ISO/IEC 5087-1:2023

INTERNATIONAL ISO/IEC
STANDARD 5087-1
First edition
2023-08
Information technology — City data
model —
Part 1:
Foundation level concepts
Reference number
ISO/IEC 5087-1:2023(E)
© ISO/IEC 2023

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ISO/IEC 5087-1:2023(E)
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© ISO/IEC 2023
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ISO/IEC 5087-1:2023(E)
Contents Page
Foreword .v
Introduction . vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Abbreviated terms and namespaces .3
5 General . 4
5.1 Unique identifiers. 4
5.2 Reference to existing patterns . 5
6 Foundational ontologies . 5
6.1 General . 5
6.2 Generic properties . 5
6.2.1 General . 5
6.2.2 Key Properties . 6
6.3 Mereology pattern . 6
6.3.1 General . 6
6.3.2 Key classes and properties . 6
6.3.3 Formalization . 7
6.4 City Units Pattern. 8
6.4.1 General . 8
6.4.2 Key classes and properties . 8
6.4.3 Formalization . 9
6.5 Time Pattern . 9
6.5.1 General . 9
6.6 Change pattern . 10
6.6.1 General . 10
6.6.2 Key classes and properties . 10
6.6.3 Formalization . 17
6.7 Location pattern. 17
6.7.1 General . 17
6.7.2 Key classes and properties . 18
6.7.3 Formalization . 19
6.8 Activity pattern .20
6.8.1 General .20
6.8.2 Key classes and properties . 20
6.8.3 Formalization . 24
6.9 Recurring Event pattern .25
6.9.1 General . 25
6.9.2 Key classes and properties . 25
6.9.3 Formalization .28
6.10 Resource pattern .29
6.10.1 General .29
6.10.2 Key classes and properties .29
6.10.3 Formalization .33
6.11 Agent pattern .34
6.11.1 General .34
6.11.2 Key classes and properties .34
6.11.3 Formalization .34
6.12 Organization Structure pattern . 35
6.12.1 General . 35
6.12.2 Key classes and properties . 35
6.12.3 Formalization . 35
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ISO/IEC 5087-1:2023(E)
6.13 Agreement pattern . 35
6.13.1 General . 35
6.13.2 Key classes and properties . 35
6.13.3 Formalization . 37
6.14 Provenance pattern .38
6.14.1 General .38
6.14.2 Key classes and properties .38
6.14.3 Formalization .38
Annex A (informative) Implementation alternatives for additional change semantics .39
Annex B (informative) Relationship to existing standards .41
Annex C (informative) Extended recurring event example .47
Annex D (informative) Location of pattern implementations .48
Bibliography .49
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ISO/IEC 5087-1:2023(E)
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
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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 or
www.iec.ch/members_experts/refdocs).
ISO and IEC draw attention to the possibility that the implementation of this document may involve the
use of (a) patent(s). ISO and IEC take no position concerning the evidence, validity or applicability of
any claimed patent rights in respect thereof. As of the date of publication of this document, ISO and IEC
had not received notice of (a) patent(s) which may be required to implement this document. However,
implementers are cautioned that this may not represent the latest information, which may be obtained
from the patent database available at www.iso.org/patents and https://patents.iec.ch. ISO and IEC shall
not be held responsible for identifying any or all such patent rights.
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. In the IEC, see www.iec.ch/understanding-standards.
This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology.
A list of all parts in the ISO/IEC 5087 series can be found on the ISO and IEC websites.
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 and
www.iec.ch/national-committees.
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ISO/IEC 5087-1:2023(E)
Introduction
The intended audience for this document includes municipal information systems departments,
municipal software designers and developers, and organizations that design and develop software for
municipalities.
Cities today face a challenge of how to integrate data from multiple, unrelated sources where the
semantics of the data are imprecise, ambiguous and overlapping. This is especially true in a world
where more and more data are being openly published by various organizations. A morass of data
is increasingly becoming available to support city planning and operations activities. In order to be
used effectively, it is necessary for the data to be unambiguously understood so that it can be correctly
combined, avoiding data silos. Early successes in data “mash-ups” relied upon an independence
assumption, where unrelated data sources were linked based solely on geospatial location, or a
unique identifier for a person or organization. More sophisticated analytics projects that require the
combination of datasets with overlapping semantics entail a significantly greater effort to transform
data into something useable. It has become increasingly clear that integrating separate datasets for this
sort of analysis requires an attention to the semantics of the underlying attributes and their values.
A common data model enables city software applications to share information, plan, coordinate and
execute city tasks, and support decision making within and across city services, by providing a precise,
unambiguous representation of information and knowledge commonly shared across city services. This
requires a clear understanding of the terms used in defining the data, as well as how they relate to one
another. This requirement goes beyond syntactic integration (e.g. common data types and protocols), it
requires semantic integration: a consistent, shared understanding of the meaning of information.
To motivate the need for a standard city data model, consider the evolution of cities. Cities deliver
physical and social services that have traditionally operated as silos. If during the process of becoming
smarter, transportation, social services, utilities, etc. were to develop their own data models, the result
would be smarter silos. To create truly smart cities, data needs to be shared across these silos. This can
only be accomplished through the use of a common data model. For example, “Household” is a category
of data that is commonly used by city services. Members of Households are the source of transportation,
housing, education and recreation demand. This category represents who occupies a home, their age,
their occupations, where they work, their abilities, etc. Though each city service can potentially gather
and/or use different aspects of a Household, much of the data needs to be shared with each other.
Supporting this interoperability among city datasets is particularly challenging due to the diversity
of the domain, the heterogeneity of its data sources, and data privacy concerns and regulations. The
purpose of this document is to support the precise and unambiguous specification of city data using the
[1],[2] [3]
technology of ontologies as implemented in the Semantic Web . By doing so it will:
— enable the computer representation of precise definitions, thereby reducing the ambiguity of
interpretation;
— remove the independence assumption, thereby allowing the world of Big Data, open source software,
mobile apps, etc., to be applied for more sophisticated analysis;
— achieve semantic interoperability, namely the ability to access, understand, merge and use data
available from datasets spread across the Semantic Web;
— enable the publishing of city data using Semantic Web and ontology standards, and
— enable the automated detection of city data inconsistency, and the root causes of variations.
With a clear semantics for the terminology, it is possible to perform consistency analysis, and thereby
validate the correct use of the document.
Figure 1 identifies the three levels of the ISO/IEC 5087 series. The lowest level, defined in
ISO/IEC 5087-1 (this document) provides the classes, properties and logical computational definitions
for representing the concepts that are foundational to representing any data. The middle level, defined
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ISO/IEC 5087-1:2023(E)
1)
in ISO/IEC 5087-2:— , will provide the classes, properties and logical computational definitions for
representing concepts common to all cities and their services but not specific to any service. The top level
provides the classes, properties and logical computational definitions for representing service domain
2)
specific concepts that are used by other services across the city. For example, ISO/IEC TS 5087-3:— ,
will define the transportation concepts. In the future, additional parts will be added to the ISO/IEC 5087
series covering further services such as education, water, sanitation, energy, etc.
Figure 1 — Stratification of city data model
Figure 2 depicts example concepts for the three levels.
Figure 2 — Example concepts for each level
It is important to distinguish between the ISO/IEC 5087 series and the related, but distinct effort
of ISO/IEC 30145-2. As specified in its Scope, ISO/IEC 30145-2:2020 “specifies a generic knowledge
management framework for a smart city, focusing on creating, capturing, sharing, using and managing
smart city knowledge. It also gives the key practices which are required to be implemented to safeguard the
use of knowledge, such as interoperability of heterogeneous data and governance of multi-sources services
within a smart city.” Figure 3 depicts the smart city knowledge management framework as described
in ISO/IEC 30145-2. The smart city domain knowledge model includes a (cross-domain) core concept
model and several domain knowledge models. This document defines the foundation level of the core
concept model. ISO/IEC 5087-2 is intended to address some of the core concept model and cuts across
1) Under preparation. Stage at the time of publication: ISO/IEC DIS 5087-2:2023.
2) Under preparation.
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ISO/IEC 5087-1:2023(E)
the domain knowledge models. There is a possibility that subsequent parts of the ISO/IEC 5087 series
(not yet defined) will define knowledge models for the services of citizen livelihood, urban management
and smart transportation illustrated in the Figure 3.
Figure 3 — The framework of smart city knowledge management from ISO/IEC 30145-2:2020
There are other existing standards that overlap conceptually with some of the terms presented in this
document. The relationship between ISO/IEC 5087-1 and existing documents that address similar or
related concepts is identified in Annex A.
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INTERNATIONAL STANDARD ISO/IEC 5087-1:2023(E)
Information technology — City data model —
Part 1:
Foundation level concepts
1 Scope
This document is part of the ISO/IEC 5087 series, which specifies a common data model for cities. This
document specifies the foundation level concepts.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements of this document. For dated references, only the edition cited applies. For
undated references, the latest edition of the referenced document (including any amendments) applies.
ISO/IEC 21972, Information technology — Upper level ontology for smart city indicators
OGC GeoSPARQL, A Geographic Query Language for RDF Data, OGC 11-052r4, Open Geospatial
Consortium, 10 September 2012. https:// www .ogc .org/ standards/ geosparql
The Ontology in OWL, W3C Candidate Recommendation 26 March 2020, https:// www .w3 .org/ TR/
owl -time/
PROV-O. The PROV Ontology, W3C Recommendation 30 April 2013, https:// www .w3 .org/ TR/ prov -o/
The Organization Ontology, W3C Recommendation 16 January 2016, https:// www .w3 .org/ TR/
vocaborg/
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:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
3.1
cardinality
number of elements in a set
[SOURCE: ISO/TS 21526:2019, 3.11]
3.2
description logic
DL
family of formal knowledge representation languages that are more expressive than propositional logic
but less expressive than first-order logic
[SOURCE: ISO/IEC 21972:2020, 3.2]
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ISO/IEC 5087-1:2023(E)
3.3
manchester syntax
compact, human readable syntax for expressing Description Logic descriptions
[SOURCE: https:// www .w3 .org/ TR/ owl2 -manchester -syntax/ (Copyright © 2012. World Wide Web
Consortium. https:// www .w3 .org/ Consortium/ Legal/ 2023/ doc -license).]
3.4
measure
value of the measurement (via the numerical_value property) which is linked to both Quantity and
Unit_of_measure
[SOURCE: ISO/IEC 21972:2020, 3.4]
3.5
namespace
collection of names, identified by a URI reference, that are used in XML documents as element names
and attribute names
Note 1 to entry: Names may also be identified by an IRI reference.
[SOURCE: ISO/IEC 21972:2020, 3.5, modified — Note 1 to entry has been added.]
3.6
ontology
formal representation of phenomena of a universe of discourse with an underlying vocabulary including
definitions and axioms that make the intended meaning explicit and describe phenomena and their
interrelationships
[SOURCE: ISO 19101-1:2014, 4.1.26]
3.7
ontology web language
ontology language for the Semantic Web with formally defined meaning
Note 1 to entry: OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as
Semantic Web documents.
[SOURCE: https:// www .w3 .org/ TR/ owl2 -overview/ (Copyright © 2012. World Wide Web Consortium.
https:// www .w3 .org/ Consortium/ Legal/ 2023/ doc -license).]
3.8
quantity
property of a phenomenon, body, or substance, where the property has a magnitude that can be
expressed by means of a number and a reference
Note 1 to entry: Quantities can appear as base quantities or derived quantities.
EXAMPLE 1 Length, mass, electric current (ISQ base quantities).
EXAMPLE 2 Plane angle, force, power (derived quantities).
[SOURCE: ISO 80000-1:2009, 3.1, modified — NOTEs 1 to 6 have been removed; new Note 1 to entry and
two EXAMPLEs have been added.]
3.9
Semantic Web
W3C’s vision of the Web of linked data
Note 1 to entry: Semantic Web technologies enable people to create data stores on the Web, build vocabularies,
and write rules for handling data. The goal is to make data on the Web machine-readable and more precise.
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[SOURCE: https:// www .w3 .org/ standards/ semanticweb/ (Copyright © 2015. World Wide Web
Consortium. https:// www .w3 .org/ Consortium/ Legal/ 2023/ doc -license).]
3.10
unit_of_measure
definite magnitude of a quantity, defined and adopted by convention and/or by law
[SOURCE: ISO/IEC 21972:2020, 3.9]
4 Abbreviated terms and namespaces
DL description logic
OWL ontology web language
RDF resource description framework
RDFS resource description framework schema
IRI international resource identifier
The following namespace prefixes are used in this document:
— activity: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ Activity/
— agent: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ Agent/
— agreement: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ Agreement/
— change: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ Change/
— cityunits: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ CityUnits/
— genprop: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ GenericProperties/
— geo: http:// www .opengis .net/ ont/ geosparql #
— i72: http:// ontology .eil .utoronto .ca/ 5087/ 2/ iso21972/
— loc: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ SpatialLoc/
— mereology: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ Mereology/
— org: http:// www .w3c .org/ ns/ org #
— org_s: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ Or ganizationStructure/
— owl: http:// www .w3 .org/ 2002/ 07/ owl #
— partwhole: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ Mereology/
— prov: http:// www .w3 .org/ ns/ prov -o #
— 5087prov: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ Prov/
— rdf: http:// www .w3 .org/ 1999/ 02/ 22 -rdf -syntax -ns #
— rdfs: http:// www .w3 .org/ 2000/ 01/ rdf -schema #
— recurringevent: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ RecurringEvent/
— resource: https:// standards .iso .org/ iso -iec/ 5087/ -1/ ed -1/ en/ ontology/ Resource/
— time:
...