ISO 8000-100:2016

INTERNATIONAL ISO
STANDARD 8000-100
First edition
Data quality —
Part 100:
Master data: Exchange of
characteristic data: Overview
Qualité des données —
Partie 100: Données permanentes: Échange des données
caractéristiques: Aperçu général
PROOF/ÉPREUVE
Reference number
©
ISO 2016
© ISO 2016, Published in Switzerland
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ii © ISO 2016 – All rights reserved

Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 2
4 Abbreviated terms . 2
5 Master data . 2
6 Data architecture for master data . 4
7 High-level data model . 5
7.1 General . 5
7.2 Diagram . 6
7.3 Entities . 6
7.3.1 data_dictionary . 6
7.3.2 data_dictionary_entry . 7
7.3.3 data_record . 7
7.3.4 data_set . 7
7.3.5 data_object . 7
7.3.6 data_object_accuracy_event. 8
7.3.7 data_object_completeness_event . 8
7.3.8 data_object_provenance_event . 8
7.3.9 property_value_assignment . 8
8 Overview of the master data quality series of parts of ISO 8000 . 9
Annex A (normative) Document identification .11
Annex B (informative) Categories of items .12
Bibliography .14
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 on 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 the following URL: www.iso.org/iso/foreword.html.
The committee responsible for this document is Technical Committee ISO/TC 184, Automation systems
and integration, Subcommittee SC 4, Industrial data.
This first edition of ISO 8000-100 cancels and replaces ISO/TS 8000-100:2009, which has been
technically revised.
ISO 8000 is organized as a series of parts, each published separately. The structure of ISO 8000 is
described in ISO/TS 8000-1.
Each part of ISO 8000 is a member of one of the following series: general data quality, master data
quality, transactional data quality, and product data quality. This part of ISO 8000 is a member of the
master data quality series.
A list of all parts in the ISO 8000 series can be found on the ISO website.
iv PROOF/ÉPREUVE © ISO 2016 – All rights reserved

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.
The master data quality series of parts of ISO 8000 addresses the quality of master data. This part of
ISO 8000 is an introduction to the series. It contains an introduction to master data, a data architecture,
a high-level data model, and an overview of the remaining parts of the series.
Annex A contains an identifier that unambiguously identifies this part of ISO 8000 in an open
information system.
Annex B describes different categories of items and their identifiers.
INTERNATIONAL STANDARD ISO 8000-100:2016(E)
Data quality —
Part 100:
Master data: Exchange of characteristic data: Overview
1 Scope
This part of ISO 8000 contains an overview of the master data quality series of parts of ISO 8000, which
addresses master data quality.
The following are within the scope of the master data quality series of parts of ISO 8000:
— master data-specific aspects of quality management systems;
— master data quality metrics.
The approach of the master data quality series of parts of ISO 8000 is to address data quality:
— from the bottom up, i.e. from the smallest meaningful element, the property value;
— at the interface of master data management systems, not within the systems.
The master data quality series of parts of ISO 8000 contains requirements that can be checked by
computer for the exchange, between organizations and systems, of master data that consists of
characteristic data. These parts address the quality of property values that are exchanged within
master data messages.
This part of ISO 8000 describes fundamentals of master data quality and specifies requirements on
both data and organizations to enable master data quality.
The following are within the scope of this part of ISO 8000:
— specification of the scope of the master data quality series of parts of ISO 8000;
— introduction to master data;
— description of the data architecture;
— overview of the content of the other parts of the series.
The following are outside the scope of this part of ISO 8000:
— aspects of data quality that apply to all data regardless of whether they are master data;
— aspects of data quality that apply to data that are not master data.
EXAMPLE Transaction data are not considered to be master data.
2 Normative references
The following referenced documents are indispensable for the application 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.
4 Abbreviated terms
MDR master data record
UML Unified Modeling Language
5 Master data
Within an organization, master data is used to identify and describe things that are significant to the
organization.
NOTE 1 In cataloguing applications, master data are used to describe things called “items”.
Figure 1 depicts a taxonomy of data, showing where master data fits.
NOTE 2 Figure 1 is not intended to be a complete taxonomy of data; it is only intended to show the context of
master data.
Figure 1 — Taxonomy of data (for master data)
Master data is typically referenced in business transactions through an identifier. The identifier is
commonly a reference both to the thing itself and to a master data record (MDR) that describes the
thing. The MDR is commonly held in a central repository.
EXAMPLE 1 It is common for the central repository of MDRs for an organization to be the organization’s
enterprise resource planning (ERP) or master data management (MDM) system.
NOTE 3 What is logically a single MDR can be represented by several physical records in a software system.
EXAMPLE 2 In a relational database implementation, a master data record could consist of rows from several
different tables.
NOTE 4 A MDR that describes something can be identified via a reference using its identifier. Something can
be described by characteristic data, represented by property values. Additionally, something can be described by
descriptive strings or definitions.
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Identifying references are designed to be used as references to master data held by others.
EXAMPLE 3 A corporate tax identifier, an individual’s national insurance number, and a part number assigned
by a manufacturer to an item of production are all examples of identifying references.
In order for an identifying reference to be meaningful, it shall be associated with a system of
identification.
EXAMPLE 4 The organization that issued the identifier can be specified by the metadata, as is common in tax
identifiers, but a part number is meaningless if the manufacturer that issued it is not known.
A description can be computer interpretable characteristic data, which is typically represented as
property values, or human readable text. Some properties are differentiating. Because of the ease with
which they can be processed, numerical or controlled values are most often used as differentiating.
One of the key aspects of managing master data quality is managing duplication. A consistent approach
to managing and eliminating inappropriate duplication is a critical part of master data management.
A characteristic that is considered differentiating by one organization could be considered non-
differentiating by another organization.
EXAMPLE 5 A manufacturer would have a different master data record for each of its items of production.
When, from a buyer’s perspective, several items of production (produced by the same manufacturer or different
manufacturers) share the same characteristics of fit, form and function, the buyer may group under a single item
of supply and assign a “stock number” as the identifying reference for the item of supply. In grouping several
items of production as a single item of supply, the buyer is making a decision to consider as non-differentiating
one or more characteristics that the manufacturer(s) consider differentiating.
A characteristic that is considered differentiating by one function within an organization may be
considered non-differentiating by another function within the same organization.
Master data is not necessarily static. Also, the number of characteristics needed to describe something
will vary by business function. As the number of differentiating characteristics various, MDRs may have
to be differentiated when characteristics are added or changed to differentiating. MDRs may become
duplicates when characteristics are removed or changed to be non-differentiating.
Examples of master data include:
— vendor master: This typically describes a vendor in term of its location and legal status. Much of
the mandatory data in a vendor master is prescribed by law as it is a common requirement for a
company to be able to identify all entities to which it has transferred funds.
— customer master: This typically describes a customer in terms of a trading entity. At a minimum it
will include the contact information necessary to transmit invoices and may contain confidential
information such as credit card information.
NOTE 5 If personal data are maintained in a customer master, it can be subject to data protection
legislation.
— item or material master: These masters typically describe tangible items that are tracked, inventoried
or regularly purchased. While they are often restricted to items purchased under contract such as
production materials they can also be used to improve the quality of spend analysis associated with
maintenance, repair and operations (MRO) purchases. Material masters are also commonly used
to support bills of materials (BOM) or to in design where they may be referred to as common parts
catalogue or a preferred part list. A variation of the material master is an illustrated parts catalogue
(IPC) or a spare parts list.
— item of supply concept: These masters include a reference to an item or material master, plus
packaging and quantity information;
— service, procedure or process master: These masters are still relatively rare except in the health
care and vehicle repair industries where automated billing for services or insurance reimbursement
is common. Typically a service is best described as a procedure or a process.
EXAMPLE 6 The American Medical Association’s Current Procedural Terminology-4 (CPT-4) codes is an
example of a procedure master.
— asset master: These masters are commonly used to track items whose purchase price is over
a preset monetary value, or whose cost is depreciated over several years. Assets are commonly
associated with a unique identifier (serial number) and often associated with movable items where
date (time occasionally) and location need to be verified and reported. Correct modelling of an asset
master is impo
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