International IEC ISO Standard ISO/IEC5259-2 Artificial intelligence Data First edition 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 I'apprentissage automatique Partie 2: Mesure de la qualité des données Reference number ISO/IEC 5259-2:2024(en) @IS0/IEC 2024 IS0/IEC 5259-2:2024(en) COPYRIGHTPROTECTEDDOCUMENT IS0/IEC2024 All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may 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 Email: copyright@iso.org Website: www.iso.org Published in Switzerland @ IS0/IEC 2024- All rights reserved i IS0/IEC 5259-2:2024(en) Contents Page Foreword. V Introduction .vi 1 Scope. .1 2 Normative references .1 & Terms and definitions ..1 4 .5 Symbols and abbreviated terms. Data quality components and data quality models for analytics and machine learning ..5 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 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 quaity reporting. .28 8.1 Data quality reporting framework 28 8.2 Data quality measure information 29 8.3 Guidance to organizations 29 Annex A (informative) Design and document of a measurement function .30 Annex B (informative) UML model of data quality measure framework .32 Annex C (informative) Overview of data quality characteristics .33 Annex D (informative) Alternative groups of data quality characteristics .35 @ IS0/IEC 2024 - All rights reserved iii