ISO/IEC 21972:2020
(Main)Information technology — Upper level ontology for smart city indicators
Information technology — Upper level ontology for smart city indicators
This document establishes general principles and gives guidelines for an indicator upper level ontology (IULO) for smart cities that enables the representation of indicator definitions and the data used to derive them. It includes: — concepts (e.g., indicator, population, cardinality); and — properties that relate concepts (e.g., cardinality_of, parameter_of_var).
Titre manque
General Information
Buy Standard
Standards Content (Sample)
INTERNATIONAL ISO/IEC
STANDARD 21972
First edition
2020-01
Information technology — Upper level
ontology for smart city indicators
Reference number
©
ISO/IEC 2020
© ISO/IEC 2020
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting
on the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address
below or ISO’s member body in the country of the requester.
ISO copyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: +41 22 749 01 11
Fax: +41 22 749 09 47
Email: copyright@iso.org
Website: www.iso.org
Published in Switzerland
ii © ISO/IEC 2020 – All rights reserved
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms . 2
5 Basic indicator ontology pattern . 3
6 Time . 4
6.1 General . 4
6.2 Core classes and properties . 5
6.3 Graphical depiction . 5
7 Quantities and units of measure . 6
7.1 General . 6
7.2 Core classes and properties . 7
7.3 Formal specification . 9
8 Indicator quantities and units of measure .10
8.1 Core classes and properties .10
8.2 Formal specification .14
9 Statistics .17
9.1 General .17
9.2 Core concepts and properties .17
9.3 Formal specification .18
10 Populations .19
10.1 General .19
10.2 Core concepts and properties .19
10.2.1 Membership extent .19
10.2.2 Spatial extent . . .21
10.2.3 Temporal extent .22
10.2.4 Measured variable .23
10.3 Formal specification .25
11 Example .26
11.1 Description .26
11.2 Specification .27
Bibliography .29
© ISO/IEC 2020 – 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.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for
the different types of document should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www .iso .org/ directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject
of patent rights. ISO and IEC shall not be held responsible for identifying any or all such patent
rights. Details of any patent rights identified during the development of the document will be in the
Introduction and/or on the ISO list of patent declarations received (see www .iso .org/ patents) or the IEC
list of patent declarations received (see http:// patents .iec .ch).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to the
World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT), see www .iso .org/
iso/ foreword .html.
This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www .iso .org/ members .html.
iv © ISO/IEC 2020 – All rights reserved
Introduction
[11]
To paraphrase Lord Kelvin, you cannot manage what you cannot measure . For cities to be smart,
their decisions need to be based on precisely defined and accurate metrics. For smart city information
and communication technology to be used to aid cities in making smart decisions, then the digital data
models they use need to precisely and accurately reflect what they represent of the city and how it is
measured. This document specifies a data model that can be used to represent city indicator definitions.
The data model is defined using the Semantic Web OWL 2 Web Ontology Language (OWL). Figure 1
depicts two intended uses of this document.
a) Definition-based Calculation b) Definition-based Diagnosis
of Indicator from Base Data of Indicator-based City Performance
Figure 1 — Possible uses of this document
Figure 1 a) depicts the indicator definition being used to automate the computation of an indicator
value. In this case, an indicator definition plus city data is input into the indicator independent
calculation application, which uses the definition to select subsets of city data, to compute the indicator.
This approach makes it possible to create an indicator calculation application that is not programmed
for a specific set of indicators. Figure 1 b) depicts a diagnosis system that uses the definition of an
indicator as a basis for determining the root cause of transversal or longitudinal deviations in an
indicator’s value over place or time. A diagnosis system must understand what data was selected and
how it was combined in order to determine the sources of change. In the remainder of this Introduction,
the motivation for and the purpose of this document are elaborated.
[33]
Cities are moving towards policy-making based on data . Yet it has been recognized by urban
researchers, city professionals and political leaders that city level data is both incomplete and
inconsistent. In 2007, it was recognized that “there are thousands of different sets of city (or urban)
indicators and hundreds of agencies compiling and reviewing them. Most cities already have some
degree of performance measurement in place. However, these indicators are usually not standardized,
consistent or comparable (over time or across cities), nor do they have sufficient endorsement to be
[27]
used as ongoing benchmarks.”
In response, ISO 37120 was developed to provide a set of indicators, across 17 themes, to measure city
performance. These indicators spanned areas such as education, finance, shelter, transportation and
environment.
Indicator definitions are people oriented; they are provided in natural language, e.g., English, and not
in a more formal, possibly computer readable language. The reader of the definition imposes their own
© ISO/IEC 2020 – All rights reserved v
interpretation of the definition based on their understanding of the language and the environment in
which they live (e.g., how their own city may define some terms).
Consider the definition of a student/teacher ratio as provided in Reference [21]: “Student/teacher ratio”.
[34]
This has been expanded to: “Student/teacher ratio”, where the numerator is “Number of Students”,
and the denominator is “Number of Teachers”. One problem is whether “student” refers to full time
students, or part time students. Are they regular students or special needs students? Do they include
kindergarten students or not? It is also difficult to compare an indicator for a single city across time if
the definition of student changes. For example, today the educational system includes students with
special needs, but 30 years ago they may not have been enrolled. Without a more precise definition
of terms, it makes it difficult to compare an indicator across cities where each city interprets what a
student is differently, or against itself where definitions change.
Obviously, the definition and documentation of indicators can be expanded, as has been done in
ISO 37120:2018, 6.4.2.
The definition of student/teacher ratio clearly addresses some of the issues raised above. Nevertheless,
there is always a disconnect between the actual value of a city’s indicator and the data sources and
processes used to measure it; while the indicator’s value is recorded in a machine-readable form
(e.g., database or semantic web), the sources and measurement processes are b
...
INTERNATIONAL ISO/IEC
STANDARD 21972
First edition
2020-01
Information technology — Upper level
ontology for smart city indicators
Reference number
©
ISO/IEC 2020
© ISO/IEC 2020
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting
on the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address
below or ISO’s member body in the country of the requester.
ISO copyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: +41 22 749 01 11
Fax: +41 22 749 09 47
Email: copyright@iso.org
Website: www.iso.org
Published in Switzerland
ii © ISO/IEC 2020 – All rights reserved
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms . 2
5 Basic indicator ontology pattern . 3
6 Time . 4
6.1 General . 4
6.2 Core classes and properties . 5
6.3 Graphical depiction . 5
7 Quantities and units of measure . 6
7.1 General . 6
7.2 Core classes and properties . 7
7.3 Formal specification . 9
8 Indicator quantities and units of measure .10
8.1 Core classes and properties .10
8.2 Formal specification .14
9 Statistics .17
9.1 General .17
9.2 Core concepts and properties .17
9.3 Formal specification .18
10 Populations .19
10.1 General .19
10.2 Core concepts and properties .19
10.2.1 Membership extent .19
10.2.2 Spatial extent . . .21
10.2.3 Temporal extent .22
10.2.4 Measured variable .23
10.3 Formal specification .25
11 Example .26
11.1 Description .26
11.2 Specification .27
Bibliography .29
© ISO/IEC 2020 – 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.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for
the different types of document should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www .iso .org/ directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject
of patent rights. ISO and IEC shall not be held responsible for identifying any or all such patent
rights. Details of any patent rights identified during the development of the document will be in the
Introduction and/or on the ISO list of patent declarations received (see www .iso .org/ patents) or the IEC
list of patent declarations received (see http:// patents .iec .ch).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to the
World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT), see www .iso .org/
iso/ foreword .html.
This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www .iso .org/ members .html.
iv © ISO/IEC 2020 – All rights reserved
Introduction
[11]
To paraphrase Lord Kelvin, you cannot manage what you cannot measure . For cities to be smart,
their decisions need to be based on precisely defined and accurate metrics. For smart city information
and communication technology to be used to aid cities in making smart decisions, then the digital data
models they use need to precisely and accurately reflect what they represent of the city and how it is
measured. This document specifies a data model that can be used to represent city indicator definitions.
The data model is defined using the Semantic Web OWL 2 Web Ontology Language (OWL). Figure 1
depicts two intended uses of this document.
a) Definition-based Calculation b) Definition-based Diagnosis
of Indicator from Base Data of Indicator-based City Performance
Figure 1 — Possible uses of this document
Figure 1 a) depicts the indicator definition being used to automate the computation of an indicator
value. In this case, an indicator definition plus city data is input into the indicator independent
calculation application, which uses the definition to select subsets of city data, to compute the indicator.
This approach makes it possible to create an indicator calculation application that is not programmed
for a specific set of indicators. Figure 1 b) depicts a diagnosis system that uses the definition of an
indicator as a basis for determining the root cause of transversal or longitudinal deviations in an
indicator’s value over place or time. A diagnosis system must understand what data was selected and
how it was combined in order to determine the sources of change. In the remainder of this Introduction,
the motivation for and the purpose of this document are elaborated.
[33]
Cities are moving towards policy-making based on data . Yet it has been recognized by urban
researchers, city professionals and political leaders that city level data is both incomplete and
inconsistent. In 2007, it was recognized that “there are thousands of different sets of city (or urban)
indicators and hundreds of agencies compiling and reviewing them. Most cities already have some
degree of performance measurement in place. However, these indicators are usually not standardized,
consistent or comparable (over time or across cities), nor do they have sufficient endorsement to be
[27]
used as ongoing benchmarks.”
In response, ISO 37120 was developed to provide a set of indicators, across 17 themes, to measure city
performance. These indicators spanned areas such as education, finance, shelter, transportation and
environment.
Indicator definitions are people oriented; they are provided in natural language, e.g., English, and not
in a more formal, possibly computer readable language. The reader of the definition imposes their own
© ISO/IEC 2020 – All rights reserved v
interpretation of the definition based on their understanding of the language and the environment in
which they live (e.g., how their own city may define some terms).
Consider the definition of a student/teacher ratio as provided in Reference [21]: “Student/teacher ratio”.
[34]
This has been expanded to: “Student/teacher ratio”, where the numerator is “Number of Students”,
and the denominator is “Number of Teachers”. One problem is whether “student” refers to full time
students, or part time students. Are they regular students or special needs students? Do they include
kindergarten students or not? It is also difficult to compare an indicator for a single city across time if
the definition of student changes. For example, today the educational system includes students with
special needs, but 30 years ago they may not have been enrolled. Without a more precise definition
of terms, it makes it difficult to compare an indicator across cities where each city interprets what a
student is differently, or against itself where definitions change.
Obviously, the definition and documentation of indicators can be expanded, as has been done in
ISO 37120:2018, 6.4.2.
The definition of student/teacher ratio clearly addresses some of the issues raised above. Nevertheless,
there is always a disconnect between the actual value of a city’s indicator and the data sources and
processes used to measure it; while the indicator’s value is recorded in a machine-readable form
(e.g., database or semantic web), the sources and measurement processes are b
...
Questions, Comments and Discussion
Ask us and Technical Secretary will try to provide an answer. You can facilitate discussion about the standard in here.