SIST EN ISO/IEC 5259-2:2025

Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 2: Data quality measures (ISO/IEC 5259-2:2024)

This document specifies a data quality model, data quality measures and guidance on reporting data quality in the context of analytics and machine learning (ML).
This document is applicable to all types of organizations who want to achieve their data quality objectives.

Künstliche Intelligenz - Datenqualität für Analytik und maschinelles Lernen (ML) - Teil 2: Datenqualitätsmaßnahmen (ISO/IEC 5259-2:2024)

Intelligence artificielle - Qualité des données pour les analyses de données et l’apprentissage automatique - Partie 2: Mesure de la qualité des données (ISO/IEC 5259-2:2024)

Le présent document spécifie un modèle de qualité des données, des mesures de la qualité des données et des recommandations concernant l’établissement de rapports sur la qualité des données dans le contexte de l’analyse de données et de l’apprentissage automatique (AA).
Le présent document s’applique à tous les types d’organismes qui souhaitent atteindre leurs objectifs de qualité des données.

Umetna inteligenca - Kakovost podatkov za analizo in strojno učenje - 2. del: Merjenja kakovosti podatkov (ISO/IEC 5259-2:2024)

General Information

• Status: Published
• Public Enquiry End Date: 15-Apr-2025
• Publication Date: 16-Jun-2025
• ICS: 35.020 - Information technology (IT) in general
• Technical Committee: UMI - Artificial intelligence
• Current Stage: 6060 - National Implementation/Publication (Adopted Project)
• Start Date: 29-May-2025
• Due Date: 03-Aug-2025
• Completion Date: 17-Jun-2025
• Ref Project: EN ISO/IEC 5259-2:2025 - Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 2: Data quality measures (ISO/IEC 5259-2:2024)

Standards Content (Sample)

SLOVENSKI STANDARD
01-julij-2025
Umetna inteligenca - Kakovost podatkov za analizo in strojno učenje - 2. del:
Merjenja kakovosti podatkov (ISO/IEC 5259-2:2024)
Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 2: Data
quality measures (ISO/IEC 5259-2:2024)
Künstliche Intelligenz - Datenqualität für Analytik und maschinelles Lernen (ML) - Teil 2:
Datenqualitätsmaßnahmen (ISO/IEC 5259-2:2024)
Intelligence artificielle - Qualité des données pour les analyses de données et
l’apprentissage automatique - Partie 2: Mesure de la qualité des données (ISO/IEC 5259
-2:2024)
Ta slovenski standard je istoveten z: EN ISO/IEC 5259-2:2025
ICS:
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 5259-2

NORME EUROPÉENNE
EUROPÄISCHE NORM
May 2025
ICS 35.020
English version
Artificial intelligence - Data quality for analytics and
machine learning (ML) - Part 2: Data quality measures
(ISO/IEC 5259-2:2024)
Intelligence artificielle - Qualité des données pour les Künstliche Intelligenz - Datenqualität für Analytik und
analyses de données et l'apprentissage automatique - maschinelles Lernen (ML) - Teil 2:
Partie 2: Mesure de la qualité des données (ISO/IEC Datenqualitätsmaßnahmen (ISO/IEC 5259-2:2024)
5259-2:2024)
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
Management Centre has the same status as the official versions.

CEN and CENELEC members are the national standards bodies and national electrotechnical committees of 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 United Kingdom.

CEN-CENELEC Management Centre:
Rue de la Science 23, B-1040 Brussels
© 2025 CEN/CENELEC All rights of exploitation in any form and by any means
Ref. No. EN ISO/IEC 5259-2:2025 E
reserved worldwide for CEN national Members and for
CENELEC Members.
Contents Page
European foreword . 3

European foreword
The text of ISO/IEC 5259-2:2024 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 5259-2:2025 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 5259-2:2024 has been approved by CEN-CENELEC as EN ISO/IEC 5259-2:2025
without any modification.
International
Standard
ISO/IEC 5259-2
First edition
Artificial intelligence — Data
2024-11
quality for analytics and machine
learning (ML) —
Part 2:
Data quality measures
Intelligence artificielle — Qualité des données pour les analyses
de données et l’apprentissage automatique —
Partie 2: Mesure de la qualité des données
Reference number
ISO/IEC 5259-2:2024(en) © ISO/IEC 2024

ISO/IEC 5259-2:2024(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
the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address below
or ISO’s member body in the country of the requester.
ISO copyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: [phone]
Email: [e-mail]
Website: www.iso.org
Published in Switzerland
© ISO/IEC 2024 – All rights reserved
ii
ISO/IEC 5259-2:2024(en)
Contents Page
Foreword .v
Introduction .vi
1 Scope .1
2 Normative references .1
3 Terms and definitions .1
4 Symbols and abbreviated terms. 5
5 Data quality components and data quality models for analytics and machine learning . 5
5.1 Data quality components in data life cycle .5
5.2 Data quality model .6
6 Data quality characteristics and quality measures .8
6.1 General .8
6.2 Inherent data quality characteristics .9
6.2.1 Accuracy .9
6.2.2 Completeness .10
6.2.3 Consistency . 12
6.2.4 Credibility . 13
6.2.5 Currentness .14
6.3 Inherent and system-dependent data quality characteristics . 15
6.3.1 Accessibility . 15
6.3.2 Compliance . 15
6.3.3 Efficiency .16
6.3.4 Precision .16
6.3.5 Traceability .17
6.3.6 Understandability .17
6.4 System-dependent data quality characteristics .18
6.4.1 Availability .18
6.4.2 Portability .18
6.4.3 Recoverability .19
6.5 Additional data quality characteristics .19
6.5.1 Auditability.19
6.5.2 Balance . 20
6.5.3 Diversity . . 22
6.5.4 Effectiveness . 23
6.5.5 Identifiability .24
6.5.6 Relevance . 25
6.5.7 Representativeness . 25
6.5.8 Similarity . . . 26
6.5.9 Timeliness .27
7 Implementing a data quality model and data quality measures for an analytics or ML
task .28
8 Data quality reporting .
...