ISO 8000-110:2021

INTERNATIONAL ISO
STANDARD 8000-110
Second edition
2021-11
Data quality —
Part 110:
Master data: Exchange of
characteristic data: Syntax, semantic
encoding, and conformance to data
specification
Qualité des données —
Partie 110: Données permanentes: Échange des données
caractéristiques: Syntaxe, sémantique, encodage et conformité aux
spécifications de données
Reference number
ISO 8000-110:2021(E)
© ISO 2021

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ISO 8000-110:2021(E)
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ISO 8000-110:2021(E)
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 2
3 Terms and definitions . 2
4 Fundamental concepts and assumptions . 2
5 Objectives . 4
6 Syntax . 5
7 Semantic encoding .5
7.1 General requirements . 5
7.1.1 Level 1 requirements. 5
7.1.2 Level 2 requirements. 6
7.2 Requirements for all property-value tuples . 7
7.3 Requirements for values of properties that are quantities . 7
7.3.1 Scope of requirements. 7
7.3.2 Representation of units of measurement . 8
7.3.3 Representation of qualifiers of measurement. 10
7.4 Requirements for currency amounts . 13
8 Conformance to the data specification .14
9 Conformance requirements .16
Annex A (normative) Document identification .17
Annex B (informative) Example of a schema that can be used to exchange master data that
are characteristic data .18
Bibliography .19
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ISO 8000-110:2021(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 second edition cancels and replaces the first edition (ISO 8000-110:2009), which has been
technically revised.
The main changes are as follows:
— removing broken Uniform Resource Locators;
— updating normative references, figures and tables;
— replacing the term “data value” with the term “value tuple”;
— replacing the terms “property value” and “property value pair” with the term “property-value
tuple”;
— adding an Annex B referencing an example of a schema for exchanging master data that are
characteristic data;
— editorial corrections to language, grammar and document layout.
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 8000-110:2021(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
1)
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. 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 use but not for another. This difference occurs when the requirements are different
between the two uses.
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 8000-1 identifies that data have syntactic (format), semantic (meaning) and pragmatic
(usefulness) characteristics.
1) https://sdgs.un.org/goals
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ISO 8000-110:2021(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 This document specifies how to exchange characteristic data that are master data.
— monitoring and measuring data and information quality;
EXAMPLE 7 ISO 8000-8 specifies approaches to measuring data and information 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, however, requires
additional information 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 supports the creation
and exchange of high-quality data. This document contains requirements necessary but not sufficient
to achieve data quality with respect to the exchange of master data. The requirements do not cover
issues such as addressing the accuracy, provenance and completeness of master data. These issues need
to be part of an overall data quality strategy adopted by each organization.
"Organization" does not necessarily mean a single, complete company or corporation. The organization
can be a subdivision or branch that covers some distinct area of business operation.
When different business units of a company exchange master data or when a business unit exchanges
master data with headquarters, these business units are organizations for the purposes of this
document.
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;
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ISO 8000-110:2021(E)
— 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.
2)
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).
Annex A of this document contains an identifier that unambiguously identifies this document in an
open information system.
Annex B of this document references an example of a schema to enable exchange of master data that are
characteristic data.
2) The content is available on the ISO Online Browsing Platform: https://www.iso.org/obp
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INTERNATIONAL STANDARD ISO 8000-110:2021(E)
Data quality —
Part 110:
Master data: Exchange of characteristic data: Syntax,
semantic encoding, and conformance to data specification
1 Scope
This document specifies requirements for the exchange of messages that contain master data consisting
of characteristic data. These requirements can be checked by computer. The messages are suitable for
exchange between organizations and between systems.
EXAMPLE 1 A supplier sends a message to a customer. The message contains characteristic data describing an
item that the customer is considering buying.
The following are within the scope of this document:
— conformance of master data messages to a formal syntax;
— semantic encoding of master data messages;
— conformance of master data messages to data specifications;
— requirements on access to the data dictionaries that enable decoding of master data messages.
The following are outside the scope of this document:
— master data that are not characteristic data;
— data that are not in messages;
— messages that do not exchange master data between organizations or systems;
EXAMPLE 2 A merchant sends a message to a credit card company. The message represents a credit
charge transaction and does not exchange master data between the organizations.
— recording the provenance of master data;
EXAMPLE 3 ISO 8000-120 addresses the capture and exchange of data provenance information.
— accuracy of master data;
EXAMPLE 4 ISO 8000-130 addresses the representation and exchange of information about the
accuracy of master data that consists of characteristic data.
— exchange of data that are not master data;
EXAMPLE 5 ISO 8000-140 addresses the representation and exchange of information about the
completeness of master data that consists of characteristic data.
— management of master data internally within an organization;
EXAMPLE 6 Data within an organization's enterprise resource planning or product data management
system is out of scope.
EXAMPLE 7 Making backup copies of data files containing master data is out of scope.
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ISO 8000-110:2021(E)
— quality of data dictionaries;
— a specific formal syntax for the exchange of master data.
EXAMPLE 8 The ISO 9735 series, the ISO 13584 series, the ISO 15926 series and the ISO 22745 series
specify formats that enable exchange of master data.
The requirements in this document are considered necessary but not sufficient to achieve data quality
with respect to exchange of master data. Issues such as the accuracy and provenance of master data
also need to be addressed as part of an overall data quality strategy.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements of this document. For dated references, only the edition cited applies. For
undated references, the latest edition of the referenced document (including any amendments) applies.
ISO 8000-2, Data quality — Part 2: Vocabulary
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO 8000-2 apply.
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/
4 Fundamental concepts and assumptions
While the bit is the fundamental building block of electronically stored data, the property-value tuple is
the fundamental building block of electronically stored characteristic data.
A value tuple by itself lacks the context to ensure unambiguous understanding of what the value
represents. The context can be represented by a property label.
EXAMPLE 1 ISO 3601-1 specifies the inside diameters, cross-sections, tolerances and designation codes for
O-rings used in fluid power systems for general industrial and aerospace applications. O-rings are endless,
ring-shaped sealing elements with a circular cross-section that are manufactured from elastomer materials
or PTFE. The designation of an O-ring is derived from the dimensions of its inner diameter and cord width in
millimetres, along with the name of the material and its Shore A hardness (e.g, “100,00x2,65. NBR 70”).
In this example, the full textual description for the O-ring would be an O-ring, part number 100,00x2,65
NBR 70 having an inside diameter of 100 millimetres, a cross-section of 2,65 millimetres, with a shore
A hardness of 70 on the durometer scale, manufactured using nitrile-butadiene rubber (NBR), coloured
black, that can be used in an operating temperature range of −30 °C, to +70 °C. The O-ring sizes and
tolerances conform to ISO 3601-1.
This natural language statement of the characteristic data can be decomposed into the elements shown
in Table 1. The first column comprises the property labels; the second column comprises the value
tuples.
Table 1 — Example characteristic data for an O-ring
Property label Value tuple
INNER DIAMETER 100 MILLIMETRES
CROSS SECTION 2,65 MILLIMETRES
SHORE HARDNESS RATING 70 DUROMETER
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ISO 8000-110:2021(E)
Table 1 (continued)
Property label Value tuple
MATERIAL NITRILE-BUTADIENE RUBBER (NBR)
COLOUR BLACK
OPERATING TEMPERATURE RANGE -30 °C TO +100 °C
MANUFACTURER CODE 100,00X2,65 NBR 70
STANDARD ISO 3601-1
Using property labels has the following disadvantages:
— the labels are in a single language, which can prevent understanding of the data by speakers of other
languages;
— the labels are susceptible to variations in spelling, letter case, punctuation, etc., making it difficult
for a computer application to understand the characteristic data;
— the labels are not defined, which can result in differing interpretations between the sender and
receiver.
To address these problems, this document requires the use of property-value tuples when exchanging
master data messages that contain characteristic data. Each property-value tuple consists of a value
tuple and, to establish the context of that value, a reference to a data dictionary entry that specifies the
property. The entry contains terms and definitions of the property in one or more languages.
It follows that, as property-value tuples are the fundamental building blocks of electronically stored
information, the quality of the property-value tuples is one of the determinants of the quality of the
information.
Semantic encoding produces messages that contain property-value tuples where each reference to a
data dictionary entry is in the form of an unambiguous identifier.
Use of a data dictionary is the foundation for semantic encoding, which, in combination with identifying
the applicable syntax for a data set, establishes that data as being portable. Portable data can pass from
one system to another reliably because the receiver can guarantee being able to process the format and
the meaning of the data.
To ensure data are portable without subsequent claims of ownership by third parties, organizations
choose a data dictionary that has appropriate licence conditions.
The remainder of this document specifies how to create portable data that conform to applicable data
specifications.
For the parts of the ISO 8000 series where those parts address master data, a foundational data
architecture supports the exchange of data without loss of content or meaning (see Figure 1).
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ISO 8000-110:2021(E)
Figure 1 — Data architecture for master data as specified by the ISO 8000 series
The data architecture establishes the basis for consistent, high quality master data. This basis includes
the data dictionary and data specifications as key elements.
EXAMPLE 2 A data dictionary can take many forms including: a concept dictionary (see ISO/TS 29002-6);
an open technical dictionary (see ISO/TS 22745-10), a reference data library (see ISO/TS 15926-4) and; a parts
library (see the ISO 13584 series). In the case of ISO/TS 15926-4 and the ISO 13584 series, the data dictionary
includes elements of the data specification.
EXAMPLE 3 A data specification can take many forms including: an identification guide (see ISO/TS 22745-30);
a reference data item (see ISO/TS 15926-4); a product characterization class (see ISO 13584-42) and; a class (see
IEC 61360-4 DB).
In addition to the data dictionary and data specifications, exchange of master data requires a formal
syntax and an identification scheme.
EXAMPLE 4 Formal syntaxes include: eXtensible Markup Language (XML) (see ISO/TS 29002-10); the clear
text encoding specified by ISO 10303-21.
EXAMPLE 5 ISO/TS 29002-5 specifies an identification scheme in the form of an internationally recognized
data identifier (IRDI). This identifier is a unique identifier that identifies administered items, each of which is
either a concept or a concept information element. ISO/TS 29002-5 is specialized by ISO 22745-13, which uses
the term “metadata object” to refer to administered items that are relevant to open technical dictionaries.
ISO/TS 29002-5 enables interoperability between implementations of the ISO 13584 series for parts libraries
and the ISO 22745 series for open technical dictionaries.
5 Objectives
Clauses 6 to 8 contain requirements that enable organizations to achieve the following objectives.
a) The receiver of a master data message is able to determine the meaning of the message and the
context in which the values in the message are valid.
b) Using a computer, the receiver is able to check automatically the correctness of the master data
message against each referenced formal syntax and each referenced data specification.
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ISO 8000-110:2021(E)
6 Syntax
Each master data message shall contain a reference to one or more formal syntaxes to which the master
data message conforms. The reference shall be in the form of an unambiguous identifier for the specific
version of the formal syntax that was used to encode the master data message. Each formal syntax shall
be available to all interested parties. If the master data are offered to the public, all the formal syntax
shall be publicly available. Each formal syntax should be available at a reasonable cost.
NOTE 1 Referencing more than one formal syntax is useful when one standard restricts the capability of
the syntax defined in another standard while remaining compatible with the latter. In this case, users of both
standards can decode the same master data message.
NOTE 2 It is not required that a formal syntax be free of charge.
NOTE 3 Valid syntaxes include those that use encryption to protect the confidentiality of content.
EXAMPLE 1 Examples of publicly-available formal syntaxes are given in Table 2.
EXAMPLE 2 A reference to the English language as the syntax does not satisfy the requirements of this clause.
EXAMPLE 3 For a message that conforms to ISO/TS 29002-10, the message includes a reference to the syntax
using the following eXtensible Markup Language (XML) element:
xmlns:cat="urn:iso:std:iso:ts:29002:-10:ed-1:tech:xml-schema:catalogue"
xmlns:val="urn:iso:std:iso:ts:29002:-10:ed-1:tech:xml-schema:value"
xmlns:bas="urn:iso:std:iso:ts:29002:-4:ed-1:tech:xml-schema:basic"
xmlns:id="urn:iso:std:iso:ts:29002:-5:ed-1:tech:xml-schema:identifier"
xsi:schemaLocation="urn:iso:std:iso:ts:29002:-10:ed-1:tech:xml-schema:catalogue catalogue.
xsd">
Table 2 — Examples of publicly-available formal syntaxes
Designation Title
ISO 9735 (all parts) Electronic data interchange for administration, commerce and transport (EDI-
FACT) — Application level syntax rules
ISO 13584-25 Industrial automation systems and integration — Parts library — Part 25: Logical
resource: Logical model of supplier library with aggregate values and explicit con-
tent
ISO/TS 13584-35 Industrial automation systems and integration — Parts library — Part 35: Imple-
mentation resources: Spreadsheet interface for parts library
ISO/TS 22745-40 Industrial automation systems and integration — Open technical dictionaries and
their application to master data — Part 40: Master data representation
7 Semantic encoding
7.1 General requirements
7.1.1 Level 1 requirements
To achieve effective semantic encoding, each property-value tuple shall consist of a combination
of references to data dictionary entries and of values, where the combination is sufficient to achieve
unambiguous understanding of what the value tuple represents.
NOTE 1 In order to understand the meaning of a property-value tuple, it is necessary to know the data type of
its value. This data type is repres
...