Data quality — Part 51: Data governance: Exchange of data policy statements

This document specifies requirements that support the exchange of data governance policy statements and automated conformance testing of data sets to the data specifications referenced by policy statements. The following are within the scope of this document: — requirements for the syntax and semantics of identifiers for organizations issuing data governance policy statements; — requirements for the syntax and semantics of identifiers for data governance policy statements; — data specifications referenced by data governance policy statements, where those specifications are computer processable. The following are outside the scope of this document: — general processes, roles and responsibilities for performing data governance; EXAMPLE An approach to data governance is covered by ISO/IEC 38505-1 and ISO/IEC TR 38505-2. — requirements for the syntax and semantics of data specifications referenced by a data governance policy statement; — requirements for the syntax and semantics of data governance policy statements; — methods used for the creation of data governance policy statements; — methods used for measuring conformance with the requirements referenced by data governance policy statements; — methods used for monitoring conformance with the requirements referenced by data governance policy statements.

Qualité des données — Partie 51: Titre manque

General Information

Status
Published
Publication Date
14-Mar-2023
Current Stage
6060 - International Standard published
Start Date
15-Mar-2023
Due Date
22-Aug-2023
Completion Date
15-Mar-2023
Ref Project

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INTERNATIONAL ISO
STANDARD 8000-51
First edition
2023-03
Data quality —
Part 51:
Data governance: Exchange of data
policy statements
Reference number
ISO 8000-51:2023(E)
© ISO 2023

---------------------- Page: 1 ----------------------
ISO 8000-51:2023(E)
COPYRIGHT PROTECTED DOCUMENT
© ISO 2023
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
Email: copyright@iso.org
Website: www.iso.org
Published in Switzerland
ii
  © ISO 2023 – All rights reserved

---------------------- Page: 2 ----------------------
ISO 8000-51:2023(E)
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 2
4 Fundamental principles and assumptions . 2
5 Requirements for representing data governance policy statements .2
6 Conformance . 3
Annex A (informative) Document identification . 4
Annex B (informative) Example of a data governance policy register . 5
Bibliography . 8
iii
© ISO 2023 – All rights reserved

---------------------- Page: 3 ----------------------
ISO 8000-51:2023(E)
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
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 ISO documents 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).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www.iso.org/patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to
the World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT), see
www.iso.org/iso/foreword.html.
This document was prepared by Technical Committee ISO/TC 184, Automation systems and integration,
Subcommittee SC 4 Industrial data.
A list of all parts in the ISO 8000 series can be found on the ISO website.
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.
iv
  © ISO 2023 – All rights reserved

---------------------- Page: 4 ----------------------
ISO 8000-51:2023(E)
Introduction
0.1  Foundations of the ISO 8000 series
Digital data deliver value by enhancing all aspects of organizational performance including:
— operational effectiveness and efficiency;
— safety and security;
— reputation with customers and the wider public;
— compliance with statutory regulations;
— innovation;
— consumer costs, revenues and stock prices.
In addition, many organizations are now addressing these considerations with reference to the United
1)
Nations Sustainable Development Goals .
The influence on performance originates from data being the formalized representation of
2)
information . This information enables organizations to make reliable decisions. This decision making
can be performed by human beings directly and also by automated data processing including artificial
intelligence systems.
Through widespread adoption of digital computing and associated communication technologies,
organizations become dependent on digital data. This dependency amplifies the negative consequences
of lack of quality in these data. These consequences are the decrease of organizational performance.
The biggest impact of digital data comes from two key factors:
— the data having a structure that reflects the nature of the subject matter;
EXAMPLE 1 A research scientist writes a report using a software application for word processing. This report
includes a table that uses a clear, logical layout to show results from an experiment. These results indicate how
material properties vary with temperature. The report is read by a designer, who uses the results to create a
product that works in a range of different operating temperatures.
— the data being computer processable (machine readable) rather than just being for a person to read
and understand.
EXAMPLE 2 A research scientist uses a database system to store the results of experiments on a material.
This system controls the format of different values in the data set. The system generates an output file of digital
data. This file is processed by a software application for engineering analysis. The application determines the
optimum geometry when using the material to make a product.
ISO 9000 explains that quality is not an abstract concept of absolute perfection. Quality is actually
the conformance of characteristics to requirements. This actuality means that any item of data can
be of high quality for one purpose but not for a different purpose. The quality is different because the
requirements are different between the two purposes.
EXAMPLE 3 Time data are processed by calendar applications and also by control systems for propulsion
units on spacecraft. These data include start times for meetings in a calendar application and activation times in
a control system. These start times require less precision than the activation times.
1) https://sdgs.un.org/goals
2) ISO 8000-2 defines information as “knowledge concerning objects, such as facts, events, things, processes, or
ideas, including concepts, that within a certain context has a particular meaning”.
v
© ISO 2023 – All rights reserved

---------------------- Page: 5 ----------------------
ISO 8000-51:2023(E)
The nature of digital data is fundamental to establishing requirements that are relevant to the specific
decisions that are made by each organization.
EXAMPLE 4 ISO 8000-1 identifies that data have syntactic (format), semantic (meaning) and pragmatic
(usefulness) characteristics.
To support the delivery of high-quality data, the ISO 8000 series addresses:
— data governance, data quality management and maturity assessment;
EXAMPLE 5 ISO 8000-61 specifies a process reference model for data quality management.
— creating and applying requirements for data and information;
EXAMPLE 6 ISO 8000-110 specifies how to exchange characteristic data that are master data.
— monitoring and measuring information and data quality;
EXAMPLE 7 ISO 8000-8 specifies approaches to measuring information and data quality.
— improving data and, consequently, information quality;
EXAMPLE 8 ISO/TS 8000-81 specifies an approach to data profiling, which identifies opportunities to improve
data quality.
— issues that are specific to the type of content in a data set.
EXAMPLE 9 ISO/TS 8000-311 specifies how to address quality considerations for product shape data.
Data quality management covers all aspects of data processing, including creating, collecting, storing,
maintaining, transferring, exploiting and presenting data to deliver information.
Effective data quality management is systemic and systematic, requiring an understanding of the
root causes of data quality issues. This understanding is the basis for not just correcting existing
nonconformities but for also implementing solutions that prevent future reoccurrence of those
nonconformities.
EXAMPLE 10 If a data set includes dates in multiple formats including “yyyy-mm-dd”, “mm-dd-yy” and
“dd-mm-yy”, then data cleansing can correct the consistency of the values. Such cleansing requires additional
information, however, to resolve ambiguous entries (such as, “04-05-20”). The cleansing also cannot address any
process issues and people issues, including training, that have caused the inconsistency.
0.2  Understanding more about the ISO 8000 series
ISO 8000-1 provides a detailed explanation of the structure and scope of the whole ISO 8000 series.
3)
ISO 8000-2 specifies the single, common vocabulary for the ISO 8000 series. This vocabulary is ideal
reading material by which to understand the overall subject matter of data quality. ISO 8000-2 presents
the vocabulary structured by a series of topic areas (for example, terms relating to quality and terms
relating to data and information).
4)
ISO has identified ISO 8000-1, ISO 8000-2 and ISO 8000-8 as horizontal deliverables .
0.3  Role of this document
As a contribution to this overall capability of the ISO 8000 series, this document enables organizations
to exchange data policy statements. These statements are the core output from data governance. This
output supports organizations to achieve availability, usability, integrity and security of data. The
policies affect the practical implementation of creating, managing and using data sets.
3) The content is available on the ISO Online Browsing Platform. https://www.iso.org/obp
4) Deliverable dealing with a subject relevant to a number of committees or sectors or of crucial importance to
ensure coherence across standardization deliverables.
vi
  © ISO 2023 – All rights reserved

---------------------- Page: 6 ----------------------
ISO 8000-51:2023(E)
An organization appoints a data governance authority to be responsible for developing and enforcing
the policies relating to the management of data.
To ensure the effect of these policies, organizations can decide each data governance policy statement:
a) is recorded by a data governance policy register (see Annex B);
b) has a reference;
c) specifies the requirements applicable to a data set in a specification that conforms with
ISO/TS 22745-30;
d) identifies the domain of application;
e) describes how to measure and monitor conformance with the requirements specified by the policy.
Software applications are available to assist organizations in the creation and management of data
governance policies. These organizations can significantly reduce the cost of implementing data
governance by creating data governance policy statements that are portable. Such statements can be
reliably interpreted by multiple applications, contributing to improved data and informatio
...

Deleted: © ISO 2022 – All rights reserved
ISO/PRF 8000-51
Deleted: 2022-09-07¶
Deleted: :2022(E)
ISO/TC 184/SC 4
Deleted: /WG 13
Secretariat: ANSI
Date: 2023-01-17
Data quality —
Part 51:
Data governance: Exchange of data policy statements
FDIS stage
© ISO 2023 – All rights reserved

---------------------- Page: 1 ----------------------
ISO/PRF 8000-51:2023(E)
Deleted: 2022
© ISO 2023
Deleted: 2022
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
E-mail: copyright@iso.org
Deleted: Fax: +41 22 749 09 47¶
Website: www.iso.org
Email
Published in Switzerland
Deleted: 2022
ii © ISO 2023 – All rights reserved

---------------------- Page: 2 ----------------------
ISO/PRF 8000-51:2023(E)
Deleted: 2022


Deleted: 2022
© ISO 2023 – All rights reserved iii

---------------------- Page: 3 ----------------------
ISO/PRF 8000-51:2023(E)
Deleted: 2022
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work. ISO
collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
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 ISO documents 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).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of any
patent rights identified during the development of the document will be in the Introduction and/or on
the ISO list of patent declarations received (see www.iso.org/patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to the World
Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT), see
www.iso.org/iso/foreword.html.
This document was prepared by Technical Committee ISO/TC 184, Automation systems and integration,
Subcommittee SC 4 Industrial data.
A list of all parts in the ISO 8000 series can be found on the ISO website.
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.
Field Code Changed
Deleted: 2022
iv © ISO 2023 – All rights reserved

---------------------- Page: 4 ----------------------
ISO/PRF 8000-51:2023(E)
Deleted: 2022
Introduction
0.1  Foundations of the ISO 8000 series
Digital data deliver value by enhancing all aspects of organizational performance including:
— operational effectiveness and efficiency;
Deleted: —
— safety and security;
Deleted: —
— reputation with customers and the wider public;
Deleted: —
— compliance with statutory regulations;
Deleted: —
— innovation;
Deleted: —
— consumer costs, revenues and stock prices.
Deleted: —
In addition, many organizations are now addressing these considerations with reference to the United
1
Nations Sustainable Development Goals .
2
The influence on performance originates from data being the formalized representation of information .
This information enables organizations to make reliable decisions. This decision making can be
performed by human beings directly and also by automated data processing including artificial
intelligence systems.
Through widespread adoption of digital computing and associated communication technologies,
organizations become dependent on digital data. This dependency amplifies the negative consequences
of lack of quality in these data. These consequences are the decrease of organizational performance.
The biggest impact of digital data comes from two key factors:
— the data having a structure that reflects the nature of the subject matter;
Deleted: —
EXAMPLE 1 A research scientist writes a report using a software application for word processing. This report
includes a table that uses a clear, logical layout to show results from an experiment. These results indicate how
material properties vary with temperature. The report is read by a designer, who uses the results to create a product
that works in a range of different operating temperatures.
— the data being computer processable (machine readable) rather than just being for a person to read
Deleted: —
and understand.
EXAMPLE 2 A research scientist uses a database system to store the results of experiments on a material. This
system controls the format of different values in the data set. The system generates an output file of digital data.
This file is processed by a software application for engineering analysis. The application determines the optimum
geometry when using the material to make a product.
ISO 9000 explains that quality is not an abstract concept of absolute perfection. Quality is actually the
conformance of characteristics to requirements. This actuality means that any item of data can be of high
quality for one purpose but not for a different purpose. The quality is different because the requirements
are different between the two purposes.
EXAMPLE 3 Time data are processed by calendar applications and also by control systems for propulsion units
on spacecraft. These data include start times for meetings in a calendar application and activation times in a control
system. These start times require less precision than the activation times.
The nature of digital data is fundamental to establishing requirements that are relevant to the specific
decisions that are made by each organization.

Deleted: https://sdgs.un.org/goals
1
 https://sdgs.un.org/goals
Deleted: -
2
 ISO 8000-2 defines information as “knowledge concerning objects, such as facts, events, things, processes, or ideas,
including concepts, that within a certain context has a particular meaning”. Deleted: 2022
© ISO 2023 – All rights reserved v

---------------------- Page: 5 ----------------------
ISO/PRF 8000-51:2023(E)
Deleted: 2022
EXAMPLE 4 ISO 8000-1 identifies that data have syntactic (format), semantic (meaning) and pragmatic
Deleted: -
(usefulness) characteristics.
To support the delivery of high-quality data, the ISO 8000 series addresses: Deleted: -
— data governance, data quality management and maturity assessment;
Deleted: —
EXAMPLE 5 ISO 8000-61 specifies a process reference model for data quality management. Deleted: -
— creating and applying requirements for data and information;
Deleted: —
EXAMPLE 6 ISO 8000-110 specifies how to exchange characteristic data that are master data.
Deleted: -
— monitoring and measuring information and data quality;
Deleted: —
EXAMPLE 7 ISO 8000-8 specifies approaches to measuring information and data quality.
Deleted: -
— improving data and, consequently, information quality;
Deleted: —
EXAMPLE 8 ISO/TS 8000-81 specifies an approach to data profiling, which identifies opportunities to improve
Deleted: -
data quality.
— issues that are specific to the type of content in a data set.
Deleted: —
EXAMPLE 9 ISO/TS 8000-311 specifies how to address quality considerations for product shape data.
Deleted: -
Data quality management covers all aspects of data processing, including creating, collecting, storing,
maintaining, transferring, exploiting and presenting data to deliver information.
Effective data quality management is systemic and systematic, requiring an understanding of the root
causes of data quality issues. This understanding is the basis for not just correcting existing
nonconformities but for also implementing solutions that prevent future reoccurrence of those
nonconformities.
EXAMPLE 10 If a data set includes dates in multiple formats including “yyyy-mm-dd”, “mm-dd-yy” and
Deleted: -
“dd-mm-yy”, then data cleansing can correct the consistency of the values. Such cleansing requires additional
Deleted: -
information, however, to resolve ambiguous entries (such as, “04-05-20”). The cleansing also cannot address any
Deleted: -
process issues and people issues, including training, that have caused the inconsistency.
Deleted: -
0.2  Understanding more about the ISO 8000 series
Deleted: -
ISO 8000-1 provides a detailed explanation of the structure and scope of the whole ISO 8000 series.
Deleted: -
3
ISO 8000-2 specifies the single, common vocabulary for the ISO 8000 series. This vocabulary is ideal Deleted: -
reading material by which to understand the overall subject matter of data quality. ISO 8000-2 presents
Deleted: -
the vocabulary structured by a series of topic areas (for example, terms relating to quality and terms
Deleted: -
relating to data and information).
Deleted: -
4
ISO has identified ISO 8000-1, ISO 8000-2 and ISO 8000-8 as horizontal deliverables .
Deleted: -
0.3  Role of this document
Deleted: -
As a contribution to this overall capability of the ISO 8000 series, this document enables organizations to
Deleted: -
exchange data policy statements. These statements are the core output from data governance. This output
Deleted: -
supports organizations to achieve availability, usability, integrity and security of data. The policies affect
the practical implementation of creating, managing and using data sets.
An organization appoints a data governance authority to be responsible for developing and enforcing the
policies relating to the management of data.
To ensure the effect of these policies, organizations can decide each data governance policy statement:

3
 The content is available on the ISO Online Browsing Platform. https://www.iso.org/obp
Deleted: http://www.iso.org/obp
4
 Deliverable dealing with a subject relevant to a number of committees or sectors or of crucial importance to ensure
coherence across standardization deliverables. Deleted: 2022
vi © ISO 2023 – All rights reserved

---------------------- Page: 6 ----------------------
ISO/PRF 8000-51:2023(E)
Deleted: 2022
a) is recorded by a data governance policy register (see Annex B);
Deleted: a)
Deleted: Annex B);
b) has a reference;
Deleted: b)
c) specifies the requirements applicable to a data set in a specification that conforms with
Deleted: c)
ISO/TS 22745-30;
Deleted: -
d) identifies the domain of application;
Deleted: d)
e) describes how to measure and monitor conformance with the requirements specified by the policy.
Deleted: e)
Software applications are available to assist organizations in the creation and management of data
governance policies. These organizations can significantly reduce the cost of implementing data
governance by creating data governance policy statements that are portable. Such statements can be
reliably interpreted by multiple applications, contributing to improved data and information quality.
Organizations can use this document on its own or in conjunction with other parts in the ISO 8000 series.
This document supports activities that affect:
— one or more information systems;
Deleted: —
— data flows within the organization and with external organizations;
Deleted: —
— any phase of the data life cycle.
Deleted: —
Annex A of this document contains an identifier that conforms to ISO/IEC 8824-1. The identifier
Deleted: Annex A
unambiguously identifies this document in an open information system.
Deleted: -
0.4  Benefits of the ISO 8000 series
By implementing parts in the ISO 8000 series to improve organizational performance, an organization
achieves the following benefits:
— objective validation of the foundations for digital transformation of the organization;
Deleted: —
— a sustainable basis for data in digital form becoming a fundamental asset class the organization relies
Deleted: —
on to deliver value;
— securing evidence-based trust from other parties (including supply chain partners and regulators)
Deleted: —
about the repeatability and reliability of data and information processing in the organization;
Deleted: -
— porta
...

INTERNATIONAL ISO
STANDARD 8000-51
First edition
Data quality —
Part 51:
Data governance: Exchange of data
policy statements
PROOF/ÉPREUVE
Reference number
ISO 8000-51:2023(E)
© ISO 2023

---------------------- Page: 1 ----------------------
ISO 8000-51:2023(E)
COPYRIGHT PROTECTED DOCUMENT
© ISO 2023
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
Email: copyright@iso.org
Website: www.iso.org
Published in Switzerland
ii
PROOF/ÉPREUVE © ISO 2023 – All rights reserved

---------------------- Page: 2 ----------------------
ISO 8000-51:2023(E)
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 2
4 Fundamental principles and assumptions . 2
5 Requirements for representing data governance policy statements .2
6 Conformance . 3
Annex A (informative) Document identification . 4
Annex B (informative) Example of a data governance policy register . 5
Bibliography . 8
iii
© ISO 2023 – All rights reserved PROOF/ÉPREUVE

---------------------- Page: 3 ----------------------
ISO 8000-51:2023(E)
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
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 ISO documents 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).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www.iso.org/patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to
the World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT), see
www.iso.org/iso/foreword.html.
This document was prepared by Technical Committee ISO/TC 184, Automation systems and integration,
Subcommittee SC 4 Industrial data.
A list of all parts in the ISO 8000 series can be found on the ISO website.
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.
iv
PROOF/ÉPREUVE © ISO 2023 – All rights reserved

---------------------- Page: 4 ----------------------
ISO 8000-51:2023(E)
Introduction
0.1  Foundations of the ISO 8000 series
Digital data deliver value by enhancing all aspects of organizational performance including:
— operational effectiveness and efficiency;
— safety and security;
— reputation with customers and the wider public;
— compliance with statutory regulations;
— innovation;
— consumer costs, revenues and stock prices.
In addition, many organizations are now addressing these considerations with reference to the United
1)
Nations Sustainable Development Goals .
The influence on performance originates from data being the formalized representation of
2)
information . This information enables organizations to make reliable decisions. This decision making
can be performed by human beings directly and also by automated data processing including artificial
intelligence systems.
Through widespread adoption of digital computing and associated communication technologies,
organizations become dependent on digital data. This dependency amplifies the negative consequences
of lack of quality in these data. These consequences are the decrease of organizational performance.
The biggest impact of digital data comes from two key factors:
— the data having a structure that reflects the nature of the subject matter;
EXAMPLE 1 A research scientist writes a report using a software application for word processing. This report
includes a table that uses a clear, logical layout to show results from an experiment. These results indicate how
material properties vary with temperature. The report is read by a designer, who uses the results to create a
product that works in a range of different operating temperatures.
— the data being computer processable (machine readable) rather than just being for a person to read
and understand.
EXAMPLE 2 A research scientist uses a database system to store the results of experiments on a material.
This system controls the format of different values in the data set. The system generates an output file of digital
data. This file is processed by a software application for engineering analysis. The application determines the
optimum geometry when using the material to make a product.
ISO 9000 explains that quality is not an abstract concept of absolute perfection. Quality is actually
the conformance of characteristics to requirements. This actuality means that any item of data can
be of high quality for one purpose but not for a different purpose. The quality is different because the
requirements are different between the two purposes.
EXAMPLE 3 Time data are processed by calendar applications and also by control systems for propulsion
units on spacecraft. These data include start times for meetings in a calendar application and activation times in
a control system. These start times require less precision than the activation times.
1) https://sdgs.un.org/goals
2) ISO 8000-2 defines information as “knowledge concerning objects, such as facts, events, things, processes, or
ideas, including concepts, that within a certain context has a particular meaning”.
v
© ISO 2023 – All rights reserved PROOF/ÉPREUVE

---------------------- Page: 5 ----------------------
ISO 8000-51:2023(E)
The nature of digital data is fundamental to establishing requirements that are relevant to the specific
decisions that are made by each organization.
EXAMPLE 4 ISO 8000-1 identifies that data have syntactic (format), semantic (meaning) and pragmatic
(usefulness) characteristics.
To support the delivery of high-quality data, the ISO 8000 series addresses:
— data governance, data quality management and maturity assessment;
EXAMPLE 5 ISO 8000-61 specifies a process reference model for data quality management.
— creating and applying requirements for data and information;
EXAMPLE 6 ISO 8000-110 specifies how to exchange characteristic data that are master data.
— monitoring and measuring information and data quality;
EXAMPLE 7 ISO 8000-8 specifies approaches to measuring information and data quality.
— improving data and, consequently, information quality;
EXAMPLE 8 ISO/TS 8000-81 specifies an approach to data profiling, which identifies opportunities to improve
data quality.
— issues that are specific to the type of content in a data set.
EXAMPLE 9 ISO/TS 8000-311 specifies how to address quality considerations for product shape data.
Data quality management covers all aspects of data processing, including creating, collecting, storing,
maintaining, transferring, exploiting and presenting data to deliver information.
Effective data quality management is systemic and systematic, requiring an understanding of the
root causes of data quality issues. This understanding is the basis for not just correcting existing
nonconformities but for also implementing solutions that prevent future reoccurrence of those
nonconformities.
EXAMPLE 10 If a data set includes dates in multiple formats including “yyyy-mm-dd”, “mm-dd-yy” and
“dd-mm-yy”, then data cleansing can correct the consistency of the values. Such cleansing requires additional
information, however, to resolve ambiguous entries (such as, “04-05-20”). The cleansing also cannot address any
process issues and people issues, including training, that have caused the inconsistency.
0.2  Understanding more about the ISO 8000 series
ISO 8000-1 provides a detailed explanation of the structure and scope of the whole ISO 8000 series.
3)
ISO 8000-2 specifies the single, common vocabulary for the ISO 8000 series. This vocabulary is ideal
reading material by which to understand the overall subject matter of data quality. ISO 8000-2 presents
the vocabulary structured by a series of topic areas (for example, terms relating to quality and terms
relating to data and information).
4)
ISO has identified ISO 8000-1, ISO 8000-2 and ISO 8000-8 as horizontal deliverables .
0.3  Role of this document
As a contribution to this overall capability of the ISO 8000 series, this document enables organizations
to exchange data policy statements. These statements are the core output from data governance. This
output supports organizations to achieve availability, usability, integrity and security of data. The
policies affect the practical implementation of creating, managing and using data sets.
3) The content is available on the ISO Online Browsing Platform. https://www.iso.org/obp
4) Deliverable dealing with a subject relevant to a number of committees or sectors or of crucial importance to
ensure coherence across standardization deliverables.
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ISO 8000-51:2023(E)
An organization appoints a data governance authority to be responsible for developing and enforcing
the policies relating to the management of data.
To ensure the effect of these policies, organizations can decide each data governance policy statement:
a) is recorded by a data governance policy register (see Annex B);
b) has a reference;
c) specifies the requirements applicable to a data set in a specification that conforms with
ISO/TS 22745-30;
d) identifies the domain of application;
e) describes how to measure and monitor conformance with the requirements specified by the policy.
Software applications are available to assist organizations in the creation and management of data
governance policies. These organizations can significantly reduce the cost of implementing data
governance by creating data governance policy statements that are portable. Such statements can be
reliably interpreted by multiple applications, contributing to improved data and information quality.
Organizations can us
...

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