ISO 8000-2:2020

INTERNATIONAL ISO
STANDARD 8000-2
Fourth edition
2020-06
Data quality —
Part 2:
Vocabulary
Qualité des données —
Partie 2: Vocabulaire
Reference number
ISO 8000-2:2020(E)
©
ISO 2020

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ISO 8000-2:2020(E)

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© ISO 2020
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ISO 8000-2:2020(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 . 2
3.3 Terms relating to identifier . 2
3.4 Terms relating to measurement . 4
3.5 Terms relating to industrial data . 4
3.6 Terms relating to data dictionary . 5
3.7 Terms relating to characteristic data . 5
3.8 Terms relating to data quality . 6
3.9 Terms relating to syntax and semantics . 8
3.10 Terms relating to transaction data . 9
3.11 Terms relating to master data . 9
3.12 Terms relating to product data .10
3.13 Terms relating to item of production and item of supply .11
3.14 Terms relating to data quality role .11
3.15 Terms relating to process assessment .12
3.16 Terms relating to data governance .14
Annex A (informative) Document identification .15
Bibliography .16
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ISO 8000-2:2020(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 fourth edition cancels and replaces the third edition (ISO 8000-2:2018), which has been technically
revised.
The main changes compared to the previous edition are as follows:
— addition and modifications of terms and definitions.
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 8000-2:2020(E)

Introduction
The ability to create, collect, store, maintain, transfer, process and present data to support business
processes in a timely and cost-effective manner requires both an understanding of the characteristics
of the data that determine its quality, and an ability to measure, manage and report on data quality.
ISO 8000 defines characteristics that can be tested by any organization in the data supply chain to
objectively determine conformance of the data to ISO 8000.
ISO 8000 provides frameworks for improving data quality for specific kinds of data. The frameworks
can be used independently or in conjunction with quality management systems.
ISO 8000 covers industrial data quality characteristics throughout the product life cycle from
conception to disposal. ISO 8000 addresses specific kinds of data including, but not limited to, master
data, transaction data and product data.
This document establishes the vocabulary for the ISO 8000 series of parts.
Annex A contains an identifier that unambiguously identifies this document in an open information
system.
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INTERNATIONAL STANDARD ISO 8000-2:2020(E)
Data quality —
Part 2:
Vocabulary
1 Scope
This document defines terms relating to data quality used in the ISO 8000 series of parts.
2 Normative references
There are no normative references in this document.
3 Terms and definitions
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at http:// 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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3.1.5
nonconformity
non-fulfilment of a requirement (3.1.2)
[SOURCE: ISO 9000:2015, 3.6.9, modified — Note to entry has 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:—, 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.]
3.3 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)
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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).
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)
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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
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
measurement requirement
textual description of how a criterion is measured (3.4.1), including any necessary additional attributes
and rules to control the test and the element or elements to be tested, and which plays the role of an
external specification for a reliable measuring algorithm
Note 1 to entry: It is important to take care that the measurement requirement does not provide an algorithm
for the measuring process (3.1.1), since it is understood that algorithm development is a competitive arena for
engineering system vendors and where standardization is not possible.
3.5 Terms relating to industrial data
3.5.1
product
thing or substance produced by a natural or artificial process (3.1.1)
[SOURCE: ISO 10303-1:—, 3.1.49]
3.5.2
product data
representation of information (3.2.1) about a product (3.5.1) in a formal manner suitable for
communication, interpretation, or processing by human beings or by computers
[SOURCE: ISO 10303-1:—, 3.1.50]
3.5.3
application
one or more processes (3.1.1) creating or using product data (3.5.2)
[SOURCE: ISO 10303-1:—, 3.1.5]
3.5.4
application protocol
AP
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 (3.5.3)
Note 1 to entry: This definition differs from the definition used in open system interconnection (OSI) standards.
No part of ISO 8000, however, contains content referring specifically to OSI communication, so this definition
applies in all parts of ISO 8000.
[SOURCE: ISO 10303-1:—, 3.1.17, modified — Note 1 to entry has been modified.]
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3.5.5
application reference model
ARM
information (3.2.1) model that describes the information requirements (3.1.2) and constraints of an
application (3.5.3) within an application protocol (3.5.4) or module
[SOURCE: ISO 10303-1:—, 3.1.18]
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 ISO 8000 data (3.2.2) architecture, 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).
Note 2 to entry: In order to exchange a value corresponding to a data dictionary entry, more information (3.2.1)
than an identifier, a name and a definition could be needed. For a property, a data type is needed. Depending on
the kind of property, other data elements (e.g. unit of measure, language) could also be needed. These elements
can be given in the data dictionary, in a data specification that references the data dictionary entry, or directly
associated with the data.
Note 3 to entry: In the ISO 13584 data architecture, the dictionary entry for a property is required to reference
a specific data type. Thus, an ISO 13584 dictionary entry is a special case of the more general concept, as it
includes elements of a data specification.
[SOURCE: ISO 22745-2:2010, B.2.17, modified — The spelling of “datatype” has been changed to “data
type” to be consistent with other terms in this document and Note 2 to entry has been modified.]
3.6.2
data dictionary
collection of data dictionary entries (3.6.1) that allows lookup by entity (3.3.3) identifier (3.3.1)
[SOURCE: ISO 22745-2:2010, B.2.16]
3.6.3
data specification
set of requirements (3.1.2) covering the characteristics of data (3.2.2) being fit for one or more particular
purposes
Note 1 to entry: ISO 8000-110 requires a data specification to describe how items belong to a particular class by
using entries from a data dictionary (3.6.2).
Note 2 to entry: In collaborative relationships, the supplier of data and the user of that data agree the content
of the data specification in order to ensure the collaboration will be successful (i.e. the supplier can supply
conforming data and the user is able to exploit the data for the intended purposes).
Note 3 to entry: An effective data specification is one where the creator of the specification intends for the
requirements to be necessary and sufficient for the data to meet the particular purposes.
Note 4 to entry: All stakeholders will be able to understand the data specification more effectively if there is an
explicit statement of the intended purposes for the data.
3.7 Terms relating to characteristic data
3.7.1
property value
instance of a specific value together with an identifier (3.3.1) for a data dictionary entry (3.6.1) that
defines a property
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3.7.2
characteristic data
description of an entity (3.3.3) by the class to which it belongs and a set of property values (3.7.1)
EXAMPLE 1 ISO 13584, ISO 15926, ISO 22745, ISO 13399 and ISO/TS 29002 all include characteristic data in
their data (3.2.2) models.
EXAMPLE 2 The item “Hex Cap Screw — A193 Grade B7,.250-20 X 1.250” appears in a manufacturer's
catalogue. It can be described as:
— class: hexagon cap screw;
— property values: [material specification, A193 Grade B7]; [diameter, 0.250 in]; [thread pitch, 20/in]; [length,
1.250 in].
In actual characteristic data, the first element of each bracketed pair would be an identifier (3.3.1) for a data
dictionary entry (3.6.1). The elements are shown decoded here for clarity.
3.8 Terms relating to data quality
3.8.1
data quality
degree to which a set of inherent characteristics of data (3.2.2) fulfils requirements (3.1.2)
Note 1 to entry: See also quality (3.1.3).
3.8.2
data quality management
coordinated activities to direct and control an organization with regard to data quality (3.8.1)
3.8.3
data error
non-fulfilment of a data (3.2.2) requirement (3.1.2)
Note 1 to entry: In this term, “error” is synonymous with nonconformity (3.1.5).
3.8.4
data provenance record
record of the ultimate derivation and passage of a piece of data (3.2.2) through its various owners or
custodians
Note 1 to entry: A data provenance record can include information (3.2.1) about creation, update, transcription,
abstraction, validation (3.8.6), and transferring ownership of data.
3.8.5
verification
confirmation, through the provision of objective evidence (3.2.6), that specified requirements (3.1.2)
have been fulfilled
[SOURCE: ISO 9000:2015, 3.8.12, modified — Notes to entry have been removed.]
3.8.6
validation
confirmation, through the provision of objective evidence (3.2.6), that the requirements (3.1.2) for a
specific intended use or application (3.5.3) have been fulfilled
[SOURCE: ISO 9000:2015, 3.8.13, modified — Notes to entry have been removed.]
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3.8.7
authoritative data source
owner of a process (3.1.1) that creates data (3.2.2)
EXAMPLE The Department of Transportation of the Commonwealth of Pennsylvania, USA, is the
authoritative data source for Pennsylvania motor vehicle registration records.
3.8.8
accepted reference value
value that serves as an agreed-upon reference for comparison
Note 1 to entry: The accepted reference value is derived as:
a) a theoretical or established value, based on scientific principles;
b) an assigned or certified value, based on experimental work of some national or international organization;
c) a consensus or certified value, based on collaborative experimental work under the auspices of a scientific or
technical group;
d) the expectation, i.e. the mean of a specified set of measurements (3.4.2), when a), b) and c) are not available.
[SOURCE: ISO 3534-2:2006, 3.2.7]
3.8.9
true value
value that characterizes a characteristic perfectly defined in the conditions that exist when the
characteristic is considered
Note 1 to entry: The true value is a theoretical concept and, in general, cannot be known exactly.
[SOURCE: ISO 3534-2:2006, 3.2.5, modified.]
3.8.10
data accuracy
quality (3.1.3) of data (3.2.2) in respect of the represented value agreeing with the corresponding true
value (3.8.9) to a degree necessary for an intended purpose
EXAMPLE 1 When creating a data specification (3.6.3) to address data accuracy considerations, an organization
decides to include in the specification a requirement (3.1.2) for a length value to have three decimal places.
EXAMPLE 2 An inherent characteristic of some data is the use of three decimal places to represent a
length value.
Note 1 to entry: For data accuracy, the relevant inherent characteristics of the data are those that determine how
to interpret the value.
Note 2 to entry: No universal specification for data accuracy exists. Data accuracy depends on the details of the
data representation, the subject matter of the data and the purpose to which the user intends to put the data.
Note 3 to entry: In practice, when assessing data accuracy, an organization can make use of an accepted reference
value (3.8.8) rather than the true value.
Note 4 to entry: Not all aspects of data accuracy can be verified (3.8.5) by just assessing, as a closed system, the
consistency of the data and the applicable data specification. If the data, for example, represents the length of a
particular screw in a warehouse then the screw is in the real world, requiring an appropriate test to look beyond
the content of the data set and the data specification. Such testing is addressed by ISO 8000-8.
Note 5 to entry: ISO 8000-130 specifies the mechanisms by which an organization can state the accuracy of
data (including identification of the method that has assessed the data) or assert the accuracy of data (including
identification of the remediation that the organization will perform if the data in fact fails to meet the asserted
level of accuracy).
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3.8.11
data accuracy record
record of the information (3.2.1) provided about the data accuracy (3.8.10) of a specified data set (3.2.4)
Note 1 to entry: A data accuracy record can include representations and warranties of the data's accuracy.
3.8.12
data completeness
quality (3.1.3) of a data set (3.2.4) in respect of the content being all that is necessary for an intended
purpose
EXAMPLE 1 When creating a data specification (3.6.3) that addresses data completeness considerations, an
organization includes in the specification a requirement (3.1.2) for a data set to identify explicitly the applicable
unit of measure for each physical quantity in the set.
EXAMPLE 2 When calculating the average speed of a journey, a user decides to use the start and end times
of the journey and the total distance travelled. This decision determines the basis for data completeness of the
required data set.
EXAMPLE 3 When calculating the maximum speed during a journey, a user decides to use a list of points in time
and, for each point, the distance travelled to that point. The user decides an appropriate duration between each
point in time. This duration being longer makes the calculation less accurate but prevents the data set becoming
inappropriately large. These decisions determine the basis for data completeness of the required data set.
EXAMPLE 4 A buyer wants a supplier to send a list of all products (3.5.1) that are available for purchase. The
supplier uses ISO 8000-140, which specifies how to provide a statement to confirm the supplier has created a
data set representing a list that meets the buyer’s requirement.
Note 1 to entry: For data completeness, the relevant inherent characteristics of the data set are those that
determine which data (3.2.2) exist as part of the data set.
Note 2 to entry: No universal specification for data completeness exists. Data completeness depends on the content
of the data set, the subject matter of the data and the purpose to which the user intends to put the data set.
Note 3 to entry: Not all aspects of data completeness can be verified (3.8.5) by just assessing, as a closed system,
the consistency of the data set and the applicable data specification. If the data set claims, for example, to be a
complete list of the employees of an organization then the actual human beings are in the real world, requiring an
appropriate test to look beyond the content of the data set and the data specification. Such testing is addressed
by ISO 8000-8.
Note 4 to entry: ISO 8000-140 specifies the mechanisms by which an organization can state the completeness of
a data set (including identification of the method that has assessed the data) or assert the completeness of a data
set (including identification of the remediation that the organization will perform if the data in fact fails to meet
the asserted level of completeness).
3.8.13
data completeness record
record of the information (3.2.1) provided about the data completeness (3.8.12) of a specified data
set (3.2.4)
Note 1 to entry: A data completeness record can include representations and warranties of the data's
completeness.
3.9 Terms relating to syntax and semantics
3.9.1
formal syntax
specification of the valid sentences of a formal language using a formal grammar
EXAMPLE 1 An XML document type definition (DTD) is a formal syntax.
EXAMPLE 2 ISO 10303-21 contains a formal syntax in Wirth Syntax Notation (WSN) for ISO 10303 physical
files.
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Note 1 to entry: A formal language is computer-interpretable.
Note 2 to entry: Formal grammars are usually Chomsky context-free grammars.
Note 3 to entry: Variants of Backus-Naur Form (BNF) such as Augmented Backus-Naur Form (ABNF) and Wirth
Syntax Notation (WSN) are often used to specify the syntax of computer programming languages and data
(3.2.2) languages.
3.9.2
semantic encoding
technique of replacing natural language terms in a message with identifiers (3.3.1) that reference data
dictionary entries (3.6.1)
3.9.3
semantically coded data specification
data requirements statement
data specification (3.6.3) that uses entries from a data dictionary (3.6.2)
EXAMPLE 1 An ISO/TS 22745-30 compliant identification guide.
EXAMPLE 2 ISO 13584-501.
Note 1 to entry: A semantically coded data specification can
...