ISO/TR 25100:2012
(Main)Intelligent transport systems - Systems architecture - Harmonization of ITS data concepts
Intelligent transport systems - Systems architecture - Harmonization of ITS data concepts
ISO TR 25100:2012 provides guidance on the harmonisation of data concepts that are being managed by data registry and data dictionaries such as those described in ISO 14817:2002. ISO TR 25100:2012 describes processes for harmonisation of such data concepts to arrive at preferred definitions for use in formal standards, specifications, technical reports and information models. It is based on consideration of a harmonisation process used by international groups involved in the ITS sector and in the wider sector of transport and logistics information and control systems.
Systèmes intelligents de transport — Architecture des systèmes — Harmonisation des concepts de données SIT
General Information
- Status
- Published
- Publication Date
- 12-Sep-2012
- Technical Committee
- ISO/TC 204 - Intelligent transport systems
- Drafting Committee
- ISO/TC 204/WG 1 - Architecture
- Current Stage
- 6060 - International Standard published
- Start Date
- 13-Sep-2012
- Completion Date
- 13-Dec-2025
Relations
- Effective Date
- 07-May-2011
Overview
ISO/TR 25100:2012 - "Intelligent transport systems - Systems architecture - Harmonization of ITS data concepts" - is a Technical Report from ISO/TC 204 that provides guidance on harmonising data concepts used in Intelligent Transport Systems (ITS). It describes processes, challenges and recommended practices for aligning definitions in data registries and data dictionaries (for example those described in ISO 14817:2002). As an informative (non‑normative) report, ISO/TR 25100:2012 helps organisations arrive at preferred definitions for use in formal standards, specifications and information models to reduce duplication and improve clarity.
Key topics
- Purpose and scope: Guidance for harmonisation of data concepts managed by metadata registries and dictionaries.
- Background issues (Clause 3): Problems addressed include proprietary data concepts, semantic differences, structural differences (e.g., XML representations), and difficulty of reuse.
- Harmonisation concepts (Clause 4): Definitions and principles for reconciling semantic, structural and syntactic differences; benefits and challenges of harmonisation versus pure interoperability.
- Harmonisation processes: Describes workflows and steps to reach preferred definitions (including investigation, mapping and reconciliation phases).
- Current approaches (Clause 5): Reviews four harmonisation approaches, examples such as ISO 14817, ISO/IEC 20943, UN/CEFACT TBG17 and core component methods, and practical registry work (e.g., metadata registries).
- Guidance for designers (Clause 6): Advice for data specification designers whether or not core components exist in a registry.
- Practical recommendations and conclusions (Clauses 7–8) on improving efficiency and reducing duplication in ITS and transport/logistics systems.
Applications and users
ISO/TR 25100:2012 is useful to:
- Standards developers and working groups creating ITS data specifications and information models.
- ITS architects and system designers seeking consistent data semantics across systems.
- Data modelers, registry maintainers and metadata librarians managing dictionaries and core components.
- Transport agencies, operators and vendors implementing ITS services who need to harmonise existing proprietary data with open registries. Practical uses include reducing ad‑hoc interface mapping, improving re‑use of data concepts, streamlining interoperability efforts and guiding harmonisation decisions in transport and logistics projects.
Related standards
- ISO 14817:2002 (metadata registries / data dictionaries)
- ISO 24531 (XML usage in ITS - structural guidance)
- ISO 14813‑6 (ASN.1 representation reference)
- ISO/IEC 20943, UN/CEFACT TBG17 and Core Components Technical Specification (CCTS) - referenced harmonisation approaches
Keywords: ISO/TR 25100:2012, Intelligent Transport Systems, ITS data harmonisation, data registry, data dictionary, metadata registry, semantic harmonisation, transport and logistics.
Frequently Asked Questions
ISO/TR 25100:2012 is a technical report published by the International Organization for Standardization (ISO). Its full title is "Intelligent transport systems - Systems architecture - Harmonization of ITS data concepts". This standard covers: ISO TR 25100:2012 provides guidance on the harmonisation of data concepts that are being managed by data registry and data dictionaries such as those described in ISO 14817:2002. ISO TR 25100:2012 describes processes for harmonisation of such data concepts to arrive at preferred definitions for use in formal standards, specifications, technical reports and information models. It is based on consideration of a harmonisation process used by international groups involved in the ITS sector and in the wider sector of transport and logistics information and control systems.
ISO TR 25100:2012 provides guidance on the harmonisation of data concepts that are being managed by data registry and data dictionaries such as those described in ISO 14817:2002. ISO TR 25100:2012 describes processes for harmonisation of such data concepts to arrive at preferred definitions for use in formal standards, specifications, technical reports and information models. It is based on consideration of a harmonisation process used by international groups involved in the ITS sector and in the wider sector of transport and logistics information and control systems.
ISO/TR 25100:2012 is classified under the following ICS (International Classification for Standards) categories: 03.220.01 - Transport in general; 35.240.60 - IT applications in transport. The ICS classification helps identify the subject area and facilitates finding related standards.
ISO/TR 25100:2012 has the following relationships with other standards: It is inter standard links to ISO/TR 25100:2008. Understanding these relationships helps ensure you are using the most current and applicable version of the standard.
ISO/TR 25100:2012 is available in PDF format for immediate download after purchase. The document can be added to your cart and obtained through the secure checkout process. Digital delivery ensures instant access to the complete standard document.
Standards Content (Sample)
TECHNICAL ISO/TR
REPORT 25100
Second edition
2012-09-15
Intelligent transport systems — Systems
architecture — Harmonization of ITS data
concepts
Systèmes intelligents de transport — Architecture des systèmes —
Harmonisation des concepts de données SIT
Reference number
©
ISO 2012
© ISO 2012
All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized in any form or by any means,
electronic or mechanical, including photocopying and microfilm, without permission in writing from either ISO at the address below or
ISO's member body in the country of the requester.
ISO copyright office
Case postale 56 CH-1211 Geneva 20
Tel. + 41 22 749 01 11
Fax + 41 22 749 09 47
E-mail copyright@iso.org
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Published in Switzerland
ii © ISO 2012 – All rights reserved
Contents Page
Foreword . iv
Introduction . v
1 Scope . 1
2 Terms, definitions and abbreviated terms . 1
2.1 Terms and definitions . 1
2.2 Abbreviated terms . 2
3 Background issues . 4
3.1 Proprietary data concepts . 4
3.2 Semantic differences . 4
3.3 Structural differences . 4
3.4 Difficulty of application of existing data concepts . 5
3.5 Report of investigation . 5
4 Harmonisation – General discussion . 5
4.1 Introduction to harmonisation . 5
4.2 Illustration of the need for harmonisation . 5
4.3 Challenges in harmonisation . 6
4.4 Harmonisation processes . 7
4.5 Steps in the harmonisation process . 10
4.6 Other work related to harmonisation . 11
5 Current approaches to harmonisation in ITS international standards . 11
5.1 Four approaches . 11
5.2 ISO 14817 harmonisation . 12
5.3 ISO/IEC 20943 approach . 13
5.4 TBG17 Business process & core components . 14
5.5 Highways Agency (UK) – Core Components Analysis of the ITS Metadata Registry . 16
6 Harmonisation approach for designers of data specifications . 24
6.1 Where there are relevant core components in a metadata registry or library . 24
6.2 Where there is no relevant registry using core components . 25
7 Harmonisation as a means to improve efficiency . 25
8 Conclusions and recommendations . 26
Annex A (informative) Conventions for precise core component mappings . 28
Bibliography . 33
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.
International Standards are drafted in accordance with the rules given in the ISO/IEC Directives, Part 2.
The main task of technical committees is to prepare International Standards. Draft International Standards
adopted by the technical committees are circulated to the member bodies for voting. Publication as an
International Standard requires approval by at least 75 % of the member bodies casting a vote.
In exceptional circumstances, when a technical committee has collected data of a different kind from that
which is normally published as an International Standard (“state of the art”, for example), it may decide by a
simple majority vote of its participating members to publish a Technical Report. A Technical Report is entirely
informative in nature and does not have to be reviewed until the data it provides are considered to be no
longer valid or useful.
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.
ISO/TR 25100 was prepared by Technical Committee ISO/TC 204, Intelligent transport systems.
This second edition cancels and replaces the first edition (ISO/TR 25100:2008). Clause 6 onwards has been
technically revised.
iv © ISO 2012 – All rights reserved
Introduction
The objective of this Technical Report is to provide user guidance for the harmonisation of data concepts
where there are similarities in definitions, including semantics.
Harmonisation has been discussed by several groups and some preliminary guidance and principles for the
effective harmonisation of data concepts for Intelligent Transport Systems [ITS] has already emerged.
It should be clearly recognised that harmonisation is not essential for interoperability, which can usually be
achieved given sufficient investment of knowledge and resources. Nevertheless this generally leads to
duplication and other unnecessary, futile and even useless work being undertaken. This also assumes that
there is an unlimited resource available to achieve the desired interoperability, whereas, in practice, time,
budget and shortage of skilled resources often cause compromise. Additionally, interoperability in one aspect
is sometimes achieved by the lack or loss of interoperability in another. Harmonisation is intended to reduce
the nugatory work, increase efficiency and thereby reduce the incidence of errors and faults.
This Technical Report describes a proposed process for harmonisation of data concepts to arrive at preferred
definitions for use in formal standards, specifications, technical reports and information models. The proposal
is based on consideration of a harmonisation process used by international groups involved in transport and
logistics information and control systems.
Harmonisation provides a means to improve efficiency and effectiveness of ITS, by helping to remove
duplication, inefficiency, ambiguity and confusion, and thereby improve clarity, comprehension, safety and
efficiency.
TECHNICAL REPORT ISO/TR 25100:2012(E)
Intelligent transport systems — Systems architecture —
Harmonization of ITS data concepts
1 Scope
This Technical Report provides guidance on the harmonisation of data concepts that are being managed by
data registry and data dictionaries such as those described in ISO 14817:2002.
This Technical Report describes processes for harmonisation of such data concepts to arrive at preferred
definitions for use in formal standards, specifications, technical reports and information models. It is based on
consideration of a harmonisation process used by international groups involved in the ITS sector and in the
wider sector of transport and logistics information and control systems.
2 Terms, definitions and abbreviated terms
2.1 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
2.1.1
attribute
data concept that represents a single property of an entity
2.1.2
data concept
definition of a kind of data representing a concept in the subject domain that can be identified
with explicit boundaries and meaning and whose properties and behaviour all follow the same
rules
NOTE This Technical Report assumes that data concepts, however they are represented, may have structure, such
that individual property definitions are grouped into aggregate entities representing larger-grained concepts in the subject
domain, and these entities may have relationships to one another; this basic idea is common to most description
languages and metamodels including UML, XML and entity-relationship notations.
2.1.3
entity
data concept that may have attributes and relationships to other entities
NOTE This Technical Report follows common usage of the term “entity” where the words “entity kind” or “entity class”
would be more accurate.
2.1.4
harmonisation of data concepts
process of reconciling differences in semantics, structure and syntax of similar data concepts
NOTE Harmonisation may include the establishment of a single pervasive definition for each data concept (i.e.
standardization), but can also encompass flexible approaches in which definitions can be understood to grow closer
without becoming identical.
2.1.5
ontology
rigorous conceptual schema representing the subject domain
2.1.6
relationship
property of a data concept that defines its relation to another data concept
2.1.7
standardization of data concepts
process of establishing a single standard definition for data concepts
2.1.8
taxonomy
classification scheme for a subject domain
2.2 Abbreviated terms
2.2.1
ACC
aggregate core component
2.2.2
ASCC
association core component
2.2.3
ASN.1
abstract syntax notation one
2.2.4
BCC
basic core component
2.2.5
BIE
business information entity
2.2.6
BRS
business requirement specification
2.2.7
CC
core component
2.2.8
CCC
change control committee [ISO 14817 (2002)]
2.2.9
CCTS
Core Components Technical Specification
2.2.10
CV
controlled vocabulary
2 © ISO 2012 – All rights reserved
2.2.11
DEN
Dictionary Entry Name
2.2.12
ETL
Extract, Transform and Load
2.2.13
IEC
International Electrotechnical Commission
2.2.14
ISO
International Organization for Standardization
2.2.15
ITS
intelligent transport systems
2.2.16
MOF
meta-object facility
2.2.17
QVT
queries views and transformations
2.2.18
RSM
requirements specification mapping
2.2.19
TBG17
'Trade and Business Processes Group working group 17', UN/CEFACT
2.2.20
TC
technical committee
2.2.21
TICS
transport information & control system
2.2.22
TIH
Travel Information Highway (UK)
2.2.23
UML
Unified Modeling Language (ISO/IEC 19501)
2.2.24
UN
United Nations
2.2.25
UN/CEFACT
United Nations Centre for Trade Facilitation and Electronic Business
2.2.26
WD
working draft
2.2.27
WG
working group
2.2.28
XML
eXtensible Markup Language
3 Background issues
Development of information systems and networks supporting business processes for transport and logistics
frequently encounters multiple similar data concepts, any or all of which may be in widespread use. The need
for harmonisation of these synonymous concepts has been acknowledged to enhance interoperability and
reusability, but there are significant issues to be overcome.
Current approaches to achieve the data interoperability are principally to write ad-hoc data interface programs
for each pair of communicating systems. Experience shows that development and maintenance of these
programs is expensive in terms of both time and money. The total effort required increases with the square of
the number of communicating systems.
3.1 Proprietary data concepts
The first issue is that many data concepts are proprietary or are deeply embedded in proprietary systems,
which work well within their intended domain but are not freely accessible for broader use. There is an
opportunity cost for a system whenever there is a similar but nevertheless separately defined and
implemented concept in use in another domain that is not applied to the subject system.
3.2 Semantic differences
A second issue is where the concepts are subjects of widely used standards, but are not identical and have
subtle semantic differences in their use. In this case the standards development organisations have generally
been protective of their own approaches, based on concern about the cost of enforced changes on already
deployed systems. This has resulted in diminished success in harmonisation processes (in the USA for
example).
Semantic clashes are where similar or overlapping concepts are used with different detailed semantics in
different standards.
3.3 Structural differences
Structural clashes are caused by the heterogeneity of representation which is possible with many techniques,
such as XML representation. For example, using XML format the same concept can be expressed in several
different ways. ISO 24531 provides assistance in these respects for the use of XML in the ITS sector.
XML Schema enables constraining of XML documents but this was designed for constraining the content of
XML documents not for the conceptual representation. Within XML, structural clashes are mainly caused by
the different usage of specific constructs, e.g. by a different usage of attributes rather than embedded
elements or by expressing concepts in enumeration values.
Usually freely designed XML documents used for specific application purposes do not provide sufficient
information about the semantics of the data. The semantics of XML elements used by web applications is
hard-coded into the applications and is typically not available in machine processable form. This applies also
4 © ISO 2012 – All rights reserved
to documents with available structural schemata (XML Schema), which in most cases define the syntactical
structure of XML documents without explicit specification of their meaning.
Recording all standardised data using ASN.1, as specified in ISO 14813-6, provides assistance for defining
structure and semantics, but of course does not prevent two independently designed structures from clashing.
Other forms of representation allow similar clashes to exist.
3.4 Difficulty of application of existing data concepts
When addressing a new application domain there should be a desire to reuse concepts that already exist as
proprietary or open standards, but the mechanism to render them usable may be unclear. This generally
results from semantic differences or uncertainty in the application of the concept, or because significant
domain knowledge is required for the successful reuse of a data concept from a different domain. It can
appear easier to an engineer to design a new concept rather than verify that an existing one is exactly suitable.
Existing concepts tend to come within structures that are not optimal for further new applications, and
unnecessary surplus structure discourages re-use.
3.5 Report of investigation
'Harmonisation' is often touted as the means to resolve these issues, but has been much more difficult to
achieve than expected. This Technical Report is based on an on-going investigation being carried out on
behalf of ISO/TC 204 working group WG1 (Intelligent Transport Systems [ITS] Architecture, Taxonomy,
Terminology and data modelling), into various approaches used for harmonisation. This Technical Report
presents tentative conclusions regarding the effectiveness of the approaches for general use in intelligent
transport systems, and the wider sector of transport and logistics.
4 Harmonisation – General discussion
4.1 Introduction to harmonisation
Harmonisation in this context is the process of resolving differences in data definitions that have semantic
overlaps. However, successful achievement of the harmonisation process remains a problem in many areas.
Members of ISO/TC 204 WG1 have been considering this matter for some time and propose solutions to the
requirement for effective harmonisation at syntactic, relationship and semantic levels. These solutions for
harmonisation are provided in this Technical Report.
Progress in this respect has also been achieved in the 'United Nations Office for Trade Facilitation and
Electronic Business' [UN/CEFACT] by the 'Trade and Business Processes Working Group' [TBG], specifically
TBG17, as discussed in a subsequent section.
Harmonisation is easier to achieve if a single organisation owns all of the systems or specifications being
harmonised. Harmonisation is particularly difficult in a mature domain where there are already established
implementations and standards but no single controlling authority to enforce the use of one particular standard.
Nevertheless even within a loosely aligned community, a harmonisation process can still be valuable in
signalling preferred representations and providing aids to translation or migration.
4.2 Illustration of the need for harmonisation
It is helpful to consider the nature of the problem to be resolved. Take for example the need for integrated use
of travel information in an advanced national traveller information service. One class of information for the
traveller information system will be timetables for various travel services. To take an example from Australia
where two timetables are to be merged but the times of service departure are expressed differently:
Travel service A departure time format: local time in New South Wales (time zone universal coordinated
time + 10 hours) 12-hour clock, subject to daylight savings time (Concept A);
Travel service B departure time format: 24 hour clock based on Western Australia (time zone universal
coordinated time + 8hrs) and not subject to daylight saving time (Concept B).
Of course, if the travel service were totally local, and travellers had no mobility, the only criteria would be local
custom. However, as the object of travel is mobility, and we may expect one traveller to move from one
locality to another, we may expect one travel provider to be providing travel information to traveller information
systems elsewhere, and in these days of Internet we may also expect direct enquiries from elsewhere; there is
therefore a significant benefit to be gained from harmonisation. An analyst can understand that both services
have an implementation of the same underlying concept – the departure time of a travel service – and can
therefore take steps to harmonise. It will be apparent that there is a need for a series of conversions and
business rules to be applied to arrive at a compatible format, which could be in either of the proponent formats
or a third (preferred) option could be the use of a standard time such as UTC with the conversion to the time
format as preferred by the person making the inquiry (query) to be made at the time of a query.
4.3 Challenges in harmonisation
For a single underlying domain concept, there are many types of difference that can arise between the
expressions of that concept in two different systems.
The following example is from a European project (Harmonise) for the 'Conceptual Normalisation of XML Data
for Interoperability in Tourism'.
This project studies problems in using XML data in the tourist industry, and while much of its harmonisation
resolution is very specific to XML it provides a methodology that in process (if not in detail) is similar to those
described in this Technical Report, and provides some good examples of the problems involved. These are
shown clearly in Tables 1 and 2 below.
Table 1 — Sample of differences
Different naming PostCode vs. PostalCode
Different position Postcode in Address rather than in ContactInfo
Different scope TelephonePrefix and TelephoneNumber separated vs. as single concept
In the wider industry there is a need to resolve these differences to achieve interoperability. Harmonisation is
possible because an observer can still see that, for example, “postcode” and “postalcode” are still expressions
of the same domain concept.
The example in Table 2 shows three valid but different ways of expressing the concept PostalCode in XML.
Table 2 — Structural heterogeneity of XML
Wannaby Street 59, Dreamtown
Wannaby Street 59
Dreamtown
X-1220
6 © ISO 2012 – All rights reserved
Wannaby Street 59,
X-1220
Dreamtown
The post code example shows some differences that can arise in the expression of one attribute within
aggregate entities. In general there will be a set of entities partially corresponding to another set of entities.
Even where two systems or specifications apparently have similar scope when viewed at a high level, there
may be entities present in one system that are entirely missing in the other.
In an example from highway location referencing in the UK, one data model included the following three
concepts:
while another system used:
There was an approximate semantic equivalence between “RoadSection” and “Section”, and between
“Section_LRP” (which stands for Location Reference Point) and “RoadsidePoint”, but there was no equivalent
for “Link” – due to differing requirements and business rules about segmentation of the road network. Any
harmonisation between the two models has to resolve the issue of how to resolve the relationship of the
“Sections” to the “Points”, which in the second model is direct but in the first model is through the intermediate
concept of “Link”. Harmonisation of the “Section” and “Link” entities would also have to resolve the differences
in business rules.
Harmonisation has thus to deal with issues at a semantic level, at a structural level, and at a syntactic level.
Every part of a data model could potentially vary from system to system even though the same concepts were
being described. These parts will include names, attributes, relationships, the boundaries of structures and
datatypes. And although the scope of harmonisation is for semantically related concepts, the detailed
semantics and business rules may differ and therefore also require resolution.
4.4 Harmonisation processes
4.4.1 Harmonisation contrasted with standardization
NOTE This Technical Report uses the definitions in Clause 2 for these terms.
A well established approach to deal with the issues raised above is to standardize on a single format to be
used in all applications. This can be very effective. However there may be forces which make complete
standardization difficult. Often the same concepts occur in different business contexts, but the realisation of a
concept that suits one business context may be very unsuitable for another business context. Harmonisation
processes recognise this by trying to reconcile differences to a practical level without always enforcing the use
of a single standard realisation of each concept in all business contexts.
The processes are clearly related, for example the outputs of harmonisation may subsequently be used as
standards, but harmonisation is always focussed on reconciling differences across more than one set of
definitions, whereas standardization may simply be the establishment of a single set of definitions.
Harmonisation increases interoperability, which need not be all or nothing: for example some parts of
harmonised specifications could produce limited interoperability, perhaps with some special work needed in
order to exchange data successfully; the better the alignment between the specifications the less special work
is needed.
4.4.2 Harmonisation by recognising underlying concepts
Harmonisation was possible and worthwhile in the above examples because the data models or other data
specifications were an expression of overlapping concepts from the subject domain. The scope and structure
of each model has been influenced by specific business contexts and other contextual factors, but each does
reflect concepts from the subject domain. Looking at two sets of data with overlapping semantics but different
formats, an analyst is able to attempt to understand similarities because the descriptions show that the
semantics overlap – both models are talking about the same domain concepts. The analyst is able to identify
semantic similarities because he/she has a mental reference model of the subject domain, and can identify
that, despite the differences that may exist, the data definitions in each set are a representation of concepts in
the subject domain.
In simple cases it is possible to proceed to harmonisation directly without making the background reference
model explicit. In these cases one data model will be changed to make it more similar to another. The extreme
example of this is complete standardization, where the two contexts come to use exactly the same model.
In more complex situations there is value in making the background reference model explicit in the form of
ontology, i.e. a rigorous conceptual schema representing the subject domain. The difference in nature
between the background ontology and the data specifications undergoing harmonisation must be stressed.
Admittedly, the data specifications may already be seen as attempts at rigorous expressions of the subject
domain, but they are shaped by their specific business contexts. The ontology used in harmonisation should
be more independent of business context. A harmonisation process can then use this reference ontology in
the understanding and also the recording of the similarities and differences between different data
specifications. These ideas are developed more fully in the UN/CEFACT Core Components approach, and the
refined harmonisation approach used by the UK Highways Agency; both are described in Clause 5.
8 © ISO 2012 – All rights reserved
harmonisation
B
A
P
Figure 1— Data concepts from specifications A and B are harmonised producing preferred or
reference set P
Figure 1 shows that data concepts from two semantically overlapping data specifications (labelled A and B in
this example) can be harmonised to produce ‘P’, a preferred or reference set of concepts.
Harmonisation is typically more than a simple superset operation. If the original sets A and B have evolved
independently then they may include differing versions of the same underlying concepts, and these are
reconciled to a single preferred version in P. In some harmonisation contexts, some or all of the changes
agreed for P will be fed back into the specifications A and B which become more interoperable.
The term "harmonisation" is used in a narrow sense to describe the process of selecting P by considering A
and B, and also in a wider sense where it also includes any adjustment of A and B to achieve a better fit
with P.
A and B in their original states may differ from each other and from P:
for valid reasons of optimisation for their different business contexts;
in cases where there is no strong justification for the difference.
The ideal goal of the overall harmonisation process is for all differences of the second kind to be removed,
and for the only remaining differences between A/B and P to be clearly justified for the specific business
context of A or B.
These process concepts and definitions may be understood more clearly by studying the specific examples in
Clause 5.
4.4.3 Harmonisation and metadata registries
A harmonisation process is usually used with a metadata registry. The harmonisation process is used to
increase the consistency of the registry contents. A and B are submissions to the registry, and the outcome P
is also stored in the registry. In some contexts A and B will be replaced by P in the registry, while in other
contexts A and B may be retained to support legacy systems.
A metadata registry imposes a structure (or "metamodel") for metadata. There are multiple registry standards
and implementations with differences in metamodel. Most basic concepts of harmonisation are independent of
the registry structure and could be instantiated with most registry implementations. However, some
harmonisation rules require certain characteristics from the metamodel, and therefore place requirements on
the type of metadata registry used.
A metadata registry may also impose a process for registration. The harmonisation processes described in
this TR are typically an extra level of detail that is not covered within defined registration processes. They
could be adapted to work together with most registry processes.
4.5 Steps in the harmonisation process
This subclause illustrates steps in the harmonisation process by continuing the simple example with the data
specifications labelled ‘A’ and ‘B’, although a harmonisation process may involve more than two input data
specifications, and may require more complex analysis at each step. Subclause 5.5 shows how these steps
are instantiated in a specific harmonisation process.
In general for a pair of data concepts from (A, B) harmonisation is the selection of preferred concept P based
on the attributes, relationships and semantics for individual data concepts in A and B.
P = h(A,B) where h is the harmonisation preference function
In some harmonisation contexts it may be possible to change concept A and/or concept B immediately to align
with concept P. In other contexts, concept P is retained as a reference that should be used as the target for
future developments.
The following steps must all be performed. They are not independent and are likely to be applied in multiple
iterations.
4.5.1 Derive entity boundaries – including names and semantics
Simple illustration: h( entity name A, entity name B ) entity name P
Harmonisation will identify a preferred or reference entity with a name. However, in generating the name, a
process of 'conceptual normalisation' [Harmonise Project] is an intrinsic part of the harmonisation process. By
agreeing a preferred name, a basis for the data concept is agreed at a highly abstracted level, without getting
concerned with the structure of the concept. However, it should be noted that the subsequent harmonisation
of detailed attributes and relationships puts a test on the results of the present step, as the full semantics of
the entity include the semantics of its attributes and relationships. The harmonisation of attributes and
relationships may cause a refinement to the harmonised entity boundaries.
4.5.2 Derive relationships – including role names and semantics
Simple illustration: h( relationship A, relationship B) relationship P
Relationships in A and B will lead to corresponding relationships between preferred or reference concepts in P.
10 © ISO 2012 – All rights reserved
4.5.3 Derive attributes – including names, semantics and datatypes
Simple illustration: h( attribute A, attribute B ) attribute P
Attributes in A and B will lead to corresponding attributes of preferred or reference concept in P. Where two
different attributes are semantically equivalent, a single preferred attribute must be chosen. In some cases
attributes with related but different semantics may indicate the need for a new entity to hold the attributes.
4.6 Other work related to harmonisation
4.6.1 Extract, Transform and Load (ETL)
The idea of resolving differences in data sets covering related concepts but using different models is also
encountered in enterprise data management, and is the focus of the "transform" step of the technique known
as Extract, Transform and Load (ETL). There are a number of ETL frameworks which allow the specification
of transformations from one data model to another. However the main focus of ETL is to establish a consistent
data warehouse, not to harmonise models for future systems developments. Despite significant tool
development we are not aware of a clear open standard approach to developing and specifying model
transforms for ETL.
4.6.2 MOF QVT (Meta-Object Facility Queries Views and Transformations)
The Object Management Group have developed and published Meta-Object Facility (MOF) “Queries Views
and Transformations” (QVT). It offers a graphical notation to extend UML, including transformation symbols.
Like ETL, QVT can be used to resolve differences in models. However, it seems focussed on model-to-model
transformation where metamodels are different, e.g. UML to relational database renditions of effectively the
same domain model. It does not provide a process for harmonisation of similar but different data concepts.
5 Current approaches to harmonisation in ITS international standards
5.1 Four approaches
The four approaches to harmonisation in the ITS sector discovered in our investigation are described below:
5.1.1 ISO 14817 approach
TC204 WG1 developed ISO 14817:2002, which primarily specifies a data registry, but it also outlines
a harmonisation process that uses the registry framework.
5.1.2 ISO/IEC 20943 approach
The ISO/IEC 20943 series reports on "Procedures for achieving metadata registry content
consistency" and is being developed in six parts, two of which have been published. These reports
expand on the ISO/IEC 11179 series of standards for metadata registries.
5.1.3 UN/CEFACT TBG17 approach
The approach developed within UN/CEFACT TBG17 is described in [TBG17 CCL (2008)]. The
purpose of TBG17 is to be responsible for consistency and harmonisation of business process models
and core components across business domains and sectors.
5.1.4 Highways Agency approach
This approach is taken by the Highways Agency (UK) to support its information exchanges with
partner organisations.
5.2 ISO 14817 harmonisation
ISO 14817:2002 was based on an earlier edition of the ISO/IEC 11179 series, customising it for the domain of
Intelligent Transport Systems.
ISO 14817:2002 describes its harmonisation process in A.6 in Annex A ITS/TICS Functional operating
procedures (for the ITS data registry and data dictionaries).
ISO 14817:2002, A.6.1 Introduction states, "These procedures detail how the CCC and the Stewards execute
their responsibilities…regarding identification, reconciliation and documentation of data concept overlaps and
duplications…’.
ISO 14817:2002, A.6.2 describes a ten-step process for identification and resolution of harmonisation issues.
The steps are summarised below.
5.2.1 Steps
Steps 1 to 4: The Registrar uses the capabilities of the Registry to identify potential overlapping or redundant
data concepts. A listing of potential issues is prepared and distributed.
Step 5: Stewards analyse their assigned issues and determine appropriate resolutions.
'The first step in this process is for each of the Stewards involved in a set of data concepts at issue to
understand the semantics of the data concepts at issue. If the semantics are not equivalent then the data
concepts should remain separate. If they are equivalent or significantly equivalent, then the Stewards should
agree to use one of them, modify one of them for joint use, or mutually agree to a new data concept to
supersede those data concepts at issue. After achieving semantic resolutions, the Stewards then should
address the Value Domain (if appropriate) of the data concepts at issue. The intent of this examination is to
agree on a mutual solution to these dimensions of the data concepts at issue.
The Resolution may be that one data concept is selected and other data concepts reference the selected data
concept as superseding, the data concepts at issue are merged into a new data element and the other data
concepts at issue reference the new data concept as superseding, or the data concepts at issue are kept
separate and independent.'
The Steward reports the resolutions to the Registrar.
Steps 6 and 7: Proposed harmonisations are distributed, with opportunity for further debate.
Steps 8 and 9: The Change Control Committee review and approve harmonisations and review issues.
Step 10: The Registry is updated.
5.2.2 Success of practical application of the process
An Australian prototype ITS data registry (supported by ITS Australia and other funding) operated for a brief
period but achieved limited progress in data harmonisation.
The UK Highways Agency implemented an extended ISO 14817 registry. The registration process was found
to be helpful, but not sufficient on its own to achieve harmonisation of multiple overlapping concepts, and a
complementary process was defined as further described in 5.5 below.
12 © ISO 2012 – All rights reserved
5.3 ISO/IEC 20943 approach
The ISO/IEC 20943 series consists of six parts, of which two have been published (as Technical Reports):
Part 1:Data elements;
Part 3:Value domains.
Additionally, Part 5: Semantic metadata mapping procedure, is particularly relevant to harmonisation and has
reached working draft stage.
All parts assume that the metadata adheres to the metamodel defined in ISO/IEC 11179-3.
5.3.1 Part 1:Data elements
This part describes two alternative approaches for populating a metadata registry: bottom-up and top-down.
The "bottom-up approach" involves harvesting data element definitions from system interfaces, and then
inferring the abstract data element concepts. (The Highways Agency approach described in 5.5 can also be
described as "bottom-up").
To quote the most relevant section of Part 1:
"…the registrar should perform content research to determine the following:
• Is the data element described in an existing International, National, or organizational standard?
• Does a data element exist in the registry, or a federation of registries, that has the potential for being
reused?
The practitioner will determine if a data element might be adapted to meet new requirements, or if some
attributes of an existing data element (e.g., value domain, data element concept, or conceptual domain) might
be reused with the new data element. Content research should include a search of conceptual domains, data
element concepts, and value domains, as well as data elements, to identify attributes that might be relevant to
the data element to be registered. If a standard data element exists that can be used as a model to meet the
particular specifications for a new purpose, some of its associated metadata items may be reused for
registration of the new data element.
The result of this step is confirmation that a new data element is needed, or a decision to modify or reuse an
existing data element or some of its attributes."
After the data elements are well described, the abstract data element concepts are derived. A single data
element concept may be related to several data elements with different representations.
The "top-down approach" is a planned approach to defining metadata, as opposed to being in response to
an existing system interface. In ISO/IEC 20943-1 the top-down approach proceeds in an object-oriented way,
registering object classes before specific data element concepts, and data element concepts before data
elements and representations.
There should be little need for harmonisation because the top-down registration should not create any
competing concepts.
5.3.2 Part 3:Value domains
Part 3 allows for the registration of similar but different value domains. When considering registration of a new
value domain, the registrar should determine whether any existing conceptual domain is appropriate, and if so,
the sets of value meanings should be checked and any new value meanings added. There is no guidance for
what to do if a pair of value meanings is similar but different.
Part 3 also allows the approach where two conceptual domains remain separate but each relate to a new
common super-ordinate conceptual domain with no enumerated values.
5.3.3 Part 5:Semantic metadata mapping procedure
This part is in progress at the time of writing. Working drafts describe how to map between overlapping
metadata sets describing similar concepts. The mapping is performed specifically for the purpose of
supporting the identification of a recommended set of data elements which may be a new combination of the
existing metadata sets.
A three-stage process is outlined:
1. Identify the metadata sets that will be in scope for mapping.
2. Group data elements by object class. An approach noted as helpful is to take one metadata set as
"primary" and to follow its groupings. For each object class, list the corresponding elements within
each metadata set.
3. Find common domain element concepts within each object group. Identify the "type of heterogeneity"
that exists for each specific data element. Derive a set of recomm
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