ISO/IEC 25005-1:2026

International
Standard
ISO/IEC 25005-1
First edition
Information technology — Data use
2026-07
in smart cities —
Part 1:
Framework
Technologies de l'information — Utilisation des données dans les
villes intelligentes —
Partie 1: Cadre général
Reference number
© ISO/IEC 2026
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© ISO/IEC 2026 – All rights reserved
ii
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Abbreviated terms . 3
5 Overview of the general framework and development principles . 3
5.1 General framework .3
5.2 Development principles for data use framework in smart cities .4
6 Description of core characteristics of considerations . 5
6.1 General .5
6.2 Sub-characteristics of considerations about data availability .5
6.3 Sub-characteristics of considerations about data quality assurance .5
6.4 Sub-characteristics of considerations about ease of data use .6
6.5 Sub-characteristics of considerations about data use security .6
6.6 Sub-characteristics of considerations about data-enabled innovation .7
Annex A (informative) Examples of the sub-characteristics of considerations concerning data
use in smart cities . 8
Bibliography .16

© ISO/IEC 2026 – 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
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The procedures used to develop this document and those intended for its further maintenance are described
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IEC Directives, Part 2 (see www.iso.org/directives or www.iec.ch/members_experts/refdocs).
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This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology.
A list of all parts in the ISO/IEC 25005 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.

© ISO/IEC 2026 – All rights reserved
iv
Introduction
This document provides an integrated framework for data use that supports the multidimensional use of
data as citywide strategic resources and assets. It aims to facilitate evidence-based decision making and
enable data-based, data-driven and data-enabled smart cities development and applications.
Data use involves activities enabling data value realization for specific purposes in smart cities along the
data value chain. This document is intended to assist in identifying problem-solving strategies and solutions
for data use, data applications and data services citywide, including but not limited to data being not
available when needed, data being not trusted when used, data not being easily used when available, data
not being used securely and data value not being realized when in use.
This document provides a framework for data use in smart cities across five dimensions:
— data availability (ensuring data are accessible);
— data quality assurance (ensuring data are useful);
— ease of data use (ensuring data are easy to use);
— data use security (ensuring data are used securely);
— data-enabled innovation (ensuring data are used for enabling intelligent applications and services).
This document enhances the total capabilities of data use to support data-based, data-driven and data-
enabled citywide information communication technology (ICT), big data and artificial intelligence (AI)
applications and smart cities services. It is intended to fill the gaps in standards development for better
collaboration and harmonization of sustainable data use considerations for smart cities from different
standards development organizations (SDOs), to satisfy the maximized needs of multiple stakeholders from
many views and various dimensions, e.g. effective, sustainable, comprehensive and innovative use of data as
strategic resources and assets citywide.
This document can be used for citywide data use planning, deployment of design, implementation and
management in smart cities development and applications.
The ISO/IEC 25005 series consists of three parts. This document provides foundations for standards
collaboration on data use citywide and provides basic principles and core characteristics of considerations
concerning the other parts in the series.
Figure 1 provides the relations among this document, ISO/IEC TR 25005-2 and ISO/IEC TS 25005-3,
describing guiding principles for data use in smart cities, core characteristics of considerations of data use
in smart cities which are the basis for data use in smart cities standard series.

© ISO/IEC 2026 – All rights reserved
v
Figure 1 — ISO/IEC 25005 series

© ISO/IEC 2026 – All rights reserved
vi
International Standard ISO/IEC 25005-1:2026(en)
Information technology — Data use in smart cities —
Part 1:
Framework
1 Scope
This document provides a framework for data use in smart cities, based on five dimensions:
— data availability (data are available);
— data quality assurance (data are useful);
— ease of data use (data are easy to use);
— data use security (data are used securely);
— data-enabled innovation (data are used for enabling intelligent applications and services).
This framework is intended to facilitate effective, sustainable, comprehensive and innovative use of data as
citywide strategic resources and assets.
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:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
3.1
data availability
property of being accessible and usable upon demand by an authorized entity
[SOURCE: ISO 37166:2022, 3.2]
3.2
data exchange
representation, transmission, reception, storage, and retrieval of data
[SOURCE: ISO/IEC 20944-1:2013, 3.21.13.1, modified — The preferred term “data interchange” has been
removed; Note 1 to entry has been deleted.]
3.3
data-enabled innovation
extent to which data are used by specified users to achieve specified goals with data-enabled monitoring
applications, data-enabled early warning and prediction applications, data-enabled intelligent decision-
making applications in a specified context of use

© ISO/IEC 2026 – All rights reserved
3.4
data quality
degree to which a set of inherent characteristics of data fulfils requirements
[SOURCE: ISO 8000-2:2022, 3.8.1, modified — Note 1 to entry has been deleted.]
3.5
data quality assurance
assurance of data quality (3.4)
Note 1 to entry: The quality requirements include completeness, authenticity, reliability, timeliness, accuracy,
consistency, and traceability.
3.6
data security
preservation of data to guarantee availability, confidentiality and data integrity
[SOURCE: ISO/IEC 29182-2:2013, 2.6.6]
3.7
data sharing
access to or processing of the same data by more than one authorized entity
Note 1 to entry: Use of the data can be synchronous or asynchronous.
Note 2 to entry: Data can be shared, for example, (i) by allowing access to, or the execution of operations over, the
original dataset, or (ii) by giving a copy of the data to the interested entity.
Note 3 to entry: The way in which data is shared fundamentally influences the available controls and the statements
needed in a data sharing agreement.
[SOURCE: ISO/IEC 23751:2022, 3.7]
3.8
data use
handling or dealing with data for a specific purpose
Note 1 to entry: In smart cities, data use refers to activities enabling data value realization along with data value-chain,
including data availability, data quality assurance, ease of data use, data use security, and data-enabled innovation
from citywide multi-stakeholder’s interests.
[SOURCE: ISO/IEC 5207:2024, 3.30, modified — Note 1 to entry has been changed.]
3.9
data use security
extent to which data can be used by specified users to achieve specified goals with effectiveness, efficiency,
inclusiveness, safety and security in a specified context of use
3.10
data value
importance that stakeholders attach to data and which is related to the perception of actual or potential
benefit
Note 1 to entry: Data value ranges from immediate operational enhancements to long-term strategic gains for urban
development and citizen’s quality of life.
[SOURCE: ISO 16439:2014, 3.75, modified — The preferred term has been expanded from “value” to “data
value ”; in the definition, “funding institutions, politicians, the public, users, staff” has been deleted and
“libraries” has been replaced by “data”, Note 1 to entry has been changed.]

© ISO/IEC 2026 – All rights reserved
3.11
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 systems, digital systems and social systems and
the transformative use of data and technology
[SOURCE: IEC 60050-831:2025, 01-19, modified — Notes 1 and 2 to entry have been deleted.]
4 Abbreviated terms
AI artificial intelligence
ERAC electrical regulatory authorities council
ICT information communication technology
SDO standards development organization
UAS uncrewed aircraft system
5 Overview of the general framework and development principles
5.1 General framework
A general framework for comprehensive use of data in smart cities is shown in Figure 2. The core
characteristics of considerations are categorized into five dimensions, with 28 sub-characteristics of
considerations from various demands for data-based value support, data-driven value support, data-enabled
value support. The five dimensions are data availability, data quality assurance, ease of data use, data use
security and data-enabled innovation.

© ISO/IEC 2026 – All rights reserved
Figure 2 — General framework for data use in smart cities
5.2 Development principles for data use framework in smart cities
When determining core characteristics and sub-characteristics of considerations and building the data use
framework in smart cities, the following eight guiding principles are considered:
a) Citizen-centric data value realization awareness: Ensure that citizens considerations are taken into
consideration as a whole to improve total quality of city service and to produce improved results in
smart cities.
b) Awareness of data as strategic resources and assets for citywide use: Ensure that data are managed and
used as strategic resources and assets throughout their lifecycle to support citywide public interests.
c) By design and default empowered data use: Ensure data availability, data trust, data connectivity and
data responsibility and intelligent services are deployed in the development of smart city to support
data-based, data-driven and data-enabled innovation and data services citywide.

© ISO/IEC 2026 – All rights reserved
d) Availability enabled data use: Ensure that data are available when needed in accordance with regulatory
requirements and agreements in smart cities, and data copyright and ownership should be included in
regulatory requirements and agreements.
e) Trustworthiness enabled data use: Ensure that data are useful and trustworthy when in use to enable
trustworthiness in business and service in smart cities.
f) Connectivity enabled data use: Ensure that data are easy to use and interoperable to enable connected
services across domains and systems in smart cities.
g) Responsibility enabled data use: Ensure that data are used responsibly to enable secure, fair, ethical,
inclusive, sustainable, transparent and accountable services across time, space, events, scenarios in
smart cities.
h) Intelligent services enabled data use: Ensure that data are used for enabling intelligent predictions and
actions, e.g. the smart activities such as data use planning and design, data analysis and application.
6 Description of core characteristics of considerations
6.1 General
In this document, tables are used to define core characteristics of considerations. Each table defines the
relevant sub-characteristics of considerations. The examples include both positive and negative use of data
in different scenarios from different countries, see Annex A.
6.2 Sub-characteristics of considerations about data availability
Sub-characteristics of considerations concerning data availability are shown in Table 1.
Table 1 — Sub-characteristics of considerations about data availability
Sub-characteristics of
Description
considerations
Extent to which products, systems, services, environments and facilities can be used
Network infrastructure
by people from a population with the widest range of characteristics and capabili-
accessibility
ties to achieve a specified goal in a specified context of use in associated with data.
Ability of ICT and smart cities associated with data that is designed to benefit to all
Inclusiveness
population segments, including persons with disabilities.
Data accessibility Degree to which data is easy to use by all people, including those with disabilities.
Coverage of data use in city Ability of ICT and smart cities infrastructure that covers many types of data demands
administration data resources from various types of stakeholders including scalability of data volume, various types
holdings of data across time, space, event, subjects and domains.
Benefits that a city derives from empowering the city community through city data
Contribution of government in
and delivering integrated citizen-centric services are magnified the more citizens
data use
and businesses engage with city services through digital channels.
Government-enterprise coopera- Impact of government-enterprise cooperation on developing public information infra-
tion on data opening and use structure, providing innovation services and promoting efficient urban governance.
Government-citizen
cooperation on data opening Impact of government-citizen cooperation on improving citizen services.
and use
Activities include formulation and enforcement of data related laws, regulations
Data laws, regulations and
and policies in a jurisdiction on data governance, data opening, data use, security
policies
protection, data copyright and ownership.
6.3 Sub-characteristics of considerations about data quality assurance
Sub-characteristics of considerations concerning data quality assurance are shown in Table 2.

© ISO/IEC 2026 – All rights reserved
Table 2 — Sub-characteristics of considerations about data quality assurance
Sub-characteristics of
Description
considerations
Degree to which data supports all the specified contents that are specified by the user for
Completeness
an intended purpose.
Authenticity Property of data that is what it claims to be.
Property of data that can be proven to be true under given conditions or consistent with
Reliability
intended behaviour and results.
Timeliness Degree to which data represent reality from the required point in time.
Accuracy Measure of closeness of the data values accepted as being true.
Degree of uniformity, standardization and freedom from contradiction among the documents,
Consistency or parts of a system or component, in terms of data provenance, data traceability, data integ-
rity, data reliability, data authenticity, no matter where the data are stored.
Discernible association among two or more logical entities, such as data provenance, data
Traceability
authenticity, data reliability, data integrity, data consistency.
6.4 Sub-characteristics of considerations about ease of data use
Sub-characteristics of considerations concerning ease of data use are shown in Table 3.
Table 3 — Sub-characteristics of considerations about ease of data use
Sub-characteristics of
Description
considerations
Systematic plan or arrangement for a task or activity to accurately share data for specific
Data sharing schemes
purposes with agreed conditions.
Systematic plan or arrangement for a task or activity to open data for maximized realization
Data opening schemes
of data value without compromise of any stakeholder’s interests.
Ability of two or more systems or applications to exchange information and to mutually
Interoperability use the information that has been exchanged, in terms of ease of data use in cities; multiple
stakeholders’ considerations about interoperability should be included.
Property for a dataset that it is possible to associate (by linking) a record concerning a data
Linkability
principal with a record concerning the same data principal in a separate dataset.
Users’ perceptions and responses that result from the use or anticipated use (or both) of a
system, product or service.
NOTE 1 Users’ perceptions and responses include the users’ emotions, beliefs, preferences,
perceptions, comfort, behaviours and accomplishments that occur before, during and after
User experience of
use.
convenience
NOTE 2 User experience is a consequence of brand image, presentation, functionality,
system performance, interactive behaviour and assistive capabilities of a system, product
or service. It also results from the user’s internal and physical state resulting from prior
experiences, attitudes, skills, abilities and personality, and from the context of use.
Performance measure giving the ratio between the information demand and the satisfaction
expressed by the information user with the information service provided.
This requires professionalism, convenience, timeliness and efficiency of data-based, da-
User satisfaction
ta-driven and data-enabled services obtained by users (including government, enterprises,
citizens, etc.), which is the users’ feedback on the use of the platform, so as to facilitate the
continuous improvement of the platform in smart cities.
6.5 Sub-characteristics of considerations about data use security
Sub-characteristics of considerations concerning data use security are shown in Table 4.

© ISO/IEC 2026 – All rights reserved
Table 4 — Sub-characteristics of considerations about data use security
Sub-characteristics of
Description
considerations
Systematic control plan or arrangement for a task or activity for verifying the identity
Data use authentication
of a user, process or device, often as a prerequisite to allowing access to data resources
control schemes
in an information system.
Systematic control plan or arrangement for a task or activity to protect security and
Data use security and
privacy of data use to meet regulatory and technical requirements, social and ethical
privacy control schemes
considerations.
Systematic plan or arrangement of protocols, processes and technologies based on the
Data monitoring and early
public warning policy to deliver and alert messages in a developing emergency situation
warning schemes
to people at risk and to first responders.
Personal data operation Systematic plan or arrangement relating to the protection of natural persons with regard
schemes to the processing of personal data and the free movement of personal data.
6.6 Sub-characteristics of considerations about data-enabled innovation
Sub-characteristics of considerations concerning data-enabled innovation are shown in Table 5.
Table 5 — Sub-characteristics of considerations about data-enabled innovation
Sub-characteristics of
Description
considerations
Data-enabled monitoring Data are used for enabling real-time statistics, analysis and report on the status of
applications smart cities development and applications.
Data-enabled early warning Data are used for enabling the prediction and early warning of abnormal conditions
and prediction applications of smart cities development and applications.
Data-enabled intelligent Data are used for enabling to interpret data, information and knowledge; to identify
decision-making applications and adapt to changes; and to improve prediction and action for cities.

© ISO/IEC 2026 – All rights reserved
Annex A
(informative)
Examples of the sub-characteristics of considerations concerning
data use in smart cities
A.1 Overview
This annex provides examples of the sub-characteristics of considerations about data use in smart cities
adopted from ISO/IEC TR 25005-2:2025. These examples are collected by ISO/IEC JTC 1 and provided by
various countries around the world, e.g. China, Canada, the United States of America, Australia, the Republic
of Korea, Japan, etc. The examples of sub-characteristics of considerations concerning data use in smart
cities are shown in Clause A.2, Clause A.3, Clause A.4, Clause A.5 and Clause A.6.
A.2 Examples of sub-characteristics of considerations about data availability
Table A.1 provides examples of sub-characteristics of considerations about data availability in practice.
Table A.1 — Examples of sub-characteristic
...