ISO/IEC 5259-3:2024

Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 3: Data quality management requirements and guidelines

This document specifies requirements and provides guidance for establishing, implementing, maintaining and continually improving the quality of data used in the areas of analytics and machine learning. This document does not define a detailed process, methods or metrics. Rather it defines the requirements and guidance for a quality management process along with a reference process and methods that can be tailored to meet the requirements in this document. The requirements and recommendations set out in this document are generic and are intended to be applicable to all organizations, regardless of type, size or nature.

Intelligence artificielle — Qualité des données pour les analyses de données et l’apprentissage automatique — Partie 3: Exigences et lignes directrices pour la gestion de la qualité des données

General Information

• Status: Published
• Publication Date: 01-Jul-2024
• ICS: 35.020 - Information technology (IT) in general
• Technical Committee: ISO/IEC JTC 1/SC 42 - Artificial intelligence
• Drafting Committee: ISO/IEC JTC 1/SC 42/WG 2 - Data
• Current Stage: 6060 - International Standard published
• Start Date: 02-Jul-2024
• Due Date: 30-Apr-2024
• Completion Date: 02-Jul-2024

Standards Content (Sample)

International
Standard
ISO/IEC 5259-3
First edition
Artificial intelligence — Data
2024-07
quality for analytics and machine
learning (ML) —
Part 3:
Data quality management
requirements and guidelines
Intelligence artificielle — Qualité des données pour les analyses
de données et l’apprentissage automatique —
Partie 3: Exigences et lignes directrices pour la gestion de la
qualité des données
Reference number
© 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
Contents Page
Foreword .v
Introduction .vi
1 Scope .1
2 Normative references .1
3 Terms and definitions .1
4 Symbols and abbreviated terms. 2
5 Intended usage . 2
6 Overall data quality management . 2
6.1 Objective.2
6.2 General .2
6.3 Requirements and recommendations .3
6.3.1 General .3
6.3.2 Data quality culture . .3
6.3.3 Management of data quality issues . .3
6.3.4 Competence management .3
6.3.5 Resource management .4
6.3.6 Management system integration .4
6.3.7 Documentation.4
6.3.8 Data quality audit and assessment.4
6.3.9 Confirmation review and data quality measures .5
6.3.10 Project-specific data quality management .5
6.4 Work products .5
7 Life cycle-specific data quality management .6
7.1 Objective.6
7.2 General .6
7.2.1 Data quality management life cycle .6
7.2.2 Data quality management life cycle stages .7
7.2.3 Project-independent tailoring of the data quality management life cycle .8
7.2.4 Horizontal aspects of the data quality management life cycle .8
7.3 Requirements and recommendations .9
7.3.1 Data motivation and conceptualization . .9
7.3.2 Data specification .9
7.3.3 Data planning .11
7.3.4 Data acquisition . . .11
7.3.5 Data preprocessing . 13
7.3.6 Data augmentation . 13
7.3.7 Data provisioning .14
7.3.8 Data decommissioning .16
7.4 Work products .17
7.4.1 Work products of data motivation and conceptualization stage .17
7.4.2 Work products of data specification stage .17
7.4.3 Work products of data planning stage .17
7.4.4 Work products of data acquisition stage .17
7.4.5 Work products of data preprocessing stage .17
7.4.6 Work products of data augmentation stage .18
7.4.7 Work products of data provisioning stage .18
7.4.8 Work products of data decommissioning stage .18
8 Horizontal processes .18
8.1 Objective.18
8.2 General .18
8.3 Requirements and recommendations .18
8.3.1 Verification and validation .18

© ISO/IEC 2024 – All rights reserved
iii
8.3.2 Configuration management .19
8.3.3 Change management .19
8.3.4 Risk management . 20
8.4 Work products .21
8.4.1 Work products of verification and validation .21
8.4.2 Work products of configuration management .21
8.4.3 Work products of change management.21
8.4.4 Work products for risk management .21
9 Management of data quality in supply chains .22
9.1 Objective. 22
9.2 Requirements and recommendations . 22
9.3 Work products . 22
10 Management of data processing tools .23
10.1 Objective. 23
10.2 Requirements and recommendations . 23
10.3 Work products . 23
11 Management of data quality dependencies .23
11.1 Objective. 23
11.2 Requirements and recommendations . 23
11.3 Work products .
...

FINAL DRAFT
International
Standard
ISO/IEC FDIS
5259-3
ISO/IEC JTC 1/SC 42
Artificial intelligence — Data
Secretariat: ANSI
quality for analytics and machine
Voting begins on:
learning (ML) —
2024-04-01
Part 3:
Voting terminates on:
2024-05-27
Data quality management
requirements and guidelines
RECIPIENTS OF THIS DRAFT ARE INVITED TO SUBMIT,
WITH THEIR COMMENTS, NOTIFICATION OF ANY
RELEVANT PATENT RIGHTS OF WHICH THEY ARE AWARE
AND TO PROVIDE SUPPOR TING DOCUMENTATION.
IN ADDITION TO THEIR EVALUATION AS
BEING ACCEPTABLE FOR INDUSTRIAL, TECHNO­
LOGICAL, COMMERCIAL AND USER PURPOSES, DRAFT
INTERNATIONAL STANDARDS MAY ON OCCASION HAVE
TO BE CONSIDERED IN THE LIGHT OF THEIR POTENTIAL
TO BECOME STAN DARDS TO WHICH REFERENCE MAY BE
MADE IN NATIONAL REGULATIONS.
Reference number
ISO/IEC FDIS 5259­3:2024(en) © ISO/IEC 2024

FINAL DRAFT
ISO/IEC FDIS 5259-3:2024(en)
International
Standard
ISO/IEC FDIS
5259-3
ISO/IEC JTC 1/SC 42
Artificial intelligence — Data
Secretariat: ANSI
quality for analytics and machine
Voting begins on:
learning (ML) —
Part 3:
Voting terminates on:
Data quality management
requirements and guidelines
RECIPIENTS OF THIS DRAFT ARE INVITED TO SUBMIT,
WITH THEIR COMMENTS, NOTIFICATION OF ANY
RELEVANT PATENT RIGHTS OF WHICH THEY ARE AWARE
AND TO PROVIDE SUPPOR TING DOCUMENTATION.
© ISO/IEC 2024
IN ADDITION TO THEIR EVALUATION AS
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
BEING ACCEPTABLE FOR INDUSTRIAL, TECHNO­
LOGICAL, COMMERCIAL AND USER PURPOSES, DRAFT
be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting on
INTERNATIONAL STANDARDS MAY ON OCCASION HAVE
the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address below
TO BE CONSIDERED IN THE LIGHT OF THEIR POTENTIAL
or ISO’s member body in the country of the requester.
TO BECOME STAN DARDS TO WHICH REFERENCE MAY BE
MADE IN NATIONAL REGULATIONS.
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 Reference number
ISO/IEC FDIS 5259­3:2024(en) © ISO/IEC 2024

© ISO/IEC 2024 – All rights reserved
ii
ISO/IEC FDIS 5259-3:2024(en)
Contents Page
Foreword .v
Introduction .vi
1 Scope .1
2 Normative references .1
3 Terms and definitions .1
4 Symbols and abbreviated terms. 2
5 Intended usage . 2
6 Overall data quality management . 2
6.1 Objective.2
6.2 General .2
6.3 Requirements and recommendations .2
6.3.1 General .2
6.3.2 Data quality culture . .3
6.3.3 Management of data quality issues . .3
6.3.4 Competence management .3
6.3.5 Resource management .3
6.3.6 Management system integration .4
6.3.7 Documentation.4
6.3.8 Data quality audit and assessment.4
6.3.9 Confirmation review and data quality measures .5
6.3.10 Project-specific data quality management .5
6.4 Work products .5
7 Life cycle-specific data quality management . 5
7.1 Objective.5
7.2 General .6
7.2.1 Data quality management life cycle .6
7.2.2 Data quality management life cycle stages .7
7.2.3 Project-independent tailoring of the data quality management life cycle .8
7.2.4 Horizontal aspects of the data quality management life cycle .8
7.3 Requirements and recommendations .9
7.3.1 Data motivation and conceptualization . .9
7.3.2 Data specification .9
7.3.3 Data planning .11
7.3.4 Data acquisition . . .11
7.3.5 Data preprocessing . 13
7.3.6 Data augmentation . 13
7.3.7 Data provisioning .14
7.3.8 Data decommissioning .16
7.4 Work products .17
7.4.1 Work products of data motivation and conceptualization stage .17
7.4.2 Work products of data specification stage .17
7.4.3 Work products of data planning stage .17
7.4.4 Work products of data acquisition stage .17
7.4.5 Work products of data preprocessing stage .17
7.4.6 Work products of data augmentation stage .18
7.4.7 Work products of data provisioning stage .18
7.4.8 Work products of data decommissioning stage .18
8 Horizontal processes .18
8.1 Objective.18
8.2 General .18
8.3 Requirements and recommendations .18
8.3.1 Verification and validation .18

© ISO/IEC 2024 – All rights reserved
iii
ISO/IEC FDIS 5259-3:2024(en)
8.3.2 Configuration management .19
8.3.3 Change management .19
8.3.4 Risk management . 20
8.4 Work products .21
8.4.1 Work products of verification and validation .21
8.4.2 Work products of configuration management .21
8.4.3 Work products of change management.21
8.4.4 Work products for risk management .21
9 Management of data quality in supply chains .22
9.1 Objective. 22
9.2 Requirements and recommendations . 22
9.3 Work products . 22
10 Management of data processing tools .23
10.1 Objective.
...

ISO/IEC FDIS 5259-3:20##(X)
ISO/IEC JTC 1/SC 42/WG 2
Secretariat: ANSI
Date: 2024-03-15
Artificial intelligence — Data quality for analytics and machine
learning (ML) — —
Part 3:
Data quality management requirements and guidelines

FDIS stage
Warning for WDs and CDs
This document is not an ISO International Standard. It is distributed for review and comment. It is subject to change
without notice and may not be referred to as an International Standard.
© ISO/IEC 202X – All rights reserved

ISO #####-#:####(X)
Recipients of this draft are invited to submit, with their comments, notification of any relevant patent rights of which
they are aware and to provide supporting documentation.
2 © ISO #### – All rights reserved

© ISO/IEC – All rights reserved
ISO/IEC CDFDIS 5259-3:202X(X2024(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: + 41 22 749 01 11
Fax: [phone]
EmailE-mail: [e-mail]
Website: www.iso.orgwww.iso.org
Published in Switzerland
iv © ISO/IEC 202X 2024 – All rights reserved

iv
ISO/IEC FDIS 5259-3:202X(X2024(en)
Contents
Foreword . viii
Introduction . ix
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms . 2
5 Intended usage . 2
6 Overall data quality management . 2
6.1 Objective . 2
6.2 General . 3
6.3 Requirements and recommendations . 3
6.3.1 General . 3
6.3.2 Data quality culture . 3
6.3.3 Management of data quality issues . 3
6.3.4 Competence management . 3
6.3.5 Resource management . 4
6.3.6 Management system integration . 4
6.3.7 Documentation . 4
6.3.8 Data quality audit and assessment . 4
6.3.9 Confirmation review and data quality measures . 5
6.3.10 Project-specific data quality management . 5
6.4 Work products . 6
7 Life cycle-specific data quality management . 6
7.1 Objective . 6
7.2 General . 6
7.2.1 Data quality management life cycle . 6
7.2.2 Data quality management life cycle stages . 8
7.2.3 Project-independent tailoring of the data quality management life cycle . 9
7.2.4 Horizontal aspects of the data quality management life cycle . 9
7.3 Requirements and recommendations . 10
7.3.1 Data motivation and conceptualization . 10
7.3.2 Data specification . 11
7.3.3 Data planning . 12
7.3.4 Data acquisition . 13
7.3.5 Data preprocessing . 15
7.3.6 Data augmentation . 15
7.3.7 Data provisioning . 16
© ISO/IEC 202X 2024 – All rights reserved

v
ISO/IEC CDFDIS 5259-3:202X(X2024(en)
7.3.8 Data decommissioning . 18
7.4 Work products . 19
7.4.1 Work products of data motivation and conceptualization stage . 19
7.4.2 Work products of data specification stage . 19
7.4.3 Work products of data planning stage . 19
7.4.4 Work products of data acquisition stage . 20
7.4.5 Work products of data preprocessing stage . 20
7.4.6 Work products of data augmentation stage . 20
7.4.7 Work products of data provisioning stage . 20
7.4.8 Work products of data decommissioning stage . 20
8 Horizontal processes . 21
8.1 Objective . 21
8.2 General . 21
8.3 Requirements and recommendations . 21
8.3.1 Verification and validation . 21
8.3.2 Configuration management . 21
8.3.3 Change management . 22
8.3.4 Risk management . 23
8.4 Work products . 23
8.4.1 Work products of verification and validation . 23
8.4.2 Work products of configuration management . 24
8.4.3 Work products of change management . 24
8.4.4 Work products for risk management . 24
9 Management of data quality in supply chains . 24
9.1 Objective . 24
9.2 Requirements and recommendations . 24
9.3 Work products . 25
10 Management of data processing tools . 25
10.1 Objective . 25
10.2 Requirements and recommendations . 25
10.3 Work products . 26
11 Management of data quality dependencies . 26
11.1 Objective . 26
11.2 Requirements and recommendations . 26
11.3 Work products . 26
12 Project-specific da
...