ISO 37166:2022

INTERNATIONAL ISO
STANDARD 37166
First edition
2022-02
Smart community infrastructures —
Urban data integration framework for
smart city planning (SCP)
Infrastructures urbaines intelligentes — Cadre d'intégration des
données urbaines pour la planification des villes intelligentes
Reference number
ISO 37166:2022(E)
© ISO 2022

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ISO 37166:2022(E)
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© ISO 2022
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
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Published in Switzerland
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ISO 37166:2022(E)
Contents Page
Foreword .v
Introduction . vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Principles . 3
4.1 General . 3
4.1.1 General . 3
4.1.2 Data availability . 3
4.1.3 Sovereignty over the data . 3
4.1.4 Data security . 3
4.1.5 Data privacy . . 3
4.1.6 Co-construction and sharing . 4
4.2 Principles of heterogeneous data integration . 4
4.2.1 General . 4
4.2.2 Unambiguity . 4
4.2.3 Scalability . 4
4.2.4 Compatibility . 4
4.2.5 Modularity . 4
4.3 Data quality recommendations . 4
5 Data of SCP on community infrastructure . 5
5.1 General . 5
5.2 Usage of community infrastructure data . 5
5.2.1 Construction project life cycle . 5
5.2.2 Urban simulation . 6
5.2.3 Smart transportation . 6
5.2.4 Smart grid . 6
5.2.5 Smart environmental sanitation . 6
5.3 Smart city planning (SCP) data . 6
5.4 Community infrastructure data . 11
5.4.1 General . 11
5.4.2 Data definition . 11
5.4.3 Source of heterogeneous planning data .13
6 SCP data integration framework .13
6.1 General .13
6.2 Integration subjects .13
6.3 Integration objects . 13
6.4 Integration process . 14
6.5 Integration results . 14
7 SCP data integration . .15
7.1 General . 15
7.2 Data model and description specification . 15
7.3 Data extraction and system exchange . 16
7.4 Data quality verification . 16
7.5 Data encoding or mapping specification . 16
7.6 Smart community infrastructure data entities . 16
7.7 Heterogeneous data integration . 18
7.8 Date management recommendations . 18
7.8.1 General . 18
7.8.2 Data exchange and sharing . 18
7.8.3 Data exchange and sharing security . 18
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ISO 37166:2022(E)
8 Management of security and privacy .18
8.1 General . 18
8.2 Data security level and protection principles . 19
8.3 Technical advice for data security . 19
8.4 Life cycle safety of data . 19
8.5 System security protection .20
Annex A (informative) Case studies .21
Bibliography .27
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ISO 37166:2022(E)
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.
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 ISO documents 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 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).
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 Technical Committee ISO/TC 268, Sustainable cities and communities,
Subcommittee SC 1, Smart community infrastructures.
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.
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ISO 37166:2022(E)
Introduction
The city is a product of social evolution, technology, economic and social civilization improvements, as
well as a fundamental unit for the social and economic life of its region. However, with the influence of
global urbanization, increasingly more problems have been observed, such as environmental pollution,
traffic congestion, insufficient resources and urban lifeline system weakness.
Urban planning refers to the conduct of engineering construction, economy, society, environment and
land use of the city and its surroundings. It involves the regional layout of industry, the regional layout
of buildings, the setting of transportation infrastructure and the planning of urban engineering. It is
related to urban development and city infrastructure construction.
The planning, construction, operation, management and evaluation of community infrastructure is
the process of natural environment transformation. This process involves multiple city managers and
various data. Therefore, the integration of heterogeneous data for smart community infrastructure
planning is particularly important. Based on ecological and spatial information, the smart city planning
(SCP) data and infrastructure data that need to be integrated should be analysed. The establishment of
a data integration framework and further realization of heterogeneous data integration is intended to
support the operation of community infrastructure construction projects throughout their life cycles
and ultimately achieve inclusive, sustainable and high-quality development of the city.
In terms of smart community infrastructure, ISO/TS 37151 describes the principles and requirements
of performance metrics. ISO/TR 37152 gives possible issues and solutions in developing and operating
smart community infrastructure, outline and benefits of a common framework for development and
operation. In addition, BS/PAS 183 provides data interoperability, types of data, data protection reform,
data value chain, purposes for data use, assessing data states, access rights for data and data structure.
ISO/TS 37151, ISO/TR 37152 and BS/PAS 183 provide the basis and guidance for ISO 37156, which
describes the types and model, opportunities, privacy and security of data exchange and sharing,
and provides guidance for data exchange and sharing of smart community infrastructure. ISO 37156
provides guidance for the integration of infrastructure data in this document, and this document is
considered to be an application scenery of ISO 37156 in data integration.
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INTERNATIONAL STANDARD ISO 37166:2022(E)
Smart community infrastructures — Urban data
integration framework for smart city planning (SCP)
1 Scope
This document establishes a data framework that involves possible multi-source common data through
standardized data integration and sharing mechanisms. It includes recommendations for:
— precision, dimensions of the data, data collection, updates and storing mechanisms;
— a data model for data integration, data standardization and data fusion approaches for heterogeneous
smart city infrastructure data;
— a data security level and sharable attributes for all involved data, principles on data sharing or
exchange.
This document focuses on the integration and application of heterogeneous data from urban
infrastructure systems, such as water, transport, energy, drainage and waste, so as to support smart
city planning (SCP). It contains case studies, in Annex A, of various smart city projects.
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 terminological 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
data
reinterpretable representation of information in a formalized manner suitable for communication,
interpretation or processing
Note 1 to entry: Data can be processed by humans or by automatic means.
[SOURCE: ISO/IEC 2382:2015, 2121272]
3.2
data availability
property of being accessible and usable upon demand by an authorized entity
[SOURCE: ISO/IEC 27000:2018, 3.7, modified — term revised.]
3.3
data exchange
accessing, transferring, and archiving of data (3.1)
[SOURCE: ISO/TS 13399-5:2014, 3.7, modified — definition revised.]
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ISO 37166:2022(E)
3.4
data sharing
reference for providing shared, exchangeable and extensible data (3.1) to enable urban infrastructure
service
[SOURCE: ISO 37156:2020, 3.3.6, modified — definition revised.]
3.5
data type
defined set of data (3.1) objects of a specified data structure and a set of permissible operations, such
that these data (3.1) objects act as operands in the execution of any one of these operations
[SOURCE: ISO/IEC 20546:2019, 3.1.12, modified — Notes to entry removed.]
3.6
heterogeneous data integration
optimization method to enable effective and transformative use of data and technology from multi-
source to support sustainable development of cities and to improve the management and control of
space and resources
3.7
information
data (3.1) in context with a particular meaning
[SOURCE: ISO5127: 2017, 3.1.1.16, modified — definition revised.]
3.8
information resource
asset
record
document or item in physical or digital form that contributes to human knowledge
EXAMPLE Abstracting and indexing database.
Note 1 to entry: Information resource sometimes has a broader meaning, including information content, and also
technology resources, human resources and financial resources that enable information content management.
[SOURCE: ISO 5127:2017, 3.1.1.44; modified — definition revised and Note 2 to entry added.]
3.9
life cycle
evolution from conception through
to destruction or recycling
[SOURCE: ISO/IEC/IEEE 15288:2015, 4.1.23, modified — definition revised.]
3.10
security
condition that results from the establishment and maintenance of protective measures that ensure a
state of inviolability from hostile acts or influences
[SOURCE: IEC Guide 120:2018, 3.13]
3.11
smart community infrastructure
community infrastructure with enhanced technological performance that is designed, operated and
maintained to contributed to sustainable development and resilience of the community
[SOURCE: ISO 37156:2020, 3.1.4]
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ISO 37166:2022(E)
3.12
smart city planning
SCP
technical and political process concerned with the development and design of land use and the built
environment, which are enhanced by the effective and sustainable integration of informational,
physical and social systems and the transformative use of heterogeneous data and technology
3.13
system
set of interrelated or interacting functions constituted to achieve a specified objective
4 Principles
4.1 General
4.1.1 General
The data gathered and to be integrated for SCP should meet some general principles so as to ensure the
validity of the following data integration process.
4.1.2 Data availability
The data to be integrated for SCP comes from various sources, some of which are private and classified
prior to any data-sharing agreements. Thus, the description of shared data in terms of, for example,
attributes, dimensions and volumes should be available to associated integration subjects (described
in 6.2), so as to determine whether the shared data are truly available for the intended data integration
purpose.
4.1.3 Sovereignty over the data
The ownership of the source data needs to be respected during the whole data integration process
among associated stakeholders.
4.1.4 Data security
The data to be integrated for SCP should be secured during the data integration process, from data
retrieval, data clean, data storage and data output.
Regional and national security requirements such as the EU General Data Protection Regulation shall
be considered. Based on ISO/IEC 27000, considering domestic regulations and technological conditions,
an information security management systems (ISMS) or alternative necessary data security procedure
and tools should be introduced to deter possible hacker attacks and other misapplication.
The data exchange should therefore be kept to a minimum and a low level of detail. Security-relevant
data for planning, constructing, operating and managing of infrastructures should basically remain
with the data-collecting organization, ordinarily the utilities.
4.1.5 Data privacy
The data from community infrastructure to be integrated for SCP usually contains private information,
from individual socio-economic characteristics to spatial-temporal behavioural data. Integrating
and further analysing these individual-based data help to evaluate and optimize urban system
performances. But individual privacy should be respected.
The use of source data during the whole integration process should be kept on an anonymous basis. The
integration of individual data, for example consumer consumption data, should be pre-desensitized,
without personal information being exposed to either data integration engineers or terminal users.
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ISO 37166:2022(E)
4.1.6 Co-construction and sharing
It is possible that an intended data integration requires data from different agencies or stakeholders.
It is recommended that the necessary data are co-constructed and shared among them on a voluntary
basis. In addition, the integration results should be shared with contributors.
4.2 Principles of heterogeneous data integration
4.2.1 General
In practice, the multi-source data used for data integration varies in format, dimensions, accuracy and
durability. Although data integration approaches are evolving with more recognition or explanation
power, it is not usually encouraged to spend huge amounts on retrieving missing data. Depending on
the availability and intended use of data, it is recommended that the data integration framework applies
the following principles of heterogeneous data integration.
4.2.2 Unambiguity
The definitions and categorizations of entities should be clear where reasonably possible and available.
Categorization should be representative and mutually exclusive.
4.2.3 Scalability
Urban data integration requirements and process are continuously updating. The integrated data need
not be thoroughly completed and comprehensive in the beginning, but it is recommended that the
integration results are flexible and scalable.
4.2.4 Compatibility
Data standards applied in the data integration framework shall be compatible with existing major
urban data standards.
4.2.5 Modularity
It is recommended that data integration input, output and approaches or algorithms are defined as
modular components, so as to be used individually or in combination for different integration purposes.
In addition to unambiguity, scalability, compatibility and modularity, the urban data integration
framework should also have extensibility and interpretability. Maintaining a high level of
interpretability is vital during the integration process as the goal is to support the urban design and
operational decisions by municipal officials, policymakers and engineer technical staff. A useful urban
data integration framework should be capable of integrating heterogeneous data in an extensible (to
multiple urban systems), scalable (to the growing amounts of quickly changing urban data streams)
and interpretable manner (such that it can inform decision-making).
4.3 Data quality recommendations
On the basis of ISO 19157, the following recommendations are dependent on the intended use of
data. For example, zonal plans can be acceptable with a tolerance of several metres but plans for
individual buildings might require an absolute positional accuracy of a few centimetres. The quality
recommendation of a variety of planning data database results should ensure locational accuracy,
attribute accuracy, completeness, logical consistency, geographic quality and data relationality as far as
the data are available and it is even possible to determine such data.
a) Locational accuracy. It is recommended that the location given in the data satisfies data requirement
in terms of geographic accuracy.
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ISO 37166:2022(E)
b) Attribute accuracy. It is recommended that attribute values given in the data match the actual
values in the real world to the extent required by the expected use. For example, no building should
be classified as a pavement, but it can sometimes matter less if a building is classified as residential
when it is in fact partly commercial.
c) Completeness. It is recommended that the number of missing or excess data items in the data set,
in comparison to the real world, are suitable for the intended use. For example, all planning data
should contain exactly the same number of plans as actually exist, but it might not be too important
if a zonal plan contains slightly more or fewer building features.
d) Logical consistency. It is recommended that the data are logically consistent with the requirements,
in terms of concept consistency, value domain consistency and topology consistency. For example,
no plan should be described as agreed if it is only proposed; it is unlikely that a road would not have
a postal address.
e) Geographic quality. It is recommended that the geometry of the data conveys the actual data
correctly. For example, buildings are defined as polygons instead of a point when the intended
use is to correlate retail shops with a metro station spatially; the boundaries of adjacent polygon
entities coincide.
f) Data relationality. It is recommended that entities being referenced by different data sources
are mapped and related to other entities through the data model defined in the data integration
framework.
It is also noteworthy that low-quality data can still be relevant and used to identify or understand the
urban environment and phenomena that are poorly documented, but high-quality data allows for more
accurate decision-making.
5 Data of SCP on community infrastructure
5.1 General
Community infrastructure is the fundamental safeguard for residents’ lives and city development.
It incorporates various equipment and systems which are utilized for economic and social activities.
Urban infrastructure is still promoting living and economic development, but its impact on ecosystems
cannot be ignored. Technology conditions
...