ISO/IEC 11179-1:2004

Information technology - Metadata registries (MDR) - Part 1: Framework

ISO/IEC 11179 specifies the kind and quality of metadata necessary to describe data, and it specifies the management and administration of that metadata in a metadata registry (MDR). It applies to the formulation of data representations, concepts, meanings, and relationships between them to be shared among people and machines, independent of the organization that produces the data. It does not apply to the physical representation of data as bits and bytes at the machine level. In ISO/IEC 11179, metadata refers to descriptions of data. ISO/IEC 11179 does not contain a general treatment of metadata. ISO/IEC 11179-1:2004 provides the means for understanding and associating the individual parts of ISO/IEC 11179 and is the foundation for a conceptual understanding of metadata and metadata registries.

Technologies de l'information — Registres de métadonnées (RM) — Partie 1: Cadre

General Information

• Status: Withdrawn
• Publication Date: 15-Sep-2004
• Withdrawal Date: 15-Sep-2004
• ICS: 35.040 - Information coding
• ICS: 35.040.50 - Automatic identification and data capture techniques
• Technical Committee: ISO/IEC JTC 1/SC 32 - Data management and interchange
• Drafting Committee: ISO/IEC JTC 1/SC 32/WG 2 - MetaData
• Current Stage: 9599 - Withdrawal of International Standard
• Start Date: 15-Dec-2015
• Completion Date: 30-Oct-2025

Relations

• Revised: ISO/IEC 11179-1:2015 - Information technology - Metadata registries (MDR) - Part 1: Framework
• Effective Date: 10-May-2012
• Revises: ISO/IEC 11179-1:1999 - Information technology - Specification and standardization of data elements - Part 1: Framework for the specification and standardization of data elements
• Effective Date: 15-Apr-2008

Standards Content (Sample)

INTERNATIONAL ISO/IEC
STANDARD 11179-1
Second edition
2004-09-15
Information technology — Metadata
registries (MDR) —
Part 1:
Framework
Technologies de l'information — Registres de métadonnées (RM) —
Partie 1: Cadre
Reference number
©
ISO/IEC 2004
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ii © ISO/IEC 2004 – All rights reserved

Contents Page
Foreword. iv
Introduction . v
1 Scope. 1
2 Normative references. 1
3 Terms and definitions. 1
3.1 Definitions of modeling constructs. 1
3.2 General terms used in this part of ISO/IEC 11179 . 2
3.3 Alphabetical list of terms used in the metamodel . 5
3.4 Specific terms used in this part of ISO/IEC 11179. 8
4 Abbreviations and acronyms. 9
5 Theory of terminology . 9
6 Metadata. 10
6.1 Concepts. 10
6.2 Fundamental model of data elements. 10
6.3 Data elements in data management and interchange. 12
6.4 Fundamental model of value domains. 12
6.5 Fundamentals of classification schemes. 15
7 Metadata registries. 16
7.1 General. 16
7.2 Overview model for an ISO/IEC 11179 MDR.16
7.3 Fundamentals of registration. 18
8 Overview of ISO/IEC 11179. 18
8.1 Introduction of parts . 18
8.2 Basic principles for applying ISO/IEC 11179. 20
9 Conformance. 21
Bibliography . 22

© ISO/IEC 2004 – All rights reserved iii

Foreword
ISO (the International Organization for Standardization) and IEC (the International Electrotechnical
Commission) form the specialized system for worldwide standardization. National bodies that are members of
ISO or IEC participate in the development of International Standards through technical committees
established by the respective organization to deal with particular fields of technical activity. ISO and IEC
technical committees collaborate in fields of mutual interest. Other international organizations, governmental
and non-governmental, in liaison with ISO and IEC, also take part in the work. In the field of information
technology, ISO and IEC have established a joint technical committee, ISO/IEC JTC 1.
International Standards are drafted in accordance with the rules given in the ISO/IEC Directives, Part 2.
The main task of the joint technical committee is to prepare International Standards. Draft International
Standards adopted by the joint technical committee are circulated to national bodies for voting. Publication as
an International Standard requires approval by at least 75 % of the national bodies casting a vote.
Attention is drawn to the possibility that some of the elements of this document may be the subject of patent
rights. ISO and IEC shall not be held responsible for identifying any or all such patent rights.
ISO/IEC 11179-1 was prepared by Technical Committee ISO/IEC JTC 1, Information technology,
Subcommittee SC 32, Data management and interchange.
This second edition cancels and replaces the first edition (ISO/IEC 11179-1:1999), which has been technically
revised.
ISO/IEC 11179 consists of the following parts, under the general title Information technology — Metadata
registries (MDR):
 Part 1: Framework
 Part 2: Classification
 Part 3: Registry metamodel and basic attributes
 Part 4: Formulation of data definitions
 Part 5: Naming and identification principles
 Part 6: Registration
iv © ISO/IEC 2004 – All rights reserved

Introduction
ISO/IEC 11179 - Metadata registries (MDR), addresses the semantics of data, the representation of data, and
the registration of the descriptions of that data. It is through these descriptions that an accurate understanding
of the semantics and a useful depiction of the data are found.
The purposes of ISO/IEC 11179 are to promote the following:
 Standard description of data
 Common understanding of data across organizational elements and between organizations
 Re-use and standardization of data over time, space, and applications
 Harmonization and standardization of data within an organization and across organizations
 Management of the components of data
 Re-use of the components of data
ISO/IEC 11179 is six part standard. Each part is devoted to addressing a different aspect of the needs listed
above. The parts and a short description follow:
 Part 1 – Framework – Contains an overview of the standard and describes the basic concepts
 Part 2 – Classification – Describes how to manage a classification scheme in a metadata registry
 Part 3 – Registry metamodel and basic attributes – Provides the basic conceptual model, including the
basic attributes and relationships, for a metadata registry
 Part 4 – Formulation of data definitions – Rules and guidelines for forming quality definitions for data
elements and their components
 Part 5 – Naming and identification principles – Describes how to form conventions for naming data
elements and their components
 Part 6 – Registration – Specifies the roles and requirements for the registration process in an
ISO/IEC 11179 metadata registry
Generally, descriptive data is known as metadata. That is, metadata is data that is used for describing other
data. As the use of the term has evolved, metadata now refers, generally, to data that is used for describing
some other objects. We limit the scope of the term as it is used here in ISO/IEC 11179 to descriptions of
data - the more traditional use of the term.
An MDR is a database of metadata that supports the functionality of registration. Registration accomplishes
three main goals: identification, provenance, and monitoring quality. Identification is accomplished by
assigning a unique identifier (within the registry) to each object registered there. Provenance addresses the
source of the metadata and the object described. Monitoring quality ensures that the metadata does the job it
is designed to do.
An MDR manages the semantics of data. Understanding data is fundamental to its design, harmonization,
standardization, use, re-use, and interchange. The underlying model for an MDR is designed to capture all
the basic components of the semantics of data, independent of any application or subject matter area.
© ISO/IEC 2004 – All rights reserved v

MDR's are organized so that those designing applications can ascertain whether a suitable object described in
the MDR already exists. Where it is established that a new object is essential, its derivation from an existing
description with appropriate modifications is encouraged, thus avoiding unnecessary variations in the way
similar objects are described. Registration will also allow two or more administered items describing identical
objects to be identified, and more importantly, it will identify situations where similar or identical names are in
use for administered items that are significantly different in one or more respects.
In ISO/IEC 11179 the basic container for data is called a data element. It may exist purely as an abstraction
or exist in some application system. In either case, the description of a data element is the same in
ISO/IEC 11179. Data element descriptions have both semantic and representational components. The
semantics are further divided into contextual and symbolic types.
The contextual semantics are described by the data element concept (DEC). The DEC describes the kinds of
objects for which data are collected and the particular characteristic of those objects being measured. The
symbolic semantics are described by the conceptual domain (CD). A CD is a set of categories, not
necessarily finite, where the categories represent the meaning of the permissible values in a value domain -
the allowed values for a data element.
The names, definitions, datatype, and related objects that are associated with a particular object in an MDR
give that object meaning. The depth of this meaning is limited, because names and definitions convey limited
information about an object. The relationships that object has with semantically related objects in a registry
provides additional information, but the additional information is dependent on how many semantically related
objects there are.
The representational component is about the permitted values a data element may use. Each value
corresponds to one of the categories in the CD. The set of these permitted values is called a value domain
(VD). A VD specifies all the values that are allowed either through an enumeration, a rule, or a combination of
these. The computational model the values follow is given by their datatype.
The semantic and representational components are described through attributes contained in the conceptual
model of a metadata registry as specified in ISO/IEC 11179-3. A metadata registry that conforms to
ISO/IEC 11179 can describe a wide variety of data. In fact, the attributes described in ISO/IEC 11179-3 are
data elements, and they can be registered in an ISO/IEC 11179 metadata registry. Moreover, any set of
descriptors or metadata attributes may be interpreted as data elements and registered in the metadata
registry.
There are two main consequences to this:
 The metadata registry can describe itself
 Metadata layers or levels are not defined in ISO/IEC 11179
As a result, ISO/IEC 11179 is a general description framework for data of any kind, in any organization, and
for any purpose. This standard does not address other data management needs, such as data models,
application specifications, programming code, program plans, business plans, and business policies. These
need to be addressed elsewhere.
The increased use of data processing and electronic data interchange heavily relies on accurate, reliable,
controllable, and verifiable data recorded in databases. One of the prerequisites for a correct and proper use
and interpretation of data is that both users and owners of data have a common understanding of the meaning
and descriptive characteristics (e.g., representation) of that data. To guarantee this shared view, a number of
basic attributes has to be defined.
vi © ISO/IEC 2004 – All rights reserved

The basic attributes specified are applicable for the definition and specification of the contents of data
dictionaries and interchanging or referencing among various collections of administered items. The "basic" in
basic attributes means that the attributes are commonly needed in specifying administered items completely
enough to ensure that they will be applicable for a variety of functions, such as
 design of information processing systems
 retrieval of data from databases
 design of EDI-messages for data interchange
 maintenance of metadata registries
 data management
 dictionary design
 dictionary control
 use of information processing systems
Basic also implies that they are independent of any
 application environment
 function of an object described by an administered item
 level of abstraction
 grouping of administered items
 method for designing information processing systems or data interchange messages
 MDR system
Basic does not imply that all attributes specified in ISO/IEC 11179-3 are required in all cases. Distinction is
made between those attributes that are mandatory, conditional, or optional.
© ISO/IEC 2004 – All rights reserved vii

INTERNATIONAL STANDARD ISO/IEC 11179-1:2004(E)

Information technology — Metadata registries (MDR) —
Part 1:
Framework
1 Scope
ISO/IEC 11179 specifies the kind and quality of metadata necessary to describe data, and it specifies the
management and administration of that metadata in a metadata registry (MDR). It applies to the formulation
of data representations, concepts, meanings, and relationships between them to be shared among people and
machines, independent of the organization that produces the data. It does not apply to the physical
representation of data as bits and bytes at the machine level.
In ISO/IEC 11179, metadata refers to descriptions of data. ISO/IEC 11179 does not contain a general
treatment of metadata. This part of ISO/IEC 11179 provides the means for understanding and associating the
individual parts and is the foundation for a conceptual understanding of metadata and metadata registries.
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 704:2000, Terminology work — Principles and methods
ISO 1087-1:2000, Terminology work — Vocabulary — Part 1: Theory and application
ISO/IEC 11179 (all parts), Information technology — Metadata registries (MDR)
3 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
3.1 Definitions of modeling constructs
This sub-clause defines the modeling constructs used in this part of ISO/IEC 11179.
3.1.1
attribute
characteristic of an object or entity
3.1.2
class
description of a set of objects that share the same attributes, operations, methods, relationships, and
semantics
[ISO/IEC 19501-1:2001, 2.5.2.9].
© ISO/IEC 2004 – All rights reserved 1

3.1.3
identifier (in Metadata Registry)
sequence of characters, capable of uniquely identifying that with which it is associated, within a specified
context
NOTE A name should be used as an identifier because it is not linguistically neutral.
3.1.4
relationship
connection among model elements
[ISO/IEC 19501-1:2001, 2.5.2.36].
3.2 General terms used in this part of ISO/IEC 11179
This sub-clause defines terms that have general usage beyond the specific needs of this part of
ISO/IEC 11179, but are not modeling constructs defined in 3.1.
3.2.1
basic attribute
attribute of a metadata item commonly needed in its specification
3.2.2
characteristic
abstraction of a property of an object or of a set of objects
NOTE Characteristics are used for describing concepts.
[ISO 1087-1:2000, 3.2.4].
3.2.3
concept
unit of knowledge created by a unique combination of characteristics
[ISO 1087-1:2000, 3.2.1].
3.2.4
concept system
set of concepts structured according to the relations among them
[ISO 1087-1:2000, 3.2.11]
3.2.5
conceptual data model
conceptual model
data model that represents an abstract view of the real world
NOTE A conceptual model represents the human understanding of a system.
3.2.6
data
re-interpretable representation of information in a formalized manner suitable for communication,
interpretation, or processing
NOTE Data can be processed by humans or by automatic means.
[ISO 2382-1:1993, 01.01.02].
2 © ISO/IEC 2004 – All rights reserved

3.2.7
data model
graphical and/or lexical representation of data, specifying their properties, structure and inter-relationships
3.2.8
definition
representation of a concept by a descriptive statement which serves to differentiate it from related concepts
[ISO 1087-1:2000, 3.3.1].
3.2.9
designation
representation of a concept by a sign which denotes it
[ISO 1087-1:2000, 3.4.1].
3.2.10
entity
any concrete or abstract thing that exists, did exist, or might exist, including associations among these things
EXAMPLE A person, object, event, idea, process, etc.
NOTE An entity exists whether data about it are available or not.
[ISO/IEC 2382-17:1999, 17.02.05].
3.2.11
essential characteristic
characteristic which is indispensable to understanding a concept
[ISO 1087-1:2000, 3.2.6].
3.2.12
extension

totality of objects to which a concept corresponds
[ISO 1087-1:2000, 3.2.8].
NOTE This term has a different meaning in ISO/IEC 11179-3.
3.2.13
general concept
concept which corresponds to two or more objects, which form a group by reason of common properties
NOTE Examples of general concepts are 'planet', 'tower'.
[ISO 1087-1:2000, 3.2.3]
3.2.14
individual concept
concept which corresponds to only one object
NOTE Examples of individual concepts are: 'Saturn', 'the Eiffel Tower'.
[ISO 1087-1:2000, 3.2.2].
© ISO/IEC 2004 – All rights reserved 3

3.2.15
intension

set of characteristics which makes up the concept
[ISO 1087-1:2000, 3.2.9].
3.2.16
metadata
data that defines and describes other data
3.2.17
metadata item
instance of a metadata object
3.2.18
metadata object
object type defined by a metamodel
3.2.19
metadata registry
MDR
information system for registering metadata
3.2.20
metamodel
data model that specifies one or more other data models
3.2.21
name
designation of an object by a linguistic expression
3.2.22
object
anything perceivable or conceivable
NOTE Objects may also be material (e.g. an engine, a sheet of paper, a diamond), immaterial (e.g. a conversion ratio,
a project plan), or imagined (e.g. a unicorn).
[ISO 1087-1:2000, 3.1.1].
3.2.23
registry item
metadata item recorded in a metadata registry
3.2.24
registry metamodel
metamodel specifying a metadata registry
3.2.25
terminological system
concept system with designations for each concept
4 © ISO/IEC 2004 – All rights reserved

3.3 Alphabetical list of terms used in the metamodel
This sub-clause provides definitions for terms used in this part of ISO/IEC 11179, which are the names of
metadata objects in the metamodel specified in ISO/IEC 11179-3.
3.3.1
administered item
registry item for which administrative information is recorded in an administration record
3.3.2
administration record
collection of administrative information for an administered item
3.3.3
administrative status
designation of the status in the administrative process of a registration authority for handling registration
requests
NOTE The values and associated meanings of “administrative status” are determined by each registration authority.
C.f. “registration status”.
3.3.4
classification scheme
descriptive information for an arrangement or division of objects into groups based on characteristics, which
the objects have in common
3.3.5
classification scheme item
CSI
item of content in a classification scheme.
NOTE This may be a node in a taxonomy or ontology, a term in a thesaurus, etc.
3.3.6
conceptual domain
CD
set of valid value meanings
NOTE The value meanings in a conceptual domain may either be enumerated or expressed via a description.
3.3.7
context
circumstance, purpose, and perspective under which an object is defined or used
NOTE This term has a different meaning in 11179-3.
3.3.8
data element
DE
unit of data for which the definition, identification, representation and permissible values are specified by
means of a set of attributes
3.3.9
data element concept
DEC
concept that can be represented in the form of a data element, described independently of any particular
representation
© ISO/IEC 2004 – All rights reserved 5

3.3.10
data identifier
DI
unique identifier for an administered item within a registration authority
3.3.11
datatype
set of distinct values, characterized by properties of those values and by operations on those values
[ISO/IEC 11404:1996, 4.11].
3.3.12
dimensionality
expression of measurement without units
NOTE A quantity is a value with an associated unit of measure. 32º Fahrenheit, 0º Celsius, $100 USD, and 10
reams (of paper) are quantities. Equivalence between two units of measure is determined by the existence of a quantity
preserving one-to-one correspondence between values measured in one unit of measure and values measured in the
other unit of measure, independent of context, and where characterizing operations are the same. Equivalent units of
measure in this sense have the same dimensionality. The equivalence defined here forms an equivalence relation on the
set of all units of measure. Each equivalence class corresponds to a dimensionality. The units of measure "temperature
in degrees Fahrenheit" and "temperature in degrees Celsius" have the same dimensionality, because for each value
measured in degrees Fahrenheit there is a value measured in degrees Celsius with the same quantity, and vice-versa.
The same operations may be performed on quantities in each unit of measure. Quantity preserving one-to-one
correspondences are the well-known equations Cº = (5/9)*(Fº - 32) and Fº = (9/5)*(Cº) + 32.
3.3.13
enumerated conceptual domain
conceptual domain that is specified by a list of all its value meanings
3.3.14
enumerated value domain
value domain that is specified by a list of all its permissible values
3.3.15
international code designator
ICD
identifier of an organization identification scheme
NOTE Based on ISO/IEC 6523-1:1998, 3.8.
3.3.16
item identifier
identifier for an item
3.3.17
item registration authority identifier
identifier of the registration authority registering the item
3.3.18
non-enumerated conceptual domain
conceptual domain that is not specified by a list of all valid value meanings
3.3.19
non-enumerated conceptual domain description
description or specification of a rule, reference, or range for a set of all value meanings for the conceptual
domain
3.3.20
non-enumerated value domain
value domain that is specified by a description rather than a list of all permissible values
6 © ISO/IEC 2004 – All rights reserved

3.3.21
non-enumerated value domain description
description or specification of a rule, reference, or range for a set of all permissible values for the value
domain
3.3.22
object class
set of ideas, abstractions, or things in the real world that are identified with explicit boundaries and meaning
and whose properties and behavior follow the same rules
3.3.23
organization
unique framework of authority within which a person or persons act, or are designated to act, towards some
purpose
[ISO/IEC 6523-1:1998, 3.1].
3.3.24
organization identifier
identifier assigned to an organization within an organization identification scheme, and unique within that
scheme
[ISO/IEC 6523-1:1998, 3.10].
3.3.25
organization part
any department, service, or other entity within an organization which needs to be identified for information
exchange
[ISO/IEC 6523-1:1998, 3.2].
3.3.26
organization part identifier
OPI
identifier allocated to a particular organization part
[ISO/IEC 6523-1:1998, 3.11].
3.3.27
organization part identifier source
source for the organization part identifier
NOTE Based on ISO/IEC 6523-1:1998, 3.12.
3.3.28
permissible value
expression of a value meaning allowed in a specific value domain
3.3.29
property
characteristic common to all members of an object class
3.3.30
registrar
representative of a registration authority
3.3.31
registration
relationship between an administered item and the registration authority
© ISO/IEC 2004 – All rights reserved 7

3.3.32
registration authority
RA
organization responsible for maintaining a register
3.3.33
registration authority identifier
identifier assigned to a registration authority
3.3.34
registration status
designation of the status in the registration life-cycle of an administered item
3.3.35
representation class
classification of types of representations
3.3.36
unit of measure
actual units in which the associated values are measured
NOTE The dimensionality of the associated conceptual domain must be appropriate for the specified unit of
measure.
3.3.37
value
data value
3.3.38
value domain
VD
set of permissible values
3.3.39
value meaning
meaning or semantic content of a value
NOTE Given a permissible value, representation of its value meaning shall be independent of (and shall not
constrain) the representation of its corresponding value.
3.3.42
value meaning description
description of a value meaning
3.3.43
version
unique version identifier of the administered item
3.4 Specific terms used in this part of ISO/IEC 11179
This sub-clause defines terms that have specific usage in this part of ISO/IEC 11179 and are not used in the
other parts.
3.4.1
data construct
object a metadata item describes
NOTE Individual data elements, value domains, data element concepts, conceptual domains, object classes, and
properties are data constructs.
8 © ISO/IEC 2004 – All rights reserved

3.4.2
quantity
value associated with a unit of measure
4 Abbreviations and acronyms
NOTE Some of the abbreviations or acronyms in this section represent terms defined in Clause 3.
CD -- Conceptual Domain
DE -- Data Element
DEC -- Data Element Concept
DI -- Data Identifier
EDI -- Electronic Data Interchange
IEC -- International Electrotechnical Commission
ICD -- International Code Designator
ISO -- International Organization for Standardization
JTC1 -- Joint Technical Committee 1
MDR -- Metadata Registry
OPI -- Organization Part Identifier
RA -- Registration Authority
SC32 --  ISO/IEC JTC1/Sub-committee 32
5 Theory of terminology
The concepts from the theory of terminology that are used in ISO/IEC 11179 shall be in conformity with
ISO 704 and ISO 1087-1. A short description of the necessary theory follows.
In the theory of terminology, an object is something conceivable or perceivable. Concepts are mental
constructs, units of thought, or unit of knowledge created by a unique combination of characteristics.
Concepts are organized or grouped by common elements, called characteristics. Essential characteristics
are indispensable to understanding a concept. Other characteristics are inessential. The sum of
characteristics that constitute a concept is called its intension. The set of objects a concept refers to is its
extension.
In natural language, concepts are expressed through definitions, which specify a unique intension and
extension.
A designation (term, appellation, or symbol) represents a concept.
A general concept has two or more objects that correspond to it. An individual concept has one object that
corresponds to it. That is, a general concept has two or more objects in its extension, and an individual
concept has one object in its extension.
A concept system is set of concepts structured according to the relations among them. A terminological
system is a concept system with designations for each concept.
© ISO/IEC 2004 – All rights reserved 9

6 Metadata
6.1 Concepts
For ISO/IEC 11179, metadata is defined to be data that defines and describes other data. This means that
metadata are data, and data become metadata when they are used in this way. This happens under
particular circumstances, for particular purposes, and with certain perspectives, as no data are always
metadata. The set of circumstances, purposes, or perspectives for which some data are used as metadata is
called the context. So, metadata are data about data in some context.
Since metadata are data, then metadata can be stored in a database and organized through the use of a
model. Some models are very application specific, and others are more general. The model presented and
described in ISO/IEC 11179-3 (Registry metamodel and basic attributes) is general. It is a representation of
the human understanding of the metadata needed to describe data constructs, including the relationships
that exist among that metadata, and not necessarily how the metadata will be represented in an application of
an MDR. A model of this kind is called a conceptual model. Conceptual models are meant for people to
read and understand.
Models that describe metadata are often referred to as metamodels. The conceptual model presented in
ISO/IEC 11179-3 is a metamodel in this sense.
6.2 Fundamental model of data elements
Figure 1 illustrates the ideas conveyed in this sub-clause. The figure itself is not normative, but it is used to
illustrate the basic ideas.
For the purposes of ISO/IEC 11179, a data element is composed of two parts:
 Data element concept – A DEC is concept that can be represented in the form of a data element,
described independently of any particular representation.
 Representation – The representation is composed of a value domain, datatype, units of measure (if
necessary), and representation class (optionally).
From a data modeling perspective and for the purposes of ISO/IEC 11179, a data element concept may be
composed of two parts:
 The object class is a set of ideas, abstractions, or things in the real world that can be identified with
explicit boundaries and meaning and whose properties and behavior follow the same rules
 The property is a characteristic common to all members of an object class
Object classes are the things for which we wish to collect and store data. They are concepts, and they
correspond to the notions embodied in classes in object-oriented models and entities in entity-relationship
models. Examples are cars, persons, households, employees, and orders. Properties are what humans use
to distinguish or describe objects. They are characteristics, not necessarily essential ones, of the object class
and form its intension. They are also concepts, and they correspond to the notions embodied in attributes
(without associated datatypes) in object-oriented or entity-relationship models. Examples of properties are
color, model, sex, age, income, address, or price.
An object class may be a general concept. This happens when the set of objects corresponding to the object
class has two or more members. The examples in the previous paragraph are of this type. Record level data
are described this way. On the other hand, an object class may be an individual concept. This happens
when the set of objects corresponding to the object class has one member. Examples are concepts
corresponding to single objects, such as "the set of persons in the US" or "the set of service sector
establishments in Australia". Aggregate data are described this way. Examples of properties are average
income or total earnings.
10 © ISO/IEC 2004 – All rights reserved

It is important to distinguish an actual object class or property from its name. This is the distinction between
concepts and their designations. Object classes and properties are concepts; their names are designations.
Complications arise because people convey concepts through words (designations), and it is easy to confuse
a concept with the designation used to represent it. For example, most people will read the word income and
be certain they have unambiguously interpreted it. But, the designation income may not convey the same
concept to all readers, and, more importantly, each instance of income may not designate the same concept.
Not all ideas are simply expressed in a natural language, either. For example, "women between the ages of
15 and 45 who have had at least one live birth in the last 12 months" is a valid object class not easily named
in English.  Some ideas may be more easily expressed in one language than in another.  The German word
Götterdämmerung has no simple English equivalent.
A data element is produced when a representation is associated with a data element concept. The
representation describes the form of the data, including a value domain, datatype, representation class
(optionally), and, if necessary, a unit of measure. Value domains are sets of permissible values for data
elements. For example, the data element representing annual household income may have the set of non-
negative integers (with units of dollars) as a set of valid values. This is its value domain.
A data element concept may be associated with different value domains as needed to form conceptually
similar data elements. There are many ways to represent similar facts about the world, but the concept for
which the facts are examples is the same. Take the DEC country of person's birth as an example.
ISO 3166-1 – Country Codes contains seven different representations for countries of the world. Each one of
these seven representations contains a set of values that may be used in the value domain associated with
the DEC. Each one of the seven associations is a data element. For each representation of the data, the
permissible values, the datatype, the representation class, and possibly the units of measure, are altered.
See ISO/IEC 20943-1:2003, Information technology — Procedures for achieving metadata registry content
consistency — Part 1: Data elements for details about the registration and management of descriptions of
data elements.
DATA ELEMENT CONCEPT DATA ELEMENT
(1:N) (1:N)
Object Class Object Class
(1:N)
(1:1) (1:1)
Property Property
(1:1)
Representation
This figure is for informational purposes only. It is not normative.
Figure 1 — Fundamental model for data elements

© ISO/IEC 2004 – All rights reserved 11

6.3 Data elements in data management and interchange
Figure 2 provides a simplified picture to illustrate those situations in which data elements lie. Data elements
appear in databases, files, and transaction sets. Data elements are the fundamental units of data an
organization manages, therefore they must be part of the design of databases and files within the organization
and all transaction sets the organization builds to communicate data to other organizations.
Within the organization, databases or files are composed of records, segments, tuples, etc., which are
composed of data elements. The data elements themselves contain various kinds of data that include
characters, images, sound, etc.
When the organization needs to transfer data to another organization, data elements are the fundamental
units that make up the transaction sets. Transactions occur primarily between databases or files, but the
structure (i.e. the records or tuples) of the files and databases don't have to be the same across organizations.
So, the common unit for transferring information (data plus understanding) is the data element.
Database, File, Etc. Transaction, Exchange Unit, Etc. Database, File, Etc.
Class, Tuple, Etc.
Data Element
Identifier
Definition
Name
Value Domain
Etc.
Field,Column, Etc
.
Character, Image,
Sound, Etc.
This figure is for informational purposes only. It is not normative.
Figure 2 — Data elements and other data concepts

6.4 Fundamental model of value domains
Figure 3 illustrates the ideas conveyed in this sub-clause. The figure itself is not normative, but it is used to
illustrate the basic ideas.
12 © ISO/IEC 2004 – All rights reserved

A value domain is a set of permissible values. A permissible value is a combination of some value and the
meaning for that value. The associated meaning is called the value meaning. A value domain is the set of
valid values for one or more data elements. It is used for validation of data in information systems and in data
exchange. It is also an integral part of the metadata needed to describe a data element. In particular, a value
domain is a guide to the content, form, and structure of the data represented by a data element.
Value domains come in two (non-exclusive) sub-types:
 Enumerated value domain – A value domain specified as a list of permissible values (values and their
meanings)
 Non-enumerated value domain – A value domain specified by a description
An enumerated value domain contains a list of all its values and their associated meanings. Each value and
meaning pair is called a permissible value. The meaning for each value is called the value meaning.
A non-enumerated value domain is specified by a description. The non-enumerated value domain
description describes precisely which permissible values belong and which do not belong to the value
domain. An example of a description is the phrase "Every real number greater than 0 and less than 1".
Each value domain is a member of the extension of a concept, called the conceptual domain. A conceptual
domain is a set of value meanings. The intension of a conceptual domain is its value meanings. Many value
domains may be in the extension of the same conceptual domain, but a value domain is associated with one
conceptual domain. Conceptual domains may have relationships with other conceptual domains, so it is
possible to create a concept system of conceptual domains. Value domains may have relationships with other
value domains, which provide the framework to capture the structure of sets of related value domains and
their associated concepts.
Conceptual domains, too, come in two (non-exclusive) sub-types:
 Enumerated conceptual domain – A conceptual domain specified as a list of value meanings
 Non-enumerated conceptual domain – A conceptual domain specified by a description
The value meanings for an enumerated conceptual domain are listed explicitly. This conceptual domain type
corresponds to the enumerated type for value domains. The value meanings for a non-enumerated
conceptual domain are expressed using a rule, called a non-enumerated conceptual domain description.
Thus, the value meanings are listed implicitly. This rule describes the meaning of permissible values in a non-
enumerated value domain. This conceptual domain type corresponds to the non-enumerated type for value
domains. See ISO/IEC TR 20943-3, Information technology — Procedures for achieving metadata registry
content consistency — Part 3: Value domains for detailed examples.
A unit of measure is sometimes required to describe data. If temperature readings are recorded in a database,
then the temperature scale (e.g., Fahrenheit or Celsius) is necessary to understand the meaning of the values.
Another example is the mass of rocks found on Mars, measured in grams. However, units of measure are not
limited to physical quantities, as currencies (e.g., US dollars, Lire, British pounds) and other socio-economic
measures are units of measure, too.
Some units of measure are equivalent to each other in the following sense: Any quantity in one unit of
measure can be transformed to the same quantity in another unit of measure. All equivalent units of measure
are said to have the same dimensionality. For example, currencies all have the same dimensionality.
Measures of speed, such as miles per hour or meters per second, have the same dimensionality. Two units
of measure that are often erroneously seen as having the same dimensionality are pounds (as in weight) and
grams. Pounds is a measure of force, and grams is a measure of mass.
A unit of measure is associated with a value domain, and the dimensionality is associated with the conceptual
domain.
© ISO/IEC 2004 – All rights reserved 13

Some value domains contain very similar values from one domain to another. Either the values themselves
are similar or the meanings of the values are the same. When these similarities occur, the value domains
may be in the extension of one conceptual domain. The following examples illustrate this and the other ideas
in this sub-clause:
...