IEC SRD 63476-1:2024
(Main)Smart city system ontology - Part 1: Gap analysis
Smart city system ontology - Part 1: Gap analysis
IEC SRD 63476-1:2024 provides a gap analysis on ontology relevant standards for smart city systems to be used as a base document for mapping, developing and maintaining a set of ontology standards for smart city systems.
Ontology is becoming a key subject in the world of big data, AI, IoT, and smart city system standards. The following benefits of ontology are recognized as important with respect to interoperability, connectivity, traceability of digital content, particularly machine readability, executability and interpretability of digital content for decision making and actions.
- Increase interoperability across domains.
- Enable machine-readable code for computational reasoning and decision making.
- Create semantic linkages between data, information and knowledge systems.
- Build accessible APIs and semantic linkages between web-based data objects.
- Link data domains with shared concepts or canonical data models.
- Connect shared data concepts and definitions between domains.
However, ontology has a variety of definitions in different international standards. How to understand different meanings of ontology and select the right definition for the right stakeholders’ concerns for the right purposes is a big challenge for effective integration of business, data, information, knowledge and decision making, across disciplines, domains, systems, platforms and applications in smart cites. Moreover, how to deal with the grand challenges of interoperability of many and various ontologies to satisfy the demands from artificial intelligence and big data analytics are gaps to be filled in the area of smart city systems. How to develop digital content that is machine readable, executable and interpretable, working in the system without human effort for a smart city system are emerging needs to be studied. There are significant demands for better communication, coordination, cooperation, collaboration and connectivity of existing ontology standards to smart cities practical sectors. This document aims:
• to identify existing ontology standards from different Standards Development Organizations (SDOs) and to provide best practice examples and considerations of ontology standards development and maintenance for smart city systems;
• to identify gaps in existing ontology standards for smart city systems and the opportunities and challenges in ontology standards development taking into account multi-dimensional and muti-domain stakeholders’ concerns city wide, and to provide recommendations for ontology standards development and maintenance to enable integration, interoperability, efficiency and effectiveness of smart city systems.
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IEC SRD 63476-1 ®
Edition 1.0 2024-07
SYSTEMS REFERENCE
DELIVERABLE
Smart city system ontology –
Part 1: Gap analysis
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IEC SRD 63476-1 ®
Edition 1.0 2024-07
SYSTEMS REFERENCE
DELIVERABLE
Smart city system ontology –
Part 1: Gap analysis
INTERNATIONAL
ELECTROTECHNICAL
COMMISSION
ICS 13.020.20 ISBN 978-2-8322-8976-1
– 2 – IEC SRD 63476-1:2024 © IEC 2024
CONTENTS
FOREWORD . 5
INRODUCTION . 7
1 Scope . 8
2 Normative references . 8
3 Terms and definitions . 8
4 Foundations of concept system building for smart city systems . 11
4.1 Methods of ISO 704:2022 . 11
4.2 Core concepts and the characteristics of smart city by different SDOs . 11
4.3 System of systems view on smart city system in IEC SRD 63235:2021 . 14
4.4 Methodology framework for smart city system concept in
IEC SRD 63235:2021 . 15
4.5 Descriptive framework of city in ISO 37105:2019 . 16
5 Existing ontology definitions from different SDOs . 16
5.1 Existing ontology definitions from different sources . 16
5.2 Methodology for identification of concepts and concept relations . 16
5.3 Concept and concept relations about ontology . 18
6 Existing ontology standards deliverables and activities in different SDOs . 21
6.1 General . 21
6.2 Ontology-related standardization activities in ISO . 21
6.2.1 ISO/TC 46/SC 4 . 21
6.2.2 ISO/TC 184/SC 4 . 21
6.2.3 ISO/TC 211 . 22
6.2.4 ISO/IEC JTC 1/WG 11 . 22
6.2.5 ISO/IEC 30182:2017, Smart city concept model (SCCM) for data
interoperability . 25
6.2.6 ISO/IEC JTC 1/SC 29 . 26
6.2.7 ISO/IEC JTC 1/SC 32 . 27
6.2.8 ISO/IEC JTC 1/SC 38 . 28
6.2.9 ISO/IEC JTC 1/SC 41 . 29
6.2.10 ISO/IEC JTC 1/SC 42 . 29
6.3 Ontology-related standardization activities in IEC . 30
6.3.1 IEC SyC Smart Energy . 30
6.3.2 IEC TC 3/SC 3D . 31
6.3.3 IEC SyC Smart Cities . 31
6.4 Ontology-related standardization activities in ITU-T . 33
6.4.1 ITU-T Study Group 20 . 33
6.5 Ontology-related standardization activities in IEEE . 33
6.5.1 IEEE Robotics and Automation Society . 33
6.5.2 IEEE Consumer Technology Society . 34
6.6 Ontology-related standardization activities in W3C OGC . 34
6.7 Ontology-related standardization activities in ETSI SmartM2M . 37
6.8 Ontology related standardization activities elsewhere . 37
6.9 Types of ontology standardization issues and concerns . 38
6.10 Processes and activities of ontology building . 39
6.11 Framework for generating and constructing ontologies . 40
6.12 Stakeholders and concerns about ontology standards . 42
6.13 Ontology standard scenarios mapping with IEC SRD 63235:2021 . 42
7 Gap analysis and recommendations for future work . 45
7.1 Limitation of ontology definitions and concepts for smart city systems . 45
7.2 Lack of harmonization of ontology concepts for smart city systems . 46
7.3 Lack of integrated ontology framework for smart city systems . 46
7.4 Recommendations for future work . 48
7.4.1 Potential new work items . 48
7.4.2 Recommendations from the international virtual seminar on ontology . 48
7.4.3 Future collaboration . 50
Annex A (informative) A survey of shared understandings on smart city . 51
Annex B (informative) Existing definitions of ontology from SDOs and authoritative
sources . 56
Annex C (informative) A survey of understandings about ontology concepts for smart
cities and smart city systems . 59
Bibliography . 65
Figure 1 – An integrated concept system on smart city . 14
Figure 2 – Concept views of smart city systems . 15
Figure 3 – A methodology framework for building smart city system concept . 16
Figure 4 – Basic process for identification of concepts and their relations . 17
Figure 5 – A continuum thinking about ontology standards development . 20
Figure 6 – Framework to demonstrate certain indicators of ontology work . 23
Figure 7 – Framework of the ISO/IEC 5087 series formed by three levels of ontologies . 24
Figure 8 – Example concepts for the three levels of ontologies according to the
ISO/IEC 5087 series . 25
Figure 9 – Smart city levels of insight . 26
Figure 10 – Framework decomposition in packages and dependencies . 41
Figure 11 – Scope of MFI ontology registration . 41
Figure 12 – A harmonized ontology concept system for smart city systems . 45
Figure 13 – An ontology continuum model mapping with ontology concepts . 46
Figure 14 – Gaps in ontology standards for smart city systems . 47
Table 1 – Core concepts and the characteristics of smart city from different SDOs . 12
Table 2 – Three types of concept relation . 18
Table 3 – Types of ontology concept relation . 19
Table 4 – ISO/TC 46/SC 4 ontology deliverables. 21
Table 5 – ISO/TC 184/SC 4 ontology deliverables . 21
Table 6 – ISO/TC 211 ontology deliverables . 22
Table 7 – ISO/IEC JTC 1/WG 11 ontology deliverables . 22
Table 8 – ISO/IEC JTC 1/SC 29 ontology deliverables . 27
Table 9 – ISO/IEC JTC 1/SC 32 ontology deliverables . 28
Table 10 – ISO/IEC JTC 1/SC 38 ontology deliverables . 28
Table 11 – ISO/IEC JTC 1/SC 41 ontology deliverables . 29
Table 12 – ISO/IEC JTC 1/SC 42 ontology deliverables . 30
Table 13 – IEC SyC Smart Energy ontology deliverables . 30
Table 14 – IEC TC 3/SC 3D ontology deliverables . 31
– 4 – IEC SRD 63476-1:2024 © IEC 2024
Table 15 – IEC SyC Smart Cities SCRAM deliverables . 32
Table 16 – ITU-T Study Group 20 ontology deliverables . 33
Table 17 – IEEE Robotics and Automation Society ontology deliverables . 34
Table 18 – IEEE Consumer Technology Society ontology deliverables . 34
Table 19 – W3C OGC ontology deliverables . 35
Table 20 – ETSI SmartM2M ontology deliverables . 37
Table 21 – Ontology deliverables elsewhere . 37
Table 22 – Common processes and activities in ontology building . 39
Table 23 – Existing ontology standards mapping with IEC SRD 63235:2021 . 42
INTERNATIONAL ELECTROTECHNICAL COMMISSION
____________
SMART CITY SYSTEM ONTOLOGY –
Part 1: Gap analysis
FOREWORD
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IEC SRD 63476 has been prepared by IEC systems committee Smart Cities: Electrotechnical
aspects of Smart Cities. It is a Systems Reference Deliverable.
The text of this Systems Reference Deliverable is based on the following documents:
Draft Report on voting
SyCSmartCities/322/DTS SyCSmartCities/334/RVDTS
Full information on the voting for its approval can be found in the report on voting indicated in
the above table.
The language used for the development of this Systems Reference Deliverable is English.
– 6 – IEC SRD 63476-1:2024 © IEC 2024
This document was drafted in accordance with ISO/IEC Directives, Part 2, and developed in
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INRODUCTION
Ontology is becoming a key subject in the world of big data, AI, IoT, and smart city system
standards. The following benefits of ontology are recognized as important with respect to
interoperability, connectivity, traceability of digital content, particularly machine readability,
executability and interpretability of digital content for decision making and actions.
– Increase interoperability across domains.
– Enable machine-readable code for computational reasoning and decision making.
– Create semantic linkages between data, information and knowledge systems.
– Build accessible APIs and semantic linkages between web-based data objects.
– Link data domains with shared concepts or canonical data models.
– Connect shared data concepts and definitions between domains.
However, ontology has a variety of definitions in different international standards. How to
understand different meanings of ontology and select the right definition for the right
stakeholders’ concerns for the right purposes is a big challenge for effective integration of
business, data, information, knowledge and decision making, across disciplines, domains,
systems, platforms and applications in smart cites. Moreover, how to deal with the grand
challenges of interoperability of many and various ontologies to satisfy the demands from
artificial intelligence and big data analytics are gaps to be filled in the area of smart city systems.
How to develop digital content that is machine readable, executable and interpretable, working
in the system without human effort for a smart city system are emerging needs to be studied.
There are significant demands for better communication, coordination, cooperation,
collaboration and connectivity of existing ontology standards to smart cities practical sectors.
This document aims:
• to identify existing ontology standards from different Standards Development Organizations
(SDOs) and to provide best practice examples and considerations of ontology standards
development and maintenance for smart city systems;
• to identify gaps in existing ontology standards for smart city systems and the opportunities
and challenges in ontology standards development taking into account multi-dimensional
and muti-domain stakeholders’ concerns city wide, and to provide recommendations for
ontology standards development and maintenance to enable integration, interoperability,
efficiency and effectiveness of smart city systems.
– 8 – IEC SRD 63476-1:2024 © IEC 2024
SMART CITY SYSTEM ONTOLOGY –
Part 1: Gap analysis
1 Scope
This document provides a gap analysis on ontology relevant standards for smart city systems
to be used as a base document for mapping, developing and maintaining a set of ontology
standards for smart city systems.
2 Normative references
There are no normative references in this document.
3 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
ISO and IEC maintain terminology databases for use in standardization at the following
addresses:
• IEC Electropedia: available at https://www.electropedia.org/
• ISO Online browsing platform: available at https://www.iso.org/obp
3.1
characteristic
abstraction of a property (3.8)
Note 1 to entry: Characteristics are used to describe concepts.
[SOURCE: ISO 1087:2019, 3.2.1, modified – The EXAMPLE has been deleted.]
3.2
concept
unit of knowledge created by a unique combination of characteristics (3.1)
[SOURCE: ISO 1087:2019, 3.2.7, modified – The Notes to entry have been deleted.]
3.3
definition
representation of a concept by an expression that describes it and differentiates it from related
concepts (3.2)
[SOURCE: ISO 1087:2019, 3.3.1]
3.4
digital system
system consisting of hardware, software, and possibly network components, used to generate
and/or use data to fulfil one or more specific functions
EXAMPLE 1: A digital traffic system that uses sensors to measure real time traffic movement digitally and sends that
data to where it can be collected, analysed and used both to control digital traffic signals and to provide information
to support decision making by staff in traffic management roles and by travellers.
EXAMPLE 2: A digital health record system that transforms information related to patients into digital form and
enables it to be shared and analysed to support treatment.
EXAMPLE 3: A digital payment system that uses smart cards, readers, and secure data transmission, and sends
queries and enables the alteration of data within financial institutions, to allow goods and services to be paid for
without the need of cash.
EXAMPLE 4: A digital assembly line system in a factory that collects and monitors data coming from a variety of
sources and uses that to coordinate robotic assembly processes and make any adjustments necessary to support
quality and efficiency goals.
[SOURCE: IEC 60050-831:–, 831-02-03]
3.5
domain
subject field
field of special knowledge
[SOURCE: ISO 1087:2019, 3.1.4]
3.6
object
anything perceivable or conceivable
Note 1 to entry: Objects can be material (e.g. ‘engine’, ‘sheet of paper’, ‘diamond’), immaterial (e.g. ‘conversion
ratio’, ‘project plan’) or imagined (e.g. ‘unicorn’, ‘scientific hypothesis’).
[SOURCE: ISO 1087:2019, 3.1.1]
3.7
physical system
set of physical objects and processes that work together to fulfil one or more specific functions
EXAMPLE Electrical power distribution systems, logistics systems, metro systems.
[SOURCE: IEC 60050-831:–, 831-03-03]
3.8
property
feature of an object (3.6)
Note 1 to entry: One or more objects can have the same property.
[SOURCE: ISO 1087:2019, 3.1.3, modified – The EXAMPLES have been deleted.]
– 10 – IEC SRD 63476-1:2024 © IEC 2024
3.9
smart city
city where improvements in quality of life, services, sustainability and resilience are facilitated
by the effective integration of many and various types of physical, digital and social systems
and the transformative use of data and technology
Note 1 to entry: This is a general definition of a smart city. The IEC looks at these aspects from the perspective of
electrotechnology.
Note 2 to entry: The effective integration of physical, digital and social systems can be facilitated by integration of
digital twins of all these systems.
[SOURCE: IEC 60050-831:–, 831-01-19]
3.10
system
combination of interacting elements organized to achieve one or more stated purposes
Note 1 to entry: In the context of smart cities, the system as a whole exhibits (as the result of interactions between
its elements) some emergent characteristics indispensable to achieve one or more of its stated purposes.
Note 2 to entry: In the city transport system the interactions between traffic management and emergency
management, sharing information related to resource allocations, road network conditions, video surveillance
imaging and control, enable the emergent characteristic of improvement in traffic congestion.
[SOURCE: ISO/IEC/IEEE 21840:2019, 3.1.8, modified – The Notes to entry have been added.]
3.11
social system
patterned series of interrelationships existing between individuals, groups, and institutions and
forming a coherent whole
EXAMPLE Nuclear family units, communities, cities, nations, college campuses, corporations, and industries.
Note 1 to entry: An individual can belong to multiple social systems at once.
Note 2 to entry: The organization and definition of groups within a social system depend on various shared
properties such as location, socioeconomic status, race, religion, societal function, or other distinguishable features.
[SOURCE: IEC 60050-831:–, 831-04-03]
3.12
system of systems
SOS
set of operationally and managerially independent systems (3.10) that are
coordinated together to achieve one or more commonly stated purposes
Note 1 to entry: Each constituent system is a useful system by itself, having its own management, goals, and
resources, and coordinates within the SOS to provide the unique capability of the SOS.
[SOURCE: IEC 60050-871:2018, 871-05-03, modified – The domain has been
added. In the definition, "operated" has been replaced by "coordinated", "commonly" has been
added, and "for a period of time" has been deleted. Note 1 to entry has been replaced by new
Note 1 to entry from ISO/IEC/IEEE 24748-1:2018, 3.56, in which "but coordinates" has been
replaced by "and coordinates".]
3.13
term
designation that represents a general concept (3.2) by linguistic means
[SOURCE: ISO 1087:2019, 3.4.2, modified – The EXAMPLE and Note 1 to entry have been
deleted.]
3.14
terminology
set of designations and concepts (3.2) belonging to one domain or subject
[SOURCE: ISO 1087:2019, 3.1.11]
4 Foundations of concept system building for smart city systems
4.1 Methods of ISO 704:2022
An analysis of key terms relevant to ‘unit of knowledge’ and ‘characteristics’ in definitions of
smart city is conducted based on understandings about ‘concept’ and ‘characteristic’ in
ISO 704:2022 and ISO 1087:2019.
The relations between the ‘object’, ‘property’, and ‘characteristic’ are well described in
ISO 704:2022, 5.4.1, which provides a way to identify object and its characteristics that helps
define concept.
4.2 Core concepts and the characteristics of smart city by different SDOs
Based on six collected definitions of smart city, a survey was conducted to identify and
investigate core concepts and their characteristics in the definitions of smart city from different
SDOs during online meetings from 29 April to 14 May 2021. Eight questions, comprising seven
closed questions and one open question, were designed in a questionnaire (see Annex A). The
questionnaire was sent to experts from IEC SyC Smart Cities through the IEC collaboration
platform and to experts of ISO/TC 268/SC 1/WG 4, ISO/IEC JTC 1/WG 11 and ITU-T SG 20 by
email. 14 responses to the survey were collected and validated for the analysis.
Table 1 and Figure 1 show core concepts in definitions of smart city from different SDOs and
their relationships and common characteristics.
At the high level, characteristics on smart city involves responding to stakeholder concerns and
domain-specific concerns. People’s issues and concerns were represented by over 80 % to
100 % agreement from different stakeholders of different SDOs in stakeholders’ concerns.
Therefore, placing a citizen-centric focus on smart city development is recommended or might
focus on present generation and future generations for its citizens. Stakeholder concerns also
include supplying side services to citizens from government and business agencies, especially
customers.
In addition, domain concerns refer to diverse city system feature issues of city which can be
divided into digital, environmental, economic, cultural and social aspects. Specifically, the
digital aspect can involve information technology, digital transformation, electrotechnical
systems, data and information. The environmental aspect includes two elements such as the
built environment and natural environment, and social aspect refers to international standards
and coordinated and reflexive system.
Means and approaches for smart city could be intermediate level to connect high level and low
level. Smart city can select from a wide range of policy, leadership and technical use methods
which refer to collaborative leadership, disciplines and city system, recognized metrics at
society level and ICT, electrotechnical systems, use of data and information from modern
technologies.
– 12 – IEC SRD 63476-1:2024 © IEC 2024
Smart object, smart status and visions and goals can be identified from definitions of smart
cities. In smart object, integration of physical, digital and social systems is possibly the most
important feature of smart city which could provide better understanding and benefits for
decision makers, development of sustainability and community. Moreover, effective integration
is also essential for smart status. Effective integration enables digitally coordinated systems as
self-organizing system that accelerate improvement of services, increase pace of learning and
reflexing and innovation. Finally, in terms of visions and goals of smart city, what smart city is
intending to achieve is defined by improvements of targeted goals. Hence, smart city is not only
intended to achieve competitiveness, stability, liveability and resilience, and repeatability and
scalability, but also to enhance fundamental improvements on efficiency, concerns addressing
quality of life and better city services.
Table 1 – Core concepts and the characteristics of smart city from different SDOs
Characteristics Concepts
ISO IEC ITU-T
Characteristics in terms of • present and future
• citizen (D1, D3) • citizen (D4, D5)
stakeholder’s concern about smart generation (D2)
city
Characteristics in terms of domain’s • built environment • city (D4, D5, D6) • economic, social,
concern about smart city (D1) environmental as
• international
well as cultural
• natural standards and
aspect (D2)
environment (D3) digital
transformation
(D5)
• electrotechnical
systems and
information
technology (D6)
Characteristics in terms of smart • integration of • city (D4, D5, D6) • city (D2)
object of smart city physical, digital
and human
systems (D1)
• city (D3)
Characteristics in terms of smart • effective • improvements • innovative (D2)
status of smart city integration (D1) accelerated (D4)
• increasing the • self-organizing
pace (D3) system (D5)
• digital
transformation as
digitally
coordinated
systems with its
own pace (D5)
• improvements for
services (D6)
Characteristics Concepts
ISO IEC ITU-T
• improve quality of
Characteristics in terms of visions • a sustainable, • improvements in
and goals of smart city prosperous and quality of life, life, efficiency of
(improvement of targeted goals) inclusive future services, urban operation and
(D1) sustainability and services, and
resilience (D4) competitiveness
• fundamentally
(D2)
• repeatability and
improving (D3)
scalability of digital
• provides social,
solutions (D5)
economic and
environmental • systematically
sustainability addressing
outcomes and concerns (D5)
responds to
• city services (D6)
challenges such
as climate
change, rapid
population growth,
and political and
economic
instability, to
deliver better
services and
quality of life (D3)
Characteristics in terms of • effective • by the effective • information and
approaches to and means of smart integration of integration of many communication
city physical, digital and various types technologies (ICTs)
and human of physical, digital and other means
systems (D1) and social systems (D2)
and the
• engage society
transformative use
applies
of data and
collaborative
technology (D4)
leadership
methods, works • internationally
across disciplines recognized metrics
and city systems, (D5)
and uses data
• electrotechnical
information and
systems and
modern
information
technologies (D3)
technology (D6)
NOTE D refers to definition. D1, D2, D3, etc. refer to codes of definitions of ontology in Annex B.
– 14 – IEC SRD 63476-1:2024 © IEC 2024
Figure 1 – An integrated concept system on smart city
4.3 System of systems view on smart city system in IEC SRD 63235:2021
Figure 2 shows a system of systems view for smart cities and smart city systems according to
IEC SRD 63235:2021:
• A system of systems view (see Figure 2) considers the smart city as a complex system
made up of many vertical domains such as transport, health, education, employment and so
on. Each of these vertical domains is interconnected by three cross-cutting overarching and
horizontal systems that include views aspects of a city centric social system, digital system
and physical system of a city and system approach, which work together as a
complementary whole in response to the concerns and representing the interests of different
stakeholders (ISO/IEC 30182:2017, 2.14). Each of these, in turn, can be subdivided to
describe in greater detail other horizontal, cross-cutting domains.
• Taking this system of systems view enables the total capability of a city-wide view to be
understood from both a technical domain and a societal perspective to be enhanced to an
extent that none of the constituent systems can accomplish on its own. Each constituent
system is a useful system by itself with its own management, goals and resources, but when
coordinated within the smart city systems (SCSs) contributes to providing a unique broader
capability as a member of the SCSs.
• The social system provides a multi-dimensional governance framework
(ISO/IEC TR 38502:2017, 3.1) for coordinating arrangements of strategies, policies,
decision-making structures and accountabilities to manage multiple stakeholders' concerns
in social space and convergence.
• A digital system provides a multi-domain architectural framework
(ISO/IEC/IEEE 24748‑1:2018, 3.7) for cooperating activities of conventions, principles and
practices for individual domain architecture and to enable, operate and support digital
transformation.
• A physical system provides a multi-layer application framework (ISO/IEC/IEEE 24765:2017,
3.177) to connect, identify and sustainably manage artefacts in each subsystem, and enable
interfaces between systems in physical spaces to support all necessary interactions.
• An integration of the social, digital and physical systems with technical domains supports
the convergence of multi-dimensional, multi-domain and multi-layer concerns and interests,
can aid the mapping and coordination of digital systems development, design and
operations, to support smart city of multiple stakeholders as well as enhancing the adaptive
capacity of a city as an ecosystem to deliver a sustainable, prosperous and inclusive future
for its citizens.
SOURCE: IEC SRD 63235:2021, Figure 1.
Figure 2 – Concept views of smart city systems
4.4 Methodology framework for smart city system concept in IEC SRD 63235:2021
Figure 3 shows a methodology framework for smart cities and smart city systems according to
IEC SRD 63235:2021.
• A methodology framework refers to a way, or structure, that supports a number of different
methods and languages to be used together effectively when developing a complex multi-
domain level system.
• The methodology framework for a smart city system concept system refers to a system of
systems way of thinking that supports multi-dimensional, multi-domain and multi-layer, life-
cycle and use case analysis approaches to be used together as a complementary whole in
developing a smart city system.
– 16 – IEC SRD 63476-1:2024 © IEC 2024
SOURCE: IEC SRD 63235:2021, Figure 2.
Figure 3 – A methodology framework for building smart city system concept
4.5 Descriptive framework of city in ISO 37105:2019
ISO 37105:2019 presents a descriptive framework for cities and communities. The descriptive
framework categorizes the components of city into three major elemental systems that is
physical structures (structure), living entities (society) and the flow of interactions between them
(interactions). These elemental systems are further described by layers that capture all the
activities of importance to a city. The descriptive framework can be the basis of formal ontology,
or knowledge model, which can be useful for helping to plan and implement city operation
solutions.
5 Existing ontology definitions from different SDOs
5.1 Existing ontology definitions from different sources
15 definitions existing in different SDOs were collected and analysed at the Ontology for Smart
Cities and Smart City Systems & Standards Workshop held by IEC SyC Smart Cities, on
30 September 2020. Furthermore, eight additional definitions from different authoritative
sources are added from this ontology workshop. In total, there are 23 definitions of ontology
collected as samples for analysis (see Annex B).
5.2 Methodology for identification of concepts and concept relations
Methodology for identification of concepts is in conformity with ISO 704:2022 and the basic
process for identification of concepts and its relations is shown in Figure 4.
NOTE Based on ISO 704:2022 and ISO 1087:2019.
Figure 4 – Basic process for identification of concepts and their relations
– 18 – IEC SRD 63476-1:2024 © IEC 2024
First, concepts are described to distinguish them from others and relationships are also
described between them based on past domain-specific knowledge. In order to describe the
concept and distinguish it from other related concepts, the definition can be used to represent
the concept. After that, in order to identify the concept relation, the concept system is structured
by a set of concepts which are related to domain and knowledge.
In addition, ISO 704:2022, 5.5.3 presents three types of concept relation: generic relation,
partitive relation and associative relation (see Table 2).
Table 2 – Three types of concept relation
No. Type of concept relation Definition
concept relation between a generic concept and a specific concept
where the intension of the specific concept includes the intension of the
generic concept plus at least one additional delimiting characteristic.
Note 1 to entry: Outside the terminology community, ‘type of relation’
1 generic relation
and ‘is a relation’ are also used instead of “generic relation”.
Note 2 to entry: In a generic relation, the subordinate concept is a
specific concept and the superordinate concept is a generic concept.
[SOURCE: ISO 1087:2019, 3.2.13]
concept relation between a comprehensive concept and a partitive
concept.
2 partitive relation
[SOURCE: ISO 1087:2019, 3.2.14]
concept relation that exists when a thematic connection can be
established between concepts by virtue of experience
3 associative relation
Note 1 to entry: Associative relations are non-hierarchical.
5.3 Concept and concept relations about ontology
Ontology concept refers to three key components: Terminology, Subclass of, and Logic (TSL).
1) Terminology refers to entities with attributes and relations with optional domain and range
specifications.
2) Subclass of refers to addition of taxonomic relations.
3) Logic refers to addition of definitions using a formal language; this level involves description
logic that has restriction.
Therefore, six types of concept relation in existing definitions of ontology are identified, shown
in Table 3 as mapping with TSL viewpoint.
Table 3 – Types of ontology concept relation
Type of ontology Source
No. TSL analysis Description of concept relation
concept relation (see Annex B)
conceptualization of a
domain/rigorous conceptual schema
Conceptualization of
representing the subject
Terminology
domain/rigorous
1 domain/model that represents a D1_D6_D11_D16
conceptual
Subclass
domain and is used to reason about
schema/model
the objects in that domain and the
relations between them
a lexicon of specialized terminology
A lexicon of specialized
2 Terminology along with some specification of the D13_D17_D24
terminology
meaning of terms in the lexicon
Organization or logic structure of
concepts for which a rational
Terminology
Logical structure of
3 argument can be made/logical D2_D5_D21
concepts or terms
Subclass of
structure of the terms used to
describe a domain of knowledge
explicit and consensual
specification of
concept/specification of concrete or
Formal, explicit and abstract things, and the
Terminology
consensual relationships among them, informal, D3_D4_D10_D14
specification of explicit specification of a shared D15_D18_D22
Subclass of
conceptualization conceptualization/formal
specification of a
conceptualization/an explicit
specification of a conceptualization
formal representat
...
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