ISO 8000-2

Data quality — Part 2: Vocabulary

This document defines terms relating to data quality used in the ISO 8000 series of parts.

Qualité des données — Partie 2: Vocabulaire

General Information

• Status: Not Published
• ICS: 01.040.25 - Manufacturing engineering (Vocabularies)
• ICS: 25.040.40 - Industrial process measurement and control
• Technical Committee: ISO/TC 184/SC 4 - Industrial data
• Drafting Committee: ISO/TC 184/SC 4 - Industrial data

RELATIONS

• Revises: ISO 8000-2:2020/Amd 1:2021 - Data quality — Part 2: Vocabulary — Amendment 1
• Effective Date: 06-Jun-2022
• Revises: ISO 8000-2:2020 - Data quality — Part 2: Vocabulary
• Effective Date: 06-Jun-2022

Standards Content (sample)

ISO 8000-2:2022(E)
ISO TC 184/SC 4/WG 13
Date: 2022-07 Deleted: 02-14
Data quality — Part 2: Vocabulary
Qualité des données — Partie 2: Vocabulaire
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ISO 8000-2:2022(E)
© ISO 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: [phone]
Email: [e-mail]
Website: www.iso.org Deleted: www.iso.org
Published in Switzerland
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ISO 8000-2:2022(E)
Contents

Foreword ................................................................................................................................................................ iv

Introduction ........................................................................................................................................................... v

1 Scope .......................................................................................................................................................... 1

2 Normative references .......................................................................................................................... 1

3 Terms and definitions .......................................................................................................................... 1

3.1 Terms relating to quality .................................................................................................................... 1

3.2 Terms relating to data and information ........................................................................................ 2

3.3 Terms relating to identifier ............................................................................................................... 4

3.4 Terms relating to measurement ...................................................................................................... 5

3.5 Terms relating to industrial data..................................................................................................... 6

3.6 Terms relating to data dictionary .................................................................................................... 7

3.7 Terms relating to characteristic data ............................................................................................. 7

3.8 Terms relating to data quality .......................................................................................................... 8

3.9 Terms relating to syntax and semantics .................................................................................... 11

3.10 Terms relating to transaction data .............................................................................................. 12

3.11 Terms relating to master data ....................................................................................................... 13

3.12 Terms relating to product data ..................................................................................................... 13

3.13 Terms relating to item of production and item of supply .................................................... 15

3.14 Terms relating to data quality role .............................................................................................. 16

3.15 Terms relating to process assessment ........................................................................................ 17

3.16 Terms relating to data governance .............................................................................................. 20

Annex A (informative) Document identification ................................................................................... 21

Bibliography ....................................................................................................................................................... 22

Alphabetical index of terms .......................................................................................................................... 24

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ISO 8000-2:2022(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.

This fifth edition cancels and replaces the fourth edition (ISO 8000-2:2020), which has been technically

revised. It also incorporates the Amendment ISO 8000-2:2020/Amd 1:2021.
The main changes are as follows: Deleted: compared to the previous edition

— additional terminological entries to align the ISO 8000 series further with ISO 9000;

— updates where the updates originate from a new edition of ISO 10303-110;

— updates where the updates originate from converting ISO 8000-150 to an International Standard

Deleted: 10303
from a Technical Specification;
— updates where the updates originate from a new edition of ISO 10303-59;

— other minor improvements to entries to improve consistency and readability of entries.

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.
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ISO 8000-2:2022(E)
Introduction

Digital data deliver value by enhancing all aspects of organizational performance including:

— operational effectiveness and efficiency;
— safety;
— 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

Nations Sustainable Development Goals .

The influence on performance originates from data being the formalized representation of information .

This information enables organizations to make reliable decisions. Such 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.
https://sdgs.un.org/goals

This document 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: © ISO 2022 – All rights reserved 5¶

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ISO 8000-2:2022(E)

The nature of digital data is fundamental to establishing requirements that are relevant to the specific

decisions made by an organization.

EXAMPLE 4 ISO 8000-8 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 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.

As a contribution to this overall capability of the ISO 8000 series, this document 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. This document presents the vocabulary structured

by a series of topic areas (for example, terms relating to quality and terms relating to data and

information).

Organizations can use this document on its own or in conjunction with other parts of the ISO 8000 series.

This document supports activities that affect:
— one or more information systems;
— data flows within the organization and with external organizations;
— any phase of the data life cycle.
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ISO 8000-2:2022(E)

By implementing parts of 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;

— a sustainable basis for data in digital form becoming a fundamental asset class the organization relies

on to deliver value;

— securing evidence-based trust from other parties (including supply chain partners and regulators)

about the repeatability and reliability of data and information processing in the organization;

— portability of data with resulting protection against loss of intellectual property and reusability

across the organization and applications;

— effective and efficient interoperability between all parties in a supply chain to achieve traceability of

data back to original sources;

— readiness to acquire or supply services where the other party expects to work with common

understanding of explicit data requirements.

ISO 8000-1 provides a detailed explanation of the structure and scope of the whole ISO 8000 series.

ISO has identified this document, ISO 8000-1 and ISO 8000-8 as horizontal deliverables .

Annex A contains an identifier that conforms to ISO/IEC 8824-1. The identifier unambiguously identifies

this document in an open information system.

A horizontal deliverable is a deliverable dealing with a subject relevant to a number of committees or sectors or

of crucial importance to ensure coherence across standardization deliverables. Deleted: © ISO 2022 – All rights reserved 7¶

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FINAL DRAFT INTERNATIONAL STANDARD ISO 8000-2:2022(E)
Data quality — Part 2: Vocabulary
1 Scope

This document defines terms relating to data quality. These terms are used by the ISO 8000 series of

standards.
Deleted: parts
2 Normative references
There are no normative references in this document.
3 Terms and definitions

ISO and IEC maintain terminology databases for use in standardization at the following addresses:

Deleted: For the purposes of this document, the following
terms and definitions apply.¶
— ISO Online browsing platform: available at https://www.iso.org/obp
Deleted: terminological
— IEC Electropedia: available at https://www.electropedia.org/
Field Code Changed
Deleted: http
3.1 Terms relating to quality
3.1.1
process Deleted: , noun

set of interrelated or interacting activities that use inputs to deliver an intended result

[SOURCE: ISO 9000:2015, 3.4.1, modified — Notes to entry have been removed.]
3.1.2
requirement
need or expectation that is stated, generally implied or obligatory
[SOURCE: ISO 9000:2015, 3.6.4, modified — Notes to entry have been removed.]
3.1.3
quality

degree to which a set of inherent characteristics of an object fulfils requirements (3.1.2)

Note 1 to entry: The term “quality” can be used with adjectives such as poor, good or excellent.

Note 2 to entry: “Inherent”, as opposed to “assigned”, means existing in the object.

[SOURCE: ISO 9000:2015, 3.6.2]
3.1.4
quality management system
part of a management system with regard to quality (3.1.3)
[SOURCE: ISO 9000:2015, 3.5.4]
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ISO 8000-2:2022(E)
3.1.5
nonconformity
non-fulfilment of a requirement (3.1.2)
[SOURCE: ISO 9000:2015, 3.6.9, modified — Note 1 to entry has been removed.]
3.1.6
defect
nonconformity (3.1.5) related to an intended or specified use

Note 1 to entry: The distinction between the concepts defect and nonconformity is important as it has legal

connotations, particularly those associated with product (3.5.2) and service liability issues.

Note 2 to entry: The intended use as intended by the customer can be affected by the nature of the information

(3.2.1), such as operating or maintenance instructions, provided by the provider.

[SOURCE: ISO 9000:2015, 3.6.10]
3.1.7
quality management
management with regard to quality (3.1.3)

Note 1 to entry: Quality management can include establishing quality policies and quality objectives, and processes

(3.1.1) to achieve these quality objectives through quality planning (3.1.8), quality control (3.1.9), quality assurance

(3.1.10) and quality improvement (3.1.11).
[SOURCE: ISO 9000:2015, 3.3.4]
3.1.8
quality planning

part of quality management (3.1.7) focused on setting quality (3.1.3) objectives and specifying necessary

operational processes (3.1.1) and related resources to achieve the quality objectives

Note 1 to entry: Establishing quality plans can be part of quality planning.
[SOURCE: ISO 9000:2015, 3.3.5]
3.1.9
quality control

part of quality management (3.1.7) focused on fulfilling quality (3.1.3) requirements (3.1.2)

[SOURCE: ISO 9000:2015, 3.3.7]
3.1.10
quality assurance

part of quality management (3.1.7) focused on providing confidence that quality (3.1.3) requirements

(3.1.2) will be fulfilled
[SOURCE: ISO 9000:2015, 3.3.6]
3.1.11
quality improvement

part of quality management (3.1.7) focused on increasing the ability to fulfil quality (3.1.3) requirements

(3.1.2)
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ISO 8000-2:2022(E)

Note 1 to entry: The quality requirements can be related to any aspect such as effectiveness, efficiency or

traceability.
[SOURCE: ISO 9000:2015, 3.3.8]
3.1.12
inspection
determination of conformity to specified requirements (3.1.2)
[SOURCE: ISO 9000:2015, 3.11.7, modified — Notes to entry have been removed.]
3.2 Terms relating to data and information
3.2.1
information

knowledge concerning objects, such as facts, events, things, processes (3.1.1), or ideas, including concepts,

that within a certain context has a particular meaning

[SOURCE: ISO/IEC 2382:2015, 2121271, modified — Field of application and notes to entry have been

removed.]
3.2.2
data

reinterpretable representation of information (3.2.1) in a formalized manner suitable for communication,

interpretation, or processing

[SOURCE: ISO/IEC 2382:2015, 2121272, modified — Notes to entry have been removed.]

3.2.3
data exchange
storing, accessing, transferring, and archiving of data (3.2.2)
[SOURCE: ISO 10303-1:2021, 3.1.31]
3.2.4
data set
logically meaningful grouping of data (3.2.2)
EXAMPLE 1 Computer-aided design (CAD) files.
EXAMPLE 2 Electronic data interchange (EDI) transactions.
3.2.5
metadata
data (3.2.2) defining and describing other data

[SOURCE: ISO/IEC 11179-1:2015, 3.2.16, modified — The words “that defines and describes” have been

replaced with “defining and describing”.]
3.2.6
objective evidence
data (3.2.2) supporting the existence or verity of something

Note 1 to entry: Objective evidence can be obtained through observing, measuring (3.4.1), testing or other means.

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ISO 8000-2:2022(E)

[SOURCE: ISO 9000:2015, 3.8.3, modified — Note 1 to entry has been modified and Note 2 to entry has

been removed.]
3.2.7
data element
unit of data (3.2.2) that is considered in context to be indivisible

Note 1 to entry: The definition states that a data element is “indivisible” in some context. This means it is possible

that a data element considered indivisible in one context (e.g. telephone number) can be divisible in another context

(e.g. country code, area code, local number).

[SOURCE: ISO/IEC 11179-1:2015, 3.3.8, modified — The abbreviated term “DE” has been removed and

the word “may” has been replaced by “can” in Note 1 to entry.]
3.2.8
value domain
set of permissible values

Note 1 to entry: The permissible values in a value domain can either be enumerated or expressed via a description.

[SOURCE: ISO/IEC 11179-1:2015, 3.3.31, modified — The abbreviated term “VD” has been removed and

the word “may” has been replaced by “can” in Note 1 to entry.]
3.2.9
data element concept
concept that is an association of a property with an object class

Note 1 to entry: A data element concept is implicitly associated with both the property and the object class whose

combination it expresses.

Note 2 to entry: A data element concept can also be associated with zero or more conceptual domains, each of which

expresses its value meanings.

Note 3 to entry: A data element concept can also be associated with zero or more data elements (3.2.7) each, of

which provides representation for the data element concept via its associated value domain (3.2.8).

[SOURCE: ISO/IEC 11179-1:2015, 3.3.9, modified — The abbreviated term “DEC” has been removed and

the word “may” has been replaced by “can” in Notes 2 and 3 to entry.]
3.3 Terms relating to identifier
3.3.1
identifier
string of characters created by an organization to reference a data set (3.2.4)
3.3.2
identifier resolution

process (3.1.1) that, when applied to an identifier (3.3.1), returns an associated data set (3.2.4)

3.3.3
entity
concrete or abstract thing in the domain under consideration

[SOURCE: ISO 19439:2006, 3.29, modified — The word “any” has been removed at the start of the

definition.]
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ISO 8000-2:2022(E)
3.3.4
organization identifier

reference that can be resolved unambiguously to the legal name, the location and the administrator of

the organization
3.3.5
legal entity

physical or juridical person granted legal status by the governing body of a nation, state or community

3.3.6
authoritative identifier

identifier (3.3.1) issued by an organization that is the originator of the object identified or that is a legal

authority

EXAMPLE The original part manufacturer issues the authoritative identifier for that part. Distributors can also

assign identifiers, which are proxy identifiers (3.3.8) (not authoritative identifiers).

Note 1 to entry: An authoritative legal entity identifier (3.3.7) is an authoritative identifier issued by an organization

that is a legal authority.
3.3.7
authoritative legal entity identifier
ALEI

identifier (3.3.1) that identifies a legal entity (3.3.5) and is issued by the administrative agency for a

governing body of the nation, state, or community with the authority to grant legal status

EXAMPLE For the State of Delaware (in the United States), the Division of Corporations is the administrative

agency that issues identifiers for juridical persons represented on documents of formation. This agency issued the

authoritative legal entity identifier “3031657” to identify the formation of the Code Management Association as a

legal entity.
3.3.8
proxy identifier

identifier (3.3.1) issued by an organization that is not the originator of the object identified

3.3.9
proxy legal entity identifier

identifier (3.3.1) that identifies a legal entity (3.3.5) and is issued by an organization that is not the

administrative agency for a government and, thus, has no authority to grant legal status

3.3.10
vital record
record of life events kept under governmental authority
EXAMPLE Birth certificates, marriage licenses and death certificates.
3.3.11
free decoding

identifier resolution (3.3.2) that, without the need to pay a fee, returns an associated data set (3.2.4)

3.3.12
fee-based decoding

identifier resolution (3.3.2) that, only after paying a fee, returns an associated data set (3.2.4)

3.3.13
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ISO 8000-2:2022(E)
free encoding

without the need to pay a fee, using terms and definitions to discover concept identifiers (3.3.1)

3.4 Terms relating to measurement
3.4.1
measure, verb
ascertain or determine the magnitude or quantity of something
3.4.2
measurement
result of measuring (3.4.1) something
3.4.3
measurement data
data (3.2.2) representing a measurement (3.4.2)
3.4.4
unit of measurement
measurement unit
unit

real scalar quantity, defined and adopted by convention, with which any other quantity of the same kind

can be compared to express the ratio of the second quantity to the first one as a number

[SOURCE: ISO 80000-1:2009, 3.9, modified — Notes to entry have been removed.]
3.4.5
qualifier of measurement

indication of a value not being an actual, exact representation of a single instance of a measurement (3.4.2)

EXAMPLE Qualifiers can include “nominal”, “maximum”, “minimum” and “typical”.
3.5 Terms relating to industrial data
3.5.1
industrial data

data (3.2.2) representing information (3.2.1) that enables and supports the life-cycle of goods and

services

EXAMPLE 1 Industrial data includes data about: products (3.5.2); life-cycle processes (3.1.1), including

manufacturing, distribution and maintenance; facilities that are used by life-cycle processes; digital twins; product

geometry, topology and visualization; technical dictionaries; and parts catalogues.

EXAMPLE 2 The ISO 10303 series, the ISO 13584 series, the ISO 15926 series, the ISO 22745 series and the

ISO/TS 29002 series each specifies requirements (3.1.2) applicable to industrial data.

EXAMPLE 3 The term “industrial” is distinct from the terms “agricultural” and “commercial”.

Note 1 to entry: Supporting the life-cycle includes supporting the processes of the life-cycle and the facilities that

are used by those processes.

Note 2 to entry: Although the ISO 8000 series is developed by ISO/TC 184/SC 4 (Industrial Data), most parts in the

series are applicable to all types of data.
3.5.2
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ISO 8000-2:2022(E)
product
thing or substance produced by a natural or artificial process (3.1.1)

[SOURCE: ISO 10303-1:2021, 3.1.49, modified — Note 1 to entry has been removed.] Deleted: ]

3.5.3
product data

representation of information (3.2.1) about a product (3.5.2) in a formal manner suitable for

communication, interpretation, or processing by human beings or by computers
Note 1 to entry: Adapted from ISO 10303-1:2021, 3.1.50.
Deleted: [SOURCE:
Deleted: ]
3.5.4
application
one or more processes (3.1.1) creating or using product data (3.5.3)
[SOURCE: ISO 10303-1:2021, 3.1.5]
3.5.5
application protocol

part of ISO 10303 that specifies an application interpreted model satisfying the scope and information

(3.2.1) requirements (3.1.2) for a specific application (3.5.4)

Note 1 to entry: This definition differs from the definition used in open system interconnection (OSI) standards. No

part of the ISO 8000 series, however, contains content referring specifically to OSI communication, so this definition

applies in all parts of the ISO 8000 series.

[SOURCE: ISO 10303-1:2021, 3.1.17, modified — Note 1 to entry has been modified.]

3.5.6
application reference model
ARM

information (3.2.1) model that describes the information requirements (3.1.2) and constraints of an

application (3.5.4) within an application protocol (3.5.5) or module
[SOURCE: ISO 10303-1:2021, 3.1.18]
3.5.7
application software
application program

software or program that is specific to the solution of an application (3.5.4) problem

[SOURCE: ISO/IEC 2382:2015, 2121364, modified — Notes to entry have been removed.]

3.6 Terms relating to data dictionary
3.6.1
data dictionary entry

description of an entity (3.3.3) type containing, at a minimum, an unambiguous identifier (3.3.1), a term

and a definition

Note 1 to entry: In the data (3.2.2) architecture specified by the ISO 8000 series, a property need not be associated

with a specific data type in a data dictionary (3.6.2). The association between a property and a data type can be

made in a data specification (3.6.3).
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ISO 8000-2:2022(E)
Note 2 to entry: In order to exchange a value corres
...

INTERNATIONAL ISO
STANDARD 8000-2
Fifth edition
Data quality —
Part 2:
Vocabulary
Qualité des données —
Partie 2: Vocabulaire
PROOF/ÉPREUVE
Reference number
ISO 8000-2:2022(E)
© ISO 2022
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ISO 8000-2:2022(E)
COPYRIGHT PROTECTED DOCUMENT
© ISO 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: [phone]
Email: [e-mail]
Website: www.iso.org
Published in Switzerland
PROOF/ÉPREUVE © ISO 2022 – All rights reserved
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ISO 8000-2:2022(E)
Contents Page

Foreword ........................................................................................................................................................................................................................................iv

Introduction .................................................................................................................................................................................................................................v

1 Scope ................................................................................................................................................................................................................................. 1

2 Normative references ..................................................................................................................................................................................... 1

3 Terms and definitions .................................................................................................................................................................................... 1

3.1 Terms relating to quality ............................................................................................................................................................... 1

3.2 Terms relating to data and information ........................................................................................................................... 3

3.3 Terms relating to identifier ......................................................................................................................................................... 4

3.4 Terms relating to measurement .............................................................................................................................................. 5

3.5 Terms relating to industrial data ........................................................................................................................................... 6

3.6 Terms relating to data dictionary.......................................................................................................................................... 7

3.7 Terms relating to characteristic data ................................................................................................................................. 8

3.8 Terms relating to data quality .................................................................................................................................................. 8

3.9 Terms relating to syntax and semantics.......................................................................................................................12

3.10 Terms relating to transaction data .................................................................................................................................... 13

3.11 Terms relating to master data ...............................................................................................................................................13

3.12 Terms relating to product data ............................................................................................................................................. 13

3.13 Terms relating to item of production and item of supply .............................................................................. 15

3.14 Terms relating to data quality role .................................................................................................................................... 16

3.15 Terms relating to process assessment............................................................................................................................ 17

3.16 Terms relating to data governance .................................................................................................................................... 20

Annex A (informative) Document identification .................................................................................................................................21

Bibliography .............................................................................................................................................................................................................................22

Index .................................................................................................................................................................................................................................................24

iii
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ISO 8000-2:2022(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.

This fifth edition cancels and replaces the fourth edition (ISO 8000-2:2020), which has been technically

revised. It also incorporates the Amendment ISO 8000-2:2020/Amd 1:2021.
The main changes are as follows:

— additional terminological entries to align the ISO 8000 series further with ISO 9000;

— updates where the updates originate from a new edition of ISO 10303-110;

— updates where the updates originate from converting ISO 8000-150 to an International Standard

from a Technical Specification;
— updates where the updates originate from a new edition of ISO 10303-59;

— other minor improvements to entries to improve consistency and readability of entries.

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.
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ISO 8000-2:2022(E)
Introduction

Digital data deliver value by enhancing all aspects of organizational performance including:

— operational effectiveness and efficiency;
— safety;
— 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

Nations Sustainable Development Goals .

The influence on performance originates from data being the formalized representation of

information . This information enables organizations to make reliable decisions. Such 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.

The nature of digital data is fundamental to establishing requirements that are relevant to the specific

decisions made by an organization.

EXAMPLE 4 ISO 8000-8 identifies that data have syntactic (format), semantic (meaning) and pragmatic

(usefulness) characteristics.
1) https://sdgs.un.org/goals

2) This document 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”.

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ISO 8000-2:2022(E)
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 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.

As a contribution to this overall capability of the ISO 8000 series, this document 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. This document presents the vocabulary

structured by a series of topic areas (for example, terms relating to quality and terms relating to data

and information).

Organizations can use this document on its own or in conjunction with other parts of the ISO 8000

series.
This document supports activities that affect:
— one or more information systems;
— data flows within the organization and with external organizations;
— any phase of the data life cycle.

By implementing parts of 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;

— a sustainable basis for data in digital form becoming a fundamental asset class the organization

relies on to deliver value;

— securing evidence-based trust from other parties (including supply chain partners and regulators)

about the repeatability and reliability of data and information processing in the organization;

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ISO 8000-2:2022(E)

— portability of data with resulting protection against loss of intellectual property and reusability

across the organization and applications;

— effective and efficient interoperability between all parties in a supply chain to achieve traceability

of data back to original sources;

— readiness to acquire or supply services where the other party expects to work with common

understanding of explicit data requirements.

ISO 8000-1 provides a detailed explanation of the structure and scope of the whole ISO 8000 series.

ISO has identified this document, ISO 8000-1 and ISO 8000-8 as horizontal deliverables .

Annex A contains an identifier that conforms to ISO/IEC 8824-1. The identifier unambiguously identifies

this document in an open information system.

3) A horizontal deliverable is a deliverable dealing with a subject relevant to a number of committees or sectors or

of crucial importance to ensure coherence across standardization deliverables.
vii
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INTERNATIONAL STANDARD ISO 8000-2:2022(E)
Data quality —
Part 2:
Vocabulary
1 Scope

This document defines terms relating to data quality. These terms are used by the ISO 8000 series of

standards.
2 Normative references
There are no normative references in this document.
3 Terms and definitions

ISO and IEC maintain terminology databases for use in standardization at the following addresses:

— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
3.1 Terms relating to quality
3.1.1
process

set of interrelated or interacting activities that use inputs to deliver an intended result

[SOURCE: ISO 9000:2015, 3.4.1, modified — Notes to entry have been removed.]
3.1.2
requirement
need or expectation that is stated, generally implied or obligatory
[SOURCE: ISO 9000:2015, 3.6.4, modified — Notes to entry have been removed.]
3.1.3
quality

degree to which a set of inherent characteristics of an object fulfils requirements (3.1.2)

Note 1 to entry: The term “quality” can be used with adjectives such as poor, good or excellent.

Note 2 to entry: “Inherent”, as opposed to “assigned”, means existing in the object.

[SOURCE: ISO 9000:2015, 3.6.2]
3.1.4
quality management system
part of a management system with regard to quality (3.1.3)
[SOURCE: ISO 9000:2015, 3.5.4]
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ISO 8000-2:2022(E)
3.1.5
nonconformity
non-fulfilment of a requirement (3.1.2)
[SOURCE: ISO 9000:2015, 3.6.9, modified — Note 1 to entry has been removed.]
3.1.6
defect
nonconformity (3.1.5) related to an intended or specified use

Note 1 to entry: The distinction between the concepts defect and nonconformity is important as it has legal

connotations, particularly those associated with product (3.5.2) and service liability issues.

Note 2 to entry: The intended use as intended by the customer can be affected by the nature of the information

(3.2.1), such as operating or maintenance instructions, provided by the provider.

[SOURCE: ISO 9000:2015, 3.6.10]
3.1.7
quality management
management with regard to quality (3.1.3)

Note 1 to entry: Quality management can include establishing quality policies and quality objectives, and

processes (3.1.1) to achieve these quality objectives through quality planning (3.1.8), quality control (3.1.9), quality

assurance (3.1.10) and quality improvement (3.1.11).
[SOURCE: ISO 9000:2015, 3.3.4]
3.1.8
quality planning

part of quality management (3.1.7) focused on setting quality (3.1.3) objectives and specifying necessary

operational processes (3.1.1) and related resources to achieve the quality objectives

Note 1 to entry: Establishing quality plans can be part of quality planning.
[SOURCE: ISO 9000:2015, 3.3.5]
3.1.9
quality control

part of quality management (3.1.7) focused on fulfilling quality (3.1.3) requirements (3.1.2)

[SOURCE: ISO 9000:2015, 3.3.7]
3.1.10
quality assurance

part of quality management (3.1.7) focused on providing confidence that quality (3.1.3) requirements

(3.1.2) will be fulfilled
[SOURCE: ISO 9000:2015, 3.3.6]
3.1.11
quality improvement

part of quality management (3.1.7) focused on increasing the ability to fulfil quality (3.1.3) requirements

(3.1.2)

Note 1 to entry: The quality requirements can be related to any aspect such as effectiveness, efficiency or

traceability.
[SOURCE: ISO 9000:2015, 3.3.8]
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ISO 8000-2:2022(E)
3.1.12
inspection
determination of conformity to specified requirements (3.1.2)
[SOURCE: ISO 9000:2015, 3.11.7, modified — Notes to entry have been removed.]
3.2 Terms relating to data and information
3.2.1
information

knowledge concerning objects, such as facts, events, things, processes (3.1.1), or ideas, including

concepts, that within a certain context has a particular meaning

[SOURCE: ISO/IEC 2382:2015, 2121271, modified — Field of application and notes to entry have been

removed.]
3.2.2
data

reinterpretable representation of information (3.2.1) in a formalized manner suitable for communication,

interpretation, or processing

[SOURCE: ISO/IEC 2382:2015, 2121272, modified — Notes to entry have been removed.]

3.2.3
data exchange
storing, accessing, transferring, and archiving of data (3.2.2)
[SOURCE: ISO 10303-1:2021, 3.1.31]
3.2.4
data set
logically meaningful grouping of data (3.2.2)
EXAMPLE 1 Computer-aided design (CAD) files.
EXAMPLE 2 Electronic data interchange (EDI) transactions.
3.2.5
metadata
data (3.2.2) defining and describing other data

[SOURCE: ISO/IEC 11179-1:2015, 3.2.16, modified — The words “that defines and describes” have been

replaced with “defining and describing”.]
3.2.6
objective evidence
data (3.2.2) supporting the existence or verity of something

Note 1 to entry: Objective evidence can be obtained through observing, measuring (3.4.1), testing or other means.

[SOURCE: ISO 9000:2015, 3.8.3, modified — Note 1 to entry has been modified and Note 2 to entry has

been removed.]
3.2.7
data element
unit of data (3.2.2) that is considered in context to be indivisible

Note 1 to entry: The definition states that a data element is “indivisible” in some context. This means it is possible

that a data element considered indivisible in one context (e.g. telephone number) can be divisible in another

context (e.g. country code, area code, local number).
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ISO 8000-2:2022(E)

[SOURCE: ISO/IEC 11179-1:2015, 3.3.8, modified — The abbreviated term “DE” has been removed and

the word “may” has been replaced by “can” in Note 1 to entry.]
3.2.8
value domain
set of permissible values

Note 1 to entry: The permissible values in a value domain can either be enumerated or expressed via a description.

[SOURCE: ISO/IEC 11179-1:2015, 3.3.31, modified — The abbreviated term “VD” has been removed and

the word “may” has been replaced by “can” in Note 1 to entry.]
3.2.9
data element concept
concept that is an association of a property with an object class

Note 1 to entry: A data element concept is implicitly associated with both the property and the object class whose

combination it expresses.

Note 2 to entry: A data element concept can also be associated with zero or more conceptual domains, each of

which expresses its value meanings.

Note 3 to entry: A data element concept can also be associated with zero or more data elements (3.2.7) each, of

which provides representation for the data element concept via its associated value domain (3.2.8).

[SOURCE: ISO/IEC 11179-1:2015, 3.3.9, modified — The abbreviated term “DEC” has been removed and

the word “may” has been replaced by “can” in Notes 2 and 3 to entry.]
3.3 Terms relating to identifier
3.3.1
identifier
string of characters created by an organization to reference a data set (3.2.4)
3.3.2
identifier resolution

process (3.1.1) that, when applied to an identifier (3.3.1), returns an associated data set (3.2.4)

3.3.3
entity
concrete or abstract thing in the domain under consideration

[SOURCE: ISO 19439:2006, 3.29, modified — The word “any” has been removed at the start of the

definition.]
3.3.4
organization identifier

reference that can be resolved unambiguously to the legal name, the location and the administrator of

the organization
3.3.5
legal entity

physical or juridical person granted legal status by the governing body of a nation, state or community

3.3.6
authoritative identifier

identifier (3.3.1) issued by an organization that is the originator of the object identified or that is a legal

authority

EXAMPLE The original part manufacturer issues the authoritative identifier for that part. Distributors can

also assign identifiers, which are proxy identifiers (3.3.8) (not authoritative identifiers).

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ISO 8000-2:2022(E)

Note 1 to entry: An authoritative legal entity identifier (3.3.7) is an authoritative identifier issued by an

organization that is a legal authority.
3.3.7
authoritative legal entity identifier
ALEI

identifier (3.3.1) that identifies a legal entity (3.3.5) and is issued by the administrative agency for a

governing body of the nation, state, or community with the authority to grant legal status

EXAMPLE For the State of Delaware (in the United States), the Division of Corporations is the administrative

agency that issues identifiers for juridical persons represented on documents of formation. This agency issued

the authoritative legal entity identifier “3031657” to identify the formation of the Code Management Association

as a legal entity.
3.3.8
proxy identifier

identifier (3.3.1) issued by an organization that is not the originator of the object identified

3.3.9
proxy legal entity identifier

identifier (3.3.1) that identifies a legal entity (3.3.5) and is issued by an organization that is not the

administrative agency for a government and, thus, has no authority to grant legal status

3.3.10
vital record
record of life events kept under governmental authority
EXAMPLE Birth certificates, marriage licenses and death certificates.
3.3.11
free decoding

identifier resolution (3.3.2) that, without the need to pay a fee, returns an associated data set (3.2.4)

3.3.12
fee-based decoding

identifier resolution (3.3.2) that, only after paying a fee, returns an associated data set (3.2.4)

3.3.13
free encoding

without the need to pay a fee, using terms and definitions to discover concept identifiers (3.3.1)

3.4 Terms relating to measurement
3.4.1
measure, verb
ascertain or determine the magnitude or quantity of something
3.4.2
measurement
result of measuring (3.4.1) something
3.4.3
measurement data
data (3.2.2) representing a measurement (3.4.2)
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ISO 8000-2:2022(E)
3.4.4
unit of measurement
measurement unit
unit

real scalar quantity, defined and adopted by convention, with which any other quantity of the same

kind can be compared to express the ratio of the second quantity to the first one as a number

[SOURCE: ISO 80000-1:2009, 3.9, modified — Notes to entry have been removed.]
3.4.5
qualifier of measurement

indication of a value not being an actual, exact representation of a single instance of a measurement

(3.4.2)
EXAMPLE Qualifiers can include “nominal”, “maximum”, “minimum” and “typical”.
3.5 Terms relating to industrial data
3.5.1
industrial data

data (3.2.2) representing information (3.2.1) that enables and supports the life-cycle of goods and

services

EXAMPLE 1 Industrial data includes data about: products (3.5.2); life-cycle processes (3.1.1), including

manufacturing, distribution and maintenance; facilities that are used by life-cycle processes; digital twins;

product geometry, topology and visualization; technical dictionaries; and parts catalogues.

EXAMPLE 2 The ISO 10303 series, the ISO 13584 series, the ISO 15926 series, the ISO 22745 series and the

ISO/TS 29002 series each specifies requirements (3.1.2) applicable to industrial data.

EXAMPLE 3 The term “industrial” is distinct from the terms “agricultural” and “commercial”.

Note 1 to entry: Supporting the life-cycle includes supporting the processes of the life-cycle and the facilities that

are used by those processes.

Note 2 to entry: Although the ISO 8000 series is developed by ISO/TC 184/SC 4 (Industrial Data), most parts in

the series are applicable to all types of data.
3.5.2
product
thing or substance produced by a natural or artificial process (3.1.1)
[SOURCE: ISO 10303-1:2021, 3.1.49, modified — Note 1 to entry has been removed.]
3.5.3
product data

representation of information (3.2.1) about a product (3.5.2) in a formal manner suitable for

communication, interpretation, or processing by human beings or by computers
Note 1 to entry: Adapted from ISO 10303-1:2021, 3.1.50.
3.5.4
application
one or more processes (3.1.1) creating or using product data (3.5.3)
[SOURCE: ISO 10303-1:2021, 3.1.5]
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ISO 8000-2:2022(E)
3.5.5
application protocol

part of ISO 10303 that specifies an application interpreted model satisfying the scope and information

(3.2.1) requirements (3.1.2) for a specific application (3.5.4)

Note 1 to entry: This definition differs from the definition used in open system interconnection (OSI) standards.

No part of the ISO 8000 series, however, contains content referring specifically to OSI communication, so this

definition applies in all parts of the ISO 8000 series.

[SOURCE: ISO 10303-1:2021, 3.1.17, modified — Note 1 to entry has been modified.]

3.5.6
application reference model
ARM

information (3.2.1) model that describes the information requirements (3.1.2) and constraints of an

application (3.5.4) within an application protocol (3.5.5) or module
[SOURCE: ISO 10303-1:2021, 3.1.18]
3.5.7
application software
application program

software or program that is specific to the solution of an application (3.5.4) problem

[SOURCE: ISO/IEC 2382:2015, 2121364, modified — Notes to entry have been removed.]

3.6 Terms relating to data dictionary
3.6.1
data dictionary entry
description of an entity (3.3.3) type containing, at a minimum, an u
...