ISO 37114:2025
(Main)Sustainable cities and communities — Appraisal framework for datasets and data processing methods that create urban management information
Sustainable cities and communities — Appraisal framework for datasets and data processing methods that create urban management information
This document provides: — an appraisal framework for datasets and data processing methods that create and use urban management information derived from statistics, objectives, indicators and long-term goals for sustainable development of cities and communities; — numerous combinations of data sources and data processing methods, making it easier to create and maintain urban management information and get ready for value mining of big data within cities and communities; — approaches to appraise the necessary data to generate management information in an organization and how to classify them into different categories for regular review and update over time; — functional requirements to support the design, daily operation and management of information systems. This document is designed to be compatible with artificial intelligence (AI) systems. It helps cities and communities prepare for the application of AI in digital fields towards sustainable development. This includes the adoption of AI systems to process and analyse data collected from various sources. The goal is to identify and solve problems that cities and communities face to aid decision-making and achieve the six sustainability purposes as provided in ISO 37101, which align with the UN Sustainable Development Goals (SDGs) in the long term. This document is in line with the delivery principles of a smart city provided by ISO 37106, including visionary, citizen-centric, digital, open and collaborative. This document is useful for support data and dataset management for standards on indicators for sustainable cities and communities developed by ISO/TC 268, but does not provide guidance on how to use those standards. Additionally, this document can be of use in research and educational activities.
Villes et communautés territoriales durables — Cadre d'évaluation pour les jeux de données et les méthodes de traitement des données qui génèrent des informations de gestion urbaine
General Information
Standards Content (Sample)
International
Standard
ISO 37114
First edition
Sustainable cities and
2025-05
communities — Appraisal
framework for datasets and data
processing methods that create
urban management information
Villes et communautés territoriales durables — Cadre
d'évaluation pour les jeux de données et les méthodes de
traitement des données qui génèrent des informations de gestion
urbaine
Reference number
© ISO 2025
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Published in Switzerland
ii
Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
3.1 Terms related to urban management information .2
3.2 Terms related to artificial intelligence (AI) .2
3.3 Terms related to data.3
4 Understanding the context of the appraisal framework . 4
4.1 General .4
4.2 Objectives for creating urban management information .4
4.3 Principles for establishment of appraisal framework .5
4.3.1 General .5
4.3.2 Principles related to the visionary community .5
4.3.3 Principles related to the citizen-centric community .5
4.3.4 Principles related to the digital community .5
4.3.5 Principles related to the open and collaborative community .6
4.4 Mapping the scenario of containing datasets and data processing methods .6
4.5 Engaging all interested parties along the data value generation chain .6
5 Overview of the appraisal framework . 7
6 Appraisal framework recommendations for the indicators classes . 9
6.1 General .9
6.2 Description of classes .10
6.2.1 Indicator class .10
6.2.2 Indicator classification class .10
6.2.3 Metadata record class .11
6.3 Artificial intelligence (AI) applications in indicators .11
7 Appraisal framework recommendations for the processing classes .11
7.1 General .11
7.2 Description of classes . 12
7.2.1 Process class . 12
7.2.2 Product specification class . 12
7.3 Description of enumeration class . 13
7.4 Artificial intelligence (AI) applications in dataset processing . 13
8 Appraisal framework recommendations for the datasets classes .13
8.1 General . 13
8.2 Description of classes .14
8.2.1 Dataset class .14
8.2.2 Metadata record class . 15
8.2.3 Value appraisal class . 15
8.3 Description of enumeration classes . 15
8.3.1 Source type class . 15
8.3.2 Geographic metadata class .16
8.3.3 Measurement method type class .17
8.3.4 Frequency of data collection class .17
8.3.5 Other classification class .18
8.4 Artificial intelligence (AI) applications in datasets .18
9 Feature catalogue .18
9.1 General .18
9.2 Indicator class .18
9.3 Indicator classification class . 20
iii
9.4 Indicator classification class: Purpose type .21
9.5 Indicator classification class: Category type . 22
9.6 Indicator classification class: Topic type . 23
9.7 Metadata record class .24
9.8 Process class . 25
9.9 Product specification class .27
9.10 Status type class. 28
9.11 Dataset class . 28
9.12 Value appraisal class . 30
9.13 Source type class .32
9.14 Geographic metadata class . 33
9.15 Measurement method type class . 33
9.16 Frequency of data collection class . 34
9.17 Other classification class . 35
Annex A (informative) An example for implementation of the appraisal framework .37
Annex B (informative) Detailed overall figure .39
Bibliography . 41
iv
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 collaborate
...
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