual interest. Other international organizations,
governmental and non-governmental, in liaison with ISO and IEC, also take part in the work.
The procedures used to develop this document and those intended for its further maintenance are described
in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the different types
of document should be noted. This document was drafted in accordance with the editorial rules of the ISO/
IEC Directives, Part 2 (see www.iso.org/directives or www.iec.ch/members_experts/refdocs).
ISO and IEC draw attention to the possibility that the implementation of this document may involve the
use of (a) patent(s). ISO and IEC take no position concerning the evidence, validity or applicability of any
claimed patent rights in respect thereof. As of the date of publication of this document, ISO and IEC had not
received notice of (a) patent(s) which may be required to implement this document. However, implementers
are cautioned that this may not represent the latest information, which may be obtained from the patent
database available at www.iso.org/patents and https://patents.iec.ch. ISO and IEC shall not be held
responsible for identifying any or all such patent rights.
Any trade name used in this document is information given for the convenience of users and does not
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For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and expressions
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In the IEC, see www.iec.ch/understanding-standards.
This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology,
Subcommittee SC 42, Artificial intelligence.
A list of all parts in the ISO/IEC 5259 series can be found on the ISO and IEC websites.
Any feedback or questions on this document should be directed to the user’s national standards
body. A complete listing of these bodies can be found at www.iso.org/members.html and
www.iec.ch/national-committees.
© ISO/IEC 2024 – All rights reserved
iv
ISO/IEC 5259-1:2024(en)
Introduction
Data are the raw material for analytics and machine learning (ML) and data quality is a critical aspect for
related analytics and ML projects and systems. The aim of the ISO/IEC 5259 series is to provide tools and
methods to assess and improve the quality of data used for analytics and ML.
Other parts of the ISO/IEC 5259 series include:
1)
— ISO/IEC 5259-2 provides a data quality model, data quality measures and guidance on rep
...
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