In the era of digitalisation, data-driven organisations and data quality are more relevant than ever. Data are a key asset of any organisation. Therefore, the adoption of governance frameworks to guide the use, storage and sharing of data is essential. This chapter discusses the relevance of data governance in the framework of smart cities. It begins with a discussion on the relevance of data governance. It then examines national efforts to enable smart cities and data governance. It concludes with a review of the main challenges to promoting smart cities and data governance.
Smart City Data Governance
Challenges and the Way Forward
OECD Urban Studies
1. Why does data governance matter for smart cities?
Abstract
Introduction
The uptake of digital technologies and infrastructure is accelerating. It is estimated that nearly two-thirds of the global population will have Internet access and the number of devices connected to Internet protocol (IP) networks will be more than 3 times the global population (29.3 billion networked devices) by 2023 (Cisco, 2020[1]). Increased urbanisation calls for an optimisation of the processes in urban space and digitalisation provides an opportunity to collect and analyse data more efficiently for effective decision making. Equipping cities with sensors and ubiquitous computers to generate data about city life (e.g. on traffic congestion, air pollution, water usage, potential natural hazards, public utilities such as roads, electricity and water) and using information about residents and urban communities to inform law enforcement, healthcare and other crucial public services are often at the heart of smart city projects. This chapter discusses the importance of smart city data governance. It explains the concept of smart cities, followed by different arguments on the relevance of smart city data governance. It then presents the international experience of promoting smart cities and the challenges countries and cities face to build smart cities and improve data governance.
Understanding smart cities and data
Digitalisation is paving the way for smart cities
Digital transformation allows for collecting and managing data, enabling governments and private sector companies to provide better public services. For example, Internet of Things (IoT) technology allows governments and enterprises to establish a more direct connection with citizens and collect new data that can feed into policies and eventually new and improved services. Digitalisation is also changing how people live by connecting machines, vehicles, infrastructure and buildings rather than users (WEF, 2020[2]). In Paris, France, digital technologies are used to simplify user interactions with public services by facilitating their use, saving time and personalising services as well as reducing energy use and the carbon footprint, understanding how outdoor spaces are used and how future developments may impact public areas (Mairie de Paris, 2020[3]). Digital technologies are helping cities prepare for more regular floods, heatwaves, droughts and other events that impact people’s health, well-being and safety. Using smart technologies for construction design can also contribute to decarbonising buildings and construction to make cities and urban life more sustainable through energy efficiency improvements (OECD, 2022[4]).
The COVID-19 pandemic has accelerated digitalisation across the world. Between 2019 and 2020, broadband adoption grew by 4.8% across the world and even by 9.8% in Latin America (Jung and Katz, 2022[5]). However, innovating in digital technologies does not necessarily mean a country has embraced digitalisation. For example, despite a global reputation for impressive technological progress and citizen awareness of embracing digital technology, Japan’s public sector – and a good portion of its private sector – has been slow to embrace the digital era.1 Before COVID-19, central and local governments had their own strategy for promoting digitalisation, resulting in 1 700 systems procured and managed separately and with dispersed responsibility. This fragmentation made the response to the pandemic ineffective and the outdated and cumbersome administrative systems hampered policy responses (Makishima, 2022[6]).
Digitalisation is transforming the way cities are conceived and work, as the use of digital technologies covers almost every aspect of urban life. For example, smart meters and pipes are used to track water quality and leaks, smart grids to manage energy consumption, smart homes to manage energy demand, autonomous cars and car-sharing platforms to improve mobility and alleviate pressure on land use, smart sensors and videos to improve traffic flow and public safety, etc. (BrighterAI, 2023[7]).
Digital technologies were used to mitigate transmission risks during the pandemic. Non-traditional sources of data such as Internet search requests, mobility tracking from mobile phones and banking card activity became important means of monitoring the state of the economy and the impact of containment measures (OECD, 2021[8]). In November 2020, for example, the city of Yokohama, Japan, organised a baseball match to test whether crowds could gather safely in preparation for the Olympics and Paralympics in 2021. Monitoring devices in the stadium and a smartphone application were used to inform spectators about congestion in different parts of the stadium. During the pandemic, Tokyo, Japan, accelerated its efforts towards its digital transformation with the promotion of online learning, telemedicine, telecommuting and the digitalisation of public services. The city introduced a smart school project to enable all school children and students in Tokyo to study online (OECD, 2020[9]). India experienced an increase in digital payments across online grocery stores, small retail outlets and online pharmacies: contactless payments via quick-response (QR) codes, wallets or contactless cards surged as they provided ease, security and allowed users to maintain social distancing.2
The COVID-19 pandemic has triggered changes in the way of working in enterprises and government agencies. Teleworking has led managers to rethink how to organise their work, replacing face-to-face interactions by virtual interfaces. In OECD countries such as Australia, France and the United Kingdom, 47% of employees teleworked during lockdowns in 2020 while, in Japan, a country without a nationwide lockdown, the rate increased from 10% to 28% between December 2019 and May 2020 (OECD, 2021[10]). In Latin America, for example, 34% of the population was able to telework during the pandemic (Jung and Katz, 2022[5]). Online payments began to increase in countries where cash transactions dominated. In Japan, online payments increased by 11% in 2020 and by almost 20% in major cities compared to 2019, which was a remarkable change in a society where cash dominated consumer purchases (OECD, 2021[8]). The percentage of new online consumers experienced a significant increase in countries like Chile (94%), Colombia (113%) and Mexico (79%) during the pandemic in 2020 compared to the previous 2 years and electronic trade grew from 13% in 2017 to 23% in 2020 on average in Latin America (Jung and Katz, 2022[5]). COVID-19 also uncovered some weaknesses in digital transformation. For example, traditional work practices (i.e. physical presence in the workplace) and poor telecommunication infrastructure in some homes hindered the possibility of teleworking. In Japan, according to research, the productivity of employees working remotely during the pandemic decreased by between 30% and 40% compared to their productivity levels in the office (Morikawa, 2021[11]).
Smart cities as a vision to address urban challenges by utilising data
The term “smart city” and other related concepts, such as “smart communities” and “ubiquitous cities”, evoke societies that leverage technologies, mostly digital ones, to boost citizens’ well-being and deliver more efficient and sustainable public services. However, the term “smart city” is subject to different interpretations and debates across OECD countries (OECD, 2020[12]). In Japan, a smart city usually refers to the use of (digital) technology to provide services and solve city problems.3 In Canada, authorities use the term “smarter communities” to refer to being innovative and using data and connected technology to strengthen communities and create opportunities for growth.4 For Korea, a smart city is a sustainable city where several city services are provided based on city infrastructure constructed by converging and integrating construction, information and communication technologies to enhance competitiveness and liveability.5 For Colombia, a city or territory is smart when it orients its actions towards sustainability and inclusion and connects and adapts to the challenges and expectations of the people, generates an environment of collaboration, innovation and constant communication, and uses technologies as tools that leverage social, economic and environmental transformation” (Government of Colombia, 2019[13]). For the city of Portland, United States, a smart city refers to “… the use of existing and innovative technologies, data collection and data management tools to enhance community engagement, improve delivery of public services, and address City goals around equity, mobility, affordability, sustainability, community health and safety, workforce development, and resiliency” (City of Portland, 2018[14]). In Japan, while the Tokyo Metropolitan Government defines smart cities as “… a vibrant city that keeps growing, a city open to the world, a city leading the world in environmental policies, and a global financial and economic center” (2016, p. 21[15]), the Cabinet Office characterises smart city is “[a] holistically optimized, sustainable city or district where management (planning, building-up, management/operations, etc) is executed leveraging such advanced technologies as ICT for the resolution of various issues of the city” (Government of Japan, 2020, p. 3[16]).
Although definitions of smart cities vary from country to country and even across international organisations, the use of digital innovation to improve competitiveness and efficiency in urban services is a common element. In smart cities, local governments and/or private sector actors develop a system of technological solutions (e.g. smart technologies such as sensors and cameras) to advance city governance and development goals. Smart technologies are used to collect and analyse data to meet cities’ particular needs, such as traffic congestion, public security, healthcare for the elderly, public transport provision, city planning and innovation (Johnson et al., 2022[17]). The OECD defines smart cities as “initiatives or approaches that effectively leverage digitalisation to boost citizen well-being and deliver more efficient, sustainable and inclusive urban services and environments as part of a collaborative, multi-stakeholder process” (2020, p. 8[12]).
However, what makes a city “smart” remains a pending question across the literature. Research suggests that a city becomes smart by using smart technologies in transport infrastructure, water systems, power supplies and public services (Thomas, 2019[18]) and this entails the interaction of technological components with political and institutional components (Fietkiewicz and Stock, 2015[19]). It also suggests that “[t]he smartness of a city is […] not about technology as such, but rather about how technology is used, as part of a wider approach, to help the city function effectively, both in its individual systems, and as a whole” (BSI, 2015, p. 6[20]). Smart cities not only provide better services and make better use of urban resources, they also guide how people govern and make decisions to ensure sustainable urban development through the use of digital technologies and urban data open to the public (Paskaleva et al., 2017[21]). For the OECD and the International Transport Forum (ITF), the term “smart” is often linked to notions of “how” (which are technological in nature and guided by industry actors) and to those of “what for” (which are the domain of public authorities and the mandates given to them by people) (ITF, 2020[22]).
Kitchin (2016[23]) has identified at least three broad concepts of smart cities that are not mutually exclusive. The first refers to smart cities as digitally instrumenting cities where networked, digitally enabled devices (e.g. digital closed-circuit television [CCTV], sensor networks, smart meters) embedded into the city’s fabric change the configuration and management of infrastructure and services. The second refers to smart cities as an initiative aimed at improving urban policy, development and governance by using information and communication technology (ICT) to boost and improve innovation, sustainability, creativity, human capital and management. Under this conception, a smart city publishes open data and fosters an open data economy, encourages citizens’ participation in planning, enables urban test-bedding and leverages digital technologies and data to create synergies and break down departmental silos, among other things. The third concept refers to smart cities as those that use digital technologies to promote a citizen-centric urban model of urban development and management, reducing inequality while enhancing transparency, accountability and civic engagement.6
Ultimately, a smart city aims at solving urban and regional problems based on a human-oriented approach (Ishida, 2021[24]) through the use of information technology (IT) and data. Data are central to achieving the objectives of smart cities. Still, the critical issue is to ensure that data are of the right quality and volume and obtained at the right time and in full security to tackle socio-economic local and regional issues (Figure 1.1). Some OECD countries, such as Australia, Canada, Japan, Korea and the Netherlands, commonly refer to “data-driven” cities, projects and strategies. Data should not be the driver of decision making and policy formulation but the enabler of achieving a city’s key priorities.7 Technology and data are a means to an end rather than an end in itself.
For the OECD (2019[25]), a “data-driven public sector”:
Recognises data as a key strategic asset, defines its value and measures its impact.
Removes barriers to managing, sharing and reusing data.
Applies data to transform the design, delivery and monitoring of public policies and services.
Values efforts to publish data openly and the use of data between and within public sector organisations.
Understands the data rights of citizens in terms of ethical behaviours, transparency of usage, protection of privacy and security of data.
However, the London Office of Technology and Information (LOTI) in the United Kingdom suggests that cities should strive to be “data-enabled”, rather than data-driven, which suggests that smart city initiatives and data use should focus more on outcomes.
Figure 1.1. How a city uses data to tackle social issues
Source: PwC (2021[26]), Smart Cities in 2050: Rebuilding the Future of Japanese Cities, https://www.pwc.com/jp/en/knowledge/thoughtleadership/assets/pdf/smart-city2050-en.pdf.
The value of smart city data depends on their application
Data and their application are key elements of smart cities. The New Leipzig Charter, a document that calls for fostering the common good using the transformative power of cities in Europe, states that cities should improve decision making and digital public services to shape digital transformation. To this end, “[d]ata should be used for the common good, with ethical and socially responsible access, use, sharing and management … [while] data usage should be carefully weighed against privacy issues” (German Government, 2020, p. 9[27]). Smart cities are undergoing an evolution process to focus on the needs of people living in urban areas through the application of the IoT. IoT is understood “… as a connected network of heterogeneous components that are sensing, collecting, transmitting, and analyzing data for intelligent systems and services” (Sarker, 2022, p. 1[28]). The total IoT market worldwide was estimated to be worth around USD 300 billion in 2021 and is forecasted to rise to more than USD 650 billion by 2026.8 In the United States alone, cities are expected to invest USD 41 trillion over the next 2 decades to upgrade and benefit from digital technologies.9 The IoT market revenue in China was projected to reach USD 4 517 million in 2022.10 In Japan, the value of IoT technology for Japanese factories was estimated at JPY 636.2 billion (approximately USD 4.4 billion) in fiscal year (FY) 2021 and forecasts project it to reach JPY 1 trillion in FY 2027 due to increasing government investment in smart public infrastructures such as smart parks and the launch of a wide range of IoT sensors and solutions.11 Moreover, the growing adoption of IoT in various industries (e.g. agriculture, healthcare, manufacturing, etc.) is also propelling the growth of the Japanese IoT market.12
Managing and sharing data responsibly is critical to ensuring the benefits of smart cities. IoT provides critical building components for smart cities, such as data acquisition, data analytics and intelligent decision making. Connected smart devices in the IoT network can share and access authorised information to make informed decisions in the public and private sectors. From an operational perspective, there is a need to maintain data integrity to ensure the smooth delivery of public services. From a public policy perspective, data can help monitor compliance with and the enforcement of rules related to urban development, well‑being and environmental sustainability. These data can also be useful for planning purposes, improving equity, promoting economic growth and contributing to people’s welfare.
Digital technologies (e.g. IoT, big data analytics, artificial intelligence [AI], three-dimensional [3D] printing, machine learning, advanced energy storage and video technology) play a key role in service provision through the data collected. A smart city typically uses ICT to collect and share data, increase the efficiency of city operations, improve the quality of public services and raise quality of life standards. As Box 1.1 suggests, the use of ICT implies generating, collecting and using data. Public organisations, private companies and individuals require reliable, updated and easily accessible data for their decision making and innovation. However, citizens cannot use or analyse data by themselves; they need intermediaries and data providers to help them use and interpret data. City data collected from diverse sources, such as sensors, Internet-connected devices, or others, are used to obtain insights and hidden correlations to provide better services to citizens and improve decision-making processes (Sarker, 2022[28]).
Box 1.1. Defining “smart city data”
Smart city data may be defined as “data collected by sensors and other technologies deployed in a smart city project, as well as the insights derived from this data” (Chyi and Panfil, 2020, p. 2[29]). It can be classified into technologies for collection and technologies for use. The former involve software applications that collect data through sensors or recorders and process, store or send data using the Internet. The latter consist of software programmes/applications that use data as input and perform a certain function, such as classification and detection, by manipulating the data and performing calculations by applying present algorithms to the data. These software programmes/applications are likely to be installed in hardware devices that support Internet connection, such as IoT devices and more interactive smart devices, such as smartphones, tablets or computers.
Smart city data can be generated in either a passive or an active way. Data generated passively means that data are generated without intention, awareness or consent through sensors and cameras. For example, massive, diverse and fine-grained data on the size and patterns of mobility are collected through IoT devices installed on the roads and public transportation, while consumers are barely aware of being part of such data and do not give any explicit consent to being accounted for in this manner. Actively generated data refer to cases where the involved people actively opted to provide or generate data themselves. The public or private sectors can collect smart city data and it is becoming increasingly common to establish public-private partnerships (PPPs) for data governance.
Source: Chyi, N. and Y. Panfil (2020[29]), “A commons approach to Smart City data governance: How Elinor Ostrom can make cities smarter”, https://www.newamerica.org/future-land-housing/reports/can-elinor-ostrom-make-cities-smarter/; OECD (2021[30]), Innovation and Data Use in Cities: A Road to Increased Well-being, https://dx.doi.org/10.1787/9f53286f-en.
National smart city frameworks emphasise the importance of accessing, producing and using timely and accurate data for decision making and public service (ITF, 2020[22]). For example, the national smart city frameworks of Germany, Turkey and the United Kingdom highlight the importance of ensuring high-quality geospatial data. Their aim is generally to enable interactive urban and landscaping planning, 3D modelling and digital land use planning. These data also enable smart mobility goals such as providing optimal routes, effective planning and land registration.
However, public and private sector stakeholders are generating more data than they are capable of handling and storing. According to estimates, every day, digital technologies generate more than 2.5 quintillion bytes of data; more than 50% of those come from IoT devices (Marr, 2018[31]) and less than 1% of IoT data has been fully utilised (McKinsey Global Institute, 2015[32]; WEF, 2022[33]). Moreover, only 2% of the data generated in 2020 was saved and retained into 2021, while the rest was either temporary (created or replicated for the purpose of consumption) or temporarily cached and then overwritten with newer data (Businesswire, 2021[34]).13 To unlock the power of data generated as part of smart city projects, cities need governance protocols and regulatory frameworks that allow them to manage growing volumes of complex data while building trust between data providers, platform operators and data users (e.g. public and private organisations, citizens) and facilitating data sharing (WEF, 2022[33]).
The relevance of data governance for smart cities
Smart cities dovetail with the data revolution. Creating, processing, analysing and sharing vast amounts of data are central to smart cities. Digital technologies, which are intrinsic to smart cities, encompass digital devices, systems and resources that help create, store and manage data. These technologies are making cities’ systems and services responsive to and reactive upon (real-time) data. Smart cities are thus part of the data revolution (Kitchin, 2016[23]; 2014[35]). Five features of the data revolution describe what smart cities are also experiencing: a wide-scale production of big data; the scaling of traditional small data into data infrastructures (digital repositories); the creation of linked data; the publishing of open data; and the development of new data analytics.
Several cities such as Dublin (Ireland), Rio de Janeiro (Brazil) (Box 1.2) and Tokyo (Japan) have adopted an urban operating system (or city OS) and dashboards to link together multiple smart city technologies to better co-ordinate city systems and link as much data together as possible to draw a profile of their city. Urban OS and dashboards exemplify cities’ efforts to link different technologies and data to create new data and inform decision making.
Box 1.2. Rio de Janeiro Urban Operations Centre
In 2010, the city of Rio de Janeiro in Brazil opened the Centro de Operações Rio (COR). This purpose-built operations centre integrates all stages of the crisis management process, with immediate responses in emergency situations. It was built to create a command and control hub for managing city operations in the lead-up to and during three major sporting events: the Confederations Cup, the World Cup, and the 2016 Olympics. Its mission is to monitor the city and integrate actions to reduce the impact of emergencies 24 hours a day.
COR integrates data from 30 public agencies and concessionaires whose services directly affect the routine of the city of Rio de Janeiro. Among them are the Rio Alert system, the Integrated Centre for Urban Mobility (CIMU), CET-Rio, RioLuz, Comlurb, Geo-Rio (sirens), the Municipal Guard, the Departments of Social Assistance, Conservation, Health and Education, Civil Defense, Águas do Rio, among others. It employs 500 professionals that control 1 500 cameras around the city.
In 2023, COR will have a new datacentre capable of processing a high volume of data, such as the amount of rain, photos and videos of emergencies, and information captured by the new georeferenced sensors. In the same facility, the streaming of the new cameras will be processed, all connected by fibre optics. COR analysts, aided by various data analytics software, process, visualise, analyse and monitor live service data, alongside data aggregated over time and large volumes of public administration data that are released on a more periodic basis. The data are used for real-time decision making and problem solving. COR can use the data it processes to investigate particular aspects of city life and build predictive models with respect to everyday city development.
Source: COR (n.d.[36]), Centro de Operações Rio, https://cor.rio/ (accessed on 3 February 2023); Kitchin, R. (2016[23]), Getting Smarter about Smart Cities: Improving Data Privacy and Data Security, https://www.researchgate.net/publication/293755608_Getting_smarter_about_smart_cities_Improving_data_privacy_and_data_security.
There are no smart cities without comprehensive and agile data governance arrangements
Data governance is a key element in the development of smart cities. There are several definitions of data governance, for example as “…the process of managing the availability, usability, integrity, and security of the data … based on internal data standards and policies that also control data usage” (Stedman and Vaughan, n.d.[37]). For the OECD, data governance refers to “diverse arrangements, including technical, policy, regulatory and institutional provisions, that affect data and their creation, collection, storage, use, protection, access, sharing and deletion, including across policy domains and organisational and national borders” (2022, p. 13[38]). Box 1.3 provides an overview of the OECD data governance model. Rules regarding the collection of, access to and control over the use of data have implications on which goals are pursued in a digitalised urban environment. The complexity and large number of actors and the need to reconcile competing economic, social and environmental interests and values call for a revision of data governance frameworks. National governments need to offer an enabling environment that provides cities with regulatory structures, instruments and institutions to balance private and public interests regarding data access and use.
Box 1.3. Advancing data governance in the public sector
The OECD has developed a model for data governance in the public sector to showcase the core elements needed to design and deploy data projects and initiatives. The model highlights the equal and strategic relevance and value of all organisational, policy and technical aspects for the success of data governance. It identifies a range of non-exclusive data governance elements and tools grouped around three core layers of data governance:
Strategic layer: Includes national data strategies and leadership roles, and considers data strategies as an element of good data governance. Data strategies enable accountability in relation to responsibilities and can help define leadership, expectations, roles and goals. This layer also highlights how the formulation of data policies and/or strategies can benefit from open and participatory processes integrating the input of actors from within and outside the public sector towards greater policy ownership.
Tactical layer: Enables the coherent implementation and steering of data-driven policies, strategies and/or initiatives. Public sector skills and competencies, job profiles, communication, co‑ordination and collaboration are used as instruments to improve the capacity of the public sector to extract value from data assets. The layer highlights the value of formal and informal institutional networks and communities of practice as levers of public sector maturity and collective knowledge. Data-related legislation and regulations are considered instruments that help countries define, drive and ensure compliance with the rules and policies guiding data management, including data openness, protection and sharing.
Delivery layer: Allows for the day-to-day implementation (or deployment) of organisational, sectoral, national or cross-border data strategies. It touches on different technical and policy aspects of the data value cycle across its different stages (from data production, openness and reuse), the role and interaction of different actors in each stage (e.g. as data providers) and the interconnection of data flows across stages. Each stage is interconnected but has specific policy implications in relation to the expected outcomes.
Figure 1.2. The OECD model for data governance in the public sector
Source: OECD (2019[25]), The Path to Becoming a Data-Driven Public Sector, https://doi.org/10.1787/059814a7-en.
Smart cities are a blend of institutions, processes, urban actors and technology. Thus, engaging in collaborative and co-ordinated processes is necessary to allow different stakeholders to generate and use the data necessary for developing smart solutions. Governance has a critical role in making cities smarter and sustainable. Inclusive stakeholder relations, the ability to co-operate and the structure of the collaborations are critical factors of governance that condition the success of smart city initiatives (Paskaleva et al., 2017[21]).
Data governance helps city governments make better and faster decisions with more certainty. Indeed, smart cities and the use of data represent or create opportunities for stakeholders to engage in decision-making processes in the pursuit of a better urban life. For this reason, many OECD countries (e.g. Canada, France, Japan, the United States) are using a citizen-centred approach to smart city initiatives in which citizens and different stakeholders (e.g. private sector companies, academics) are seen as key stakeholders for the design and implementation of smart city initiatives/projects. In the United States, for example, the U.S. Department of Transportation organises a smart city challenge through which cities develop proposals on how to overcome mobility challenges using new digital technologies. The department, residents and private sector are all closely involved in work on project proposals in order to put their smart city vision into action. The winning city receives financial support from the department to support the implementation of its mobility project.14
In this context, what makes the governance of smart cities work is the cities’ governance capacity, in other words access to highly skilled staff in the public and private sectors, the ability of the public sector to engage in long-term projects and the ability to fund and finance projects beyond the pilot phase. The governance of smart cities also requires strengthening their capacity to develop sustainable relationships among the different stakeholders and enhancing their organisational capacity to ensure co-ordination and communication.
A particular issue for the governance of smart cities is governing the exponential growth and access to greater data volumes. Smart city projects produce a large amount of data due to the use of IoT technology and other devices. Data governance can assist cities in collecting data in a cleaned, standardised and accurate manner to facilitate use and sharing. Energy consumption, mobility, health, environment, people’s consumption or leisure are examples of areas where data are being collected and much of that data is open and easily accessible to citizens. The development of IoT, AI and the deployment of fifth-generation technology standard for broadband cellular networks (5G) technology have intensified and made it easier to generate data. Essential data for city life, such as data on demographics, housing, traffic, pollution, crime and health, are being collected and managed by local public authorities. Data come from different sources and domains, making data governance a key challenge for smart cities. A dilemma national and local policy makers face is what data are necessary and sufficient to make a smart city work.
Data governance for smart cities should be an inclusive and iterative process of data collection and management
In the development and implementation of smart city projects, many actors are engaged in collecting, analysing, managing and interpreting urban data. This means that data collection and management is a process of interaction among different stakeholders in which citizens may have the opportunity to participate. A central body in charge of the co-ordination of smart city projects and interaction among the different stakeholders may be set up. For example, in New York City, United States, the Mayor’s Office of the Chief Technology Officer is responsible for implementing the New York City Internet of Things Strategy. In London, United Kingdom, the local government set up a Smart London Board composed of academics, entrepreneurs and business leaders to implement and monitor the Smart London Plan.
Promoting intersectoral, inter-organisational and governmental-non-governmental collaboration is one of the most important success factors for smart city initiatives (Paskaleva et al., 2017[21]). Many smart city projects are a collective venture of different public and private organisations, each with different rationales, ambitions and perspectives. Large corporations partner with the government and academia for the implementation of smart city pilot projects. In fact, research has shown that overlooking the challenges to partnership governance compromises the scaling up of smart city projects, which may then fade out after the pilot stage and fail to generate scalable solutions for urban problems across the whole city (Van Winden and Van Den Buuse, 2017[39]). Therefore, cities need to integrate data governance approaches into their smart city frameworks based on solid stakeholders’ partnerships. Smart city project managers need to be aware that partners enter the projects for a variety of reasons, including testing new products, improving urban services, sharing and accessing data to enable innovative solutions and products, enhancing energy efficiency, etc. The case of the Energy Atlas in the city of Amsterdam in the Netherlands illustrates a case where a strong link between the pilot project team and the parent organisation and the explicit common interest and commitment move the project forward in a multi-stakeholder setting (Box 1.4).
Box 1.4. Amsterdam’s Energy Atlas
Amsterdam’s Energy Atlas project explores the use of urban data to improve energy management. The city government expects the project to stimulate the use of renewable energy, as citizens become more aware of their own energy usage and realise that there are gains to be made. Companies will be able to determine their own usage and that of others and find out where renewable sources of energy and the energy infrastructure are located.
The Energy Atlas is a platform type of smart city innovation in which key public and private players in the local energy system share their data and create an online interactive platform (the Energy Atlas) that reveals data on real energy, water and sewerage use at building-block level for the entire city. The Energy Atlas helps identify the geographic locations in the city with the highest potential for adopting new energy solutions.
Between January 2012 and August 2015, European funding from the Transform project supported the project initially. The Amsterdam city administration was the lead agency in the project, leading and managing the project from the outset and organising the process of partner engagement and data integration. Participating utilities and housing corporations in Amsterdam agreed to provide their data for free on the condition that the platform would be open and would not reveal energy use on the level of individual clients. This created a challenge for partners as they had to cluster information on clients in such a way as to keep anonymity. Despite these technical and legal challenges, partner organisations (e.g. Alliander, Gemeente Amsterdam, Liander, TNO, Vattenfall-Nuon, Waternet) decided to continue with the project as they realised the value and importance of sharing data.
The Energy Atlas gives up-to-date and real (rather than projected or estimated) data on a wide variety of energy consumption and production in the entire city. The atlas now operates without European cofinancing and the local partner management boards have committed to continuing to feed the platform with data and keeping it technically up to date.
Source: Van Winden, W. and D. Van Den Buuse (2017[39]), “Smart city pilot projects: Exploring the dimensions and conditions of scaling up”, https://doi.org/10.1080/10630732.2017.1348884; Open Data Soft (2017[40]), “How Amsterdam uses urban data to build a more sustainable city”, https://www.opendatasoft.com/en/blog/amsterdams-energy-atlas-using-urban-data-to-build-a-sustainable-city/; De Pater, M. (2016[41]), Energy Atlas, https://amsterdamsmartcity.com/updates/project/energy-atlas.
The cases of Amsterdam in the Netherlands, Copenhagen in Denmark and New Delhi, India, show that, through data governance, cities can tailor data to the specific needs of stakeholders in critical areas for the city’s management and citizen well-being. The cities can also realise their sustainable development goals in urban sectors.
Data governance in smart cities could lead to more efficiency and inclusion
Data are the raw material of smart city initiatives. Therefore, how cities govern data largely dictates how effective and innovative governments are in tackling urban challenges. To that end, national and subnational governments must find a balance between bringing more value to the data (i.e. analysing and using it for decision making) and securing or protecting personal data provided by citizens. Here, data governance means the core mechanism of smart city operations, that is decision making and innovation on how to use data to solve urban/regional problems.
Data governance is often employed to generate additional revenue for the city. Milton Keynes Council in the United Kingdom, for example, runs the MK Data Hub, which requires the private sector to pay a certain amount of money to use their data for commercial purposes.15 The data hub incorporates a vast amount of data from various sources, such as key infrastructure networks for energy and transportation, sensor networks for weather and environment, and social media.16 Therefore, the pricing structure depends both on the provider side (e.g. data accuracy, granularity, timeliness) and the user side (e.g. type of user and purposes). While selling (access to) data is the most straightforward way of monetisation, more complicated models are being adopted as well. For example, LinkNYC, a smart city project initiated by New York City to transform payphones around the city into smart kiosks called Links for Public Services, was funded by setting up a partnership with a private company called CityBridge.17 Services provided by LinkNYC include Wi-Fi, telephone calls, an emergency button, phone chargers, maps, etc.18 In exchange for the development, New York City granted CityBridge the rights to operate the kiosks as well as user data generated during the operation. Using the data and advertisements, both the city and the company were able to raise their own revenue continuously.
Data governance can also bring about significant intangible benefits. While many data governance projects aim to enhance the quality of life of all citizens, some are more dedicated to improving the lives of future generations, i.e. sustainability, or those of minorities, i.e. inclusion. Smart meters are a classic example of achieving sustainability through data governance. By collecting real-time data on energy usage and letting users monitor the status, smart meters induce savings and closer control of energy consumption. For example, the Japanese government has set the goal of installing 80 million smart meters by 2025 to improve energy efficiency. The Tokyo Electric Power Company (TEPCO) is deploying 27 million smart meters as part of a citywide energy management platform.19 In the United States, nearly 107 million smart meters were deployed as of 2020, covering 75% of households, and the number of smart meters deployed grew to 111 million in 2021.20
The collection and use of data with smart technologies are also geared more toward fostering inclusion and well-being. In Japan, the city of Takamatsu, for example, piloted a project to use wearable vital sensors and cardiac rate monitors for the elderly. In particular, the COVID-19 pandemic has increased the relevance of real-time data. The East Japan Railway Company (JR East), the largest train company in the Tokyo area, used real-time data to inform passengers about overcrowding in trains and stations to avoid contagion. In the United Kingdom, the Greater London Authority (GLA) created a high streets data service and partnership to provide organisations with constant access to the best data on local high streets and town centres at a low cost. The partnership helped the local government access private companies’ real‑time data during the pandemic to track which areas of the city were recovering faster.
Data governance has a key role in scaling up smart city projects
Many smart city projects die after the pilot stage. Poor collaboration among stakeholders, limited municipal organisational and technical capacity, failings in the articulation of public needs at a citywide scale, low levels of social acceptance of new technologies and technological uncertainty are some of the main governance factors that prevent scaling up smart city projects around the world (Bundgaard and Borrás, 2021[42]). The lack of scalability makes many smart city projects mere social experiments as they remain at the stage of piloting. For example, in Japan, only 23 smart city projects were rolled out into actual mainstream service delivery in 2020. A possible explanation is that 43% of local government revenue comes from central government transfers and those resources are mostly earmarked despite attempts to limit this practice (OECD/UCLG, 2019[43]).
Sustaining smart city pilot projects is becoming a challenge for many cities around the world. Different factors account for this trend, such as: the failure to secure the necessary budgetary resources to transfer smart city pilot projects into actual public service delivery; a lack of incentives for scaling up; and a lack of mechanisms and incentives included in pilot projects to maximise scaling up potential (Van Winden and Van Den Buuse, 2017[39]). In some cases, policy makers and private sector stakeholders are not aware that smart city projects will take time to produce the desired change and will most probably require the accumulation of different projects. For example, the OECD has already pointed out that most smart city projects in Japan are developed individually and are not interconnected, which may prevent their scaling up without a sharing knowledge mechanism (OECD, 2021[8]). However, through engagement with local communities and stakeholders, local smart initiatives can draw on the opportunities of urban data, (digital) technologies and networks to realise urban sustainable development goals. In other words, “…governance is in effect the landscape for understanding and driving processes and activities in data-sensitive issues related to sustainability in the smart city” (Paskaleva et al., 2017, p. 5[21]).
Another explanation is that stakeholders in smart city projects do not develop or prepare clear investment recovery models, which results in corporations seeing smart city projects as testing sites (PwC, 2021[26]). Pilot projects provide valuable information on how smart city initiatives may work but are not assessed regarding their possible pitfalls. A testing site cannot be considered a smart city as it does not spread the benefits of the project to the city as a whole. The lack of an investment recovery model makes it difficult for local governments to secure external financing due to the difficulty in making decisions regarding large‑scale investments and revenue projections. The case of the Cargohopper in Amsterdam and Utrecht in the Netherlands exemplifies a case of replication of a smart city solution developed to address the particular needs of a city and then replicated in another (Box 1.5). Explicit knowledge needs to be transferred efficiently to new circumstances in order to facilitate replication. Data must be collected from different stakeholders processed within the IT system to scale up. To do so, trust needs to be established and an incentive to share data defined. Since several logistic providers interact with each other, the system must achieve data interoperability and thus must be designed to be capable of handling data from different sources. The case of Cargohopper also highlights that, to upscale a smart city project, there needs to be a minimum threshold of clients in a city using the service (or product) to develop a viable business model. Co-ordination of data sharing is essential to scale up smart city projects as it allows different stakeholders to take an active part in the project and benefit from the services or products.
Box 1.5. Cargohopper, environmentally friendly urban goods transport in Amsterdam
The Cargohopper project of Amsterdam is an inner-city delivery project using electric transportation. It was first piloted in the city of Utrecht and was then replicated in Amsterdam in collaboration with the local administration. The logistics company Transmission, with the support of various institutions across the Netherlands, was the initiator of the project, a response to the growing number of Dutch cities introducing bans of large diesel trucks in inner-city areas labelled “environmental zones” to limit pollution and congestion. The project consists of an electric freight vehicle and a smart distribution system. More than an appealing road train with separate carriages, Cargohopper is a complete logistics system.
In a distribution centre (located at a facility just outside the zone), shipments are processed, bundled and loaded onto the electric freight vehicle. These shipments are sorted by address in separate carriages, allowing efficient delivery to businesses based on the proximity of delivery addresses in the same area. Only through the establishment of data interoperability can the databases be harmonised and stakeholder collaboration become more effective. The local government allowed Cargohopper to operate and delivery goods within the city centre environmental zone and partially subsidised the development of the first electric vehicle.
Source: Van Winden, W. and D. Van Den Buuse (2017[39]), “Smart city pilot projects: Exploring the dimensions and conditions of scaling up”, https://doi.org/10.1080/10630732.2017.1348884; Lechner (n.d.[44]), Cargohopper (Environmentally Friendly Urban Goods Transport), http://okosvaros.lechnerkozpont.hu/en/node/232.
Knowledge transfer mechanisms among stakeholders in a smart city project are critical for scaling up. Replicating a successful smart city solution requires the know-what and know-how (tacit or explicit) to be transferred from place to place but also needs contextualisation of knowledge (Van Winden and Van Den Buuse, 2017[39]). Large companies often are able (and have financial incentives) to organise effective knowledge transfer mechanisms. But this option is not available to start-ups or small and medium-sized enterprises (SMEs) as they may not have the same network of partners as large companies. Thus, it is important that smart city projects include mechanisms for knowledge sharing and dissemination, and that the IT system is capable of managing an increasing number of interactions in terms of data.
There are different approaches to data governance for institutional needs
Research has identified at least five approaches to data governance: centralised, replicated, federated, collaborative and decentralised (González Morales and Orrell, n.d.[45]). They represent a continuum on which different models can be identified for different circumstances and needs (Figure 1.3). For example, a more centralised model of data governance could be used when a central office, such as the statistics office, oversees data collection, standard-setting, security and storage, while a more decentralised model may be used in cases when data control is distributed among several organisations.
There are pros and cons to the use of any of the extremes in the continuum. A decentralised model does not work when common standards and co-ordination are needed to facilitate data sharing, whereas a centralised model may create problems in an environment that needs to foster creativity, innovation and experimentation. A middle ground could be found in the replicated, federated or collaborative models but all of them require clear institutional rules and mechanisms for communication and co-ordination. A federated model, for example, allows multiple organisations to be part of a co-ordinated network of hubs, reducing the complexity of data exchange management, but allows for multiple representations of information based on the different needs and priorities of participating organisations. A collaborative model to data governance can be an effective way to engender a more multi-stakeholder, open and ecosystem approach to tackling interoperability problems (see Chapter 2). It allows greater adaptability and flexibility than other models.
Figure 1.3. A continuum of models of data governance
Source: Based on González Morales, L. and T. Orrell (n.d.[45]), Data Interoperability: A Practitioner’s Guide to Joining Up Data in the Development Sector, https://www.data4sdgs.org/sites/default/files/services_files/Interoperability%20-%20A%20practitioner%E2%80%99s%20guide%20to%20joining-up%20data%20in%20the%20development%20sector.pdf.
How do countries promote a national enabling framework for smart cities and data governance?
There is no one-size-fits-all guideline or mechanism to promote data-enabled smart cities. However, a review of international experiences offers indications of how countries and cities could build a sound framework for smart city projects that enables more efficient and effective use of data.
A vision and a policy framework for smart cities and data
Setting a clear vision is the first step towards a smart city. The experience of many smart cities around the world shows the significance of a clear vision identifying current challenges and the ideal future that cities want to achieve. Indeed, challenges and visions depend on each city’s particular history and priorities and no single smart city model can fit in all contexts. By clearly defining issues and goals, cities can manage to lead innovations and new technologies to face their challenges. The vision can be set both at the national and subnational levels. For example, in 2016, the Japanese government launched Society 5.0, a vision for the future society Japan should aspire to. This involves “[a] human-centered society that balances economic advancement with the resolution of social problems by a system that highly integrates cyberspace and physical space” (Japanese Cabinet Office, n.d.[46]). The aim is to achieve a forward-looking society that breaks down the existing sense of stagnation through social reform (innovation). This approach highlights the organisational changes to leverage what is already happening at the micro level, such as smart cities, smart mobility and smart medicine, and roll them out across the economy and country. Cities also set their vision depicting their own identity. For example, the vision of the cities of Copenhagen, Denmark, and Helsinki, Finland, (Box 1.6) represent a “mission statement” or “development model” along different indicators or topics. The vision is generally based on the goals that a city or community has derived from current challenges and opportunities that it wants to grasp in the foreseeable future. The lesson from these experiences is that governments and citizens should debate the future of the city and what they want the city to be before engaging in smart city projects.
Box 1.6. Smart city vision – Copenhagen and Helsinki
Copenhagen, Denmark, aims to become the world’s first carbon-neutral capital by 2025 and is implementing initiatives to rebuild the vision for the city in co-operation with the national government, as well as promoting smart city initiatives in different areas such as industry and tourism, disaster management and crime prevention, and public services. The city aims to be a clean and healthy city, a carbon-neutral capital, a green and blue capital and the world’s best city for cyclists.
Helsinki, Finland, aims to become the most functional city in the world by turning the whole city into a testing site to support the creation of innovative services and products by applying digital technology as well as providing services under the concept of City as a Service.
Source: Copenhagen Connecting (n.d.[47]), Copenhagen Smart City: The Challenge, https://www.almanac.in-jet.eu/downloads/M2M_Workshop_Presentations/Session%204/Mia_Copenhagen_smart_city_2015.pdf; Helsinki Partners (2020[48]), “A smart city saves time and produces better services”, https://www.myhelsinki.fi/en/business-and-invest/invest/a-smart-city-saves-time-and-produces-better-services.
A national policy framework may guide smart city strategies for development and facilitate the adoption of smart city initiatives at the local level. This could be an explicit smart city policy or an implicit objective immersed in broader policy objectives. In countries with explicit smart cities, a smart city national framework (SCNF) in place would normally include a vision for the cities and a plan to maximise their potential through the use of technologies.
The SCNF may also incorporate a diagnosis of how the national government understands national and local challenges, the division of responsibilities across all levels of government contributing to the development of cities and how government action could promote investment and growth. The aim of an SCNF is to ensure co-ordinated action and approaches in public investment at the city level across levels of government. Even when there is no established national smart cities framework, the national government can provide resources or other kinds of support to regional and local governments and their stakeholders (ITF, 2020[22]).
Some countries do not have an explicit national policy framework for smart cities. In this case, countries need to leverage complementarities and co-ordination with other national policies. Building synergies and avoiding a duplication of efforts to ensure better efficiency and effectiveness is key in the implementation of smart city strategies, as smart city goals cut across different domains.
The existence of an SCNF may help empower and guide local governments in the identification of their main assets, needs and opportunities. The SCNF is not a way for national governments to prescribe policy or select needs and courses of action on behalf of local governments: it simply helps them to do so. In fact, subnational levels regularly inform national policy of government and, thus, the SCNF should reflect the diverse challenges that cities face (ITF, 2020[22]). In Italy, for example, the Strategy for Digital Growth was developed based on the capability of municipalities to identify social and economic challenges and smart city solutions to meet people’s needs.
The SCNF may also include a comprehensive set of tools for cities to develop their smart city strategies, including principles, standards and guidelines. For example, Japan’s basic concept of smart city initiatives is based on three “basic philosophies” and five “basic principles” (Box 1.7). Both highlight the importance of data in achieving the objectives of a smart city initiative. A critical element is the utilisation of data among cities, which requires governance frameworks to ensure the interoperability of data-sharing platforms for other cities to be able to access and use openly available data. Interoperability may be understood as the ability of organisations to interact in view of mutual goals, sharing information and knowledge through the exchange of data via their ICT systems (see Chapter 2). The development of smart cities in Japan depends on the co-ordination of strategy, a reference architecture, guidebooks, the development of standards and PPP platforms (Figure 1.4).
Box 1.7. Japan’s basic concept of smart city initiatives
Three basic philosophies
1. Being resident (user)-centric – Improve well-being, take the standpoint of residents and respect their independent activities.
2. Being vision-challenged focused – Attach importance to solving challenges and realising visions, going beyond the sole use of technology.
3. Attaching importance to collaboration among sectors/cities – Attach relevance to cross-sectoral data linkage and cross-regional collaboration to address compound or cross-regional challenges.
Five basic principles
1. Ensuring fairness and inclusiveness – To allow all residents to enjoy services equally and all entities to participate.
2. Ensuring privacy protection – To ensure the protection of residents’ privacy in utilising their personal data.
3. Ensuring operational and financial sustainability - To realise a sustainable smart city that takes root in the community.
4. Ensuring security and resiliency – To protect privacy and prepare for emergencies, including natural disasters.
5. Ensuring interoperability, openness and transparency – To ensure the interoperability of the data platform, an open data distribution environment and transparency of the decision-making process.
Figure 1.4. Elements underpinning smart city development in Japan
Source (figure): Hiramoto, K. (2022[49]), “Smart cities in Japan”, PowerPoint presentation given to the OECD team, Tokyo.
Source (box): Japanese Cabinet Office (2022[50]), “Japan’s Smart Cities”, Presentation to the OECD, Secretariat of Science, Technology and Innovation Policy.
Where it exists, an SCNF introduces an articulated public agenda for smart cities in a given country and provides a framework to index smart city initiatives. For example, in 2020, the Brazilian federal government adopted the Brazilian Charter for Smart Cities (Carta Brasileira para Cidades Inteligentes), the country’s SCNF. Its main purpose is to support the promotion of sustainable urban development standards taking into account the Brazilian context of digital transformation in cities. For this, it seeks to integrate the urban development and digital transformation agendas under environmental, urban, social, cultural, economic, financial and digital sustainability perspectives. An innovation of the charter is that it introduces a definition of a smart city that considers the reality, diversity and complexity of the country’s cities (Box 1.8).
Box 1.8. Brazil’s Charter for Smart Cities
The Brazilian Charter for Smart Cities is a democratic political document that expresses a public agenda for the digital transformation of cities. It defines Brazilian smart cities as “[c]ommitted to sustainable urban development and digital transformation, in their economic, environmental, and sociocultural aspects that act in a planned, innovative, inclusive, and networked manner, promote digital literacy, governance, and collaborative management and use technologies to solve real problems, create opportunities, offer services efficiently, reduce inequalities, increase resilience and improve the quality of life of all people, ensuring the safe and responsible use of data and information and communication technologies” (Government of Brazil, 2021, p. 8[51]).
The charter constitutes a concept that guides, informs and supports subnational governments in the design and implementation of smart city projects and programmes. It is based on five guiding principles and six guiding directives.
Table 1.1. Guiding principles and directives of Brazil’s Charter for Smart Cities
The principles and directives structure 8 strategic goals implemented through 163 recommendations for action directed to key audience segments:
1. Integrate transformation into sustainable urban development policies, programmes and actions, respecting diversities and considering the inequalities present in Brazilian cities.
2. Provide equitable quality Internet access for all.
3. Establish data and technology governance systems with transparency, security and privacy.
4. Adopt innovative and inclusive models of urban governance and strengthen the role of public authorities as managers of the impact of digital transformation in cities.
5. Foster local economic development in the context of digital transformation.
6. Stimulate sustainable urban development financing models and instruments in the context of digital transformation.
7. Foster a massive and innovative movement in public education and communication for greater engagement of society in the process of digital transformation and sustainable urban development.
8. Build up means to understand and evaluate, continuously and systematically, the impacts of digital transformation in cities.
Source: Government of Brazil (2021[51]), The Brazilian Charter for Smart Cities, https://www.gov.br/mdr/pt-br/assuntos/desenvolvimento-urbano/carta-brasileira-para-cidades-inteligentes/The_Brazilian_Charter_for_SmartCities_Short_VersionFinal.pdf.
In Japan, the Smart City Reference Architecture (SCRA) guides the development of smart cities under a common structure (see Annex 1.A and Figure 1.5). This is to ensure a common framework for the development of smart cities, share experiences, provide guidance to areas with no experience and ensure data compatibility among systems to facilitate data sharing (Government of Japan, 2020[16]). The SCRA intends to provide a common ground for all of the different smart city initiatives across the country, facilitating interoperability.21 This is of critical importance as private sector organisations may be reluctant to invest in smart city projects where there is restricted technology integration. Differences in technical standards among different local governments could prevent an expansive scale, that is the development of more smart city projects across the country.
All public and private stakeholders involved in the development and implementation of smart city initiatives in the country are encouraged to keep the four principles in consideration while working on their smart city projects. The SCRA in Japan was developed through the Cross-ministerial Strategic Innovation Promotion Program (SIP). The use of the SCRA is expected to prevent smart city initiatives from becoming standalone efforts, making it easier to enable the repurposing of outcomes and the interoperability between cities and between domains.
Figure 1.5. Foundational components of Japan’s SCRA
Source: Government of Japan (2020[16]), Smart City Reference Architecture White Paper, https://www8.cao.go.jp/cstp/stmain/a-whitepaper1_200331_en.pdf.
One of the expected benefits of using a common architecture for the development of smart city initiatives in Japan is what is called a “cross-sectional data federation”. By federating (or centralising) data from individual services for citizens, Japanese authorities expect to develop a one-stop service for citizens and private sector stakeholders. Cross-domain federation of data would facilitate linking and analysing the data of other cities to understand the characteristics of one’s own community and lead to the creation of unique local businesses. Inter-domain federation of data would enable data use across different domains, making it possible to, for example, advance disaster prevention measures by combining government hazard maps, road traffic records in private sectors, satellite images, meteorological data, etc.
Cities establish specific strategies as a roadmap for becoming a smart city. Following national guidance, local governments tend to adopt a specific smart city reference framework that describes the landscape of IoT usage across the city and provides a long-term vision of the future of the city. A local strategy normally includes the governing principles that will guide the formation of the smart city and that must be observed by all projects implemented under this framework. The principles structure the city’s approach to IoT usage and act as a guidepost for the analysis, recommendations and actions set in the strategy. The strategy should be based on a reflection of the city’s challenges and opportunities and how the usage of (digital) technologies can help to meet the city’s needs and its vision. For example:
In France, the city of Paris developed a strategy entitled Smart and Sustainable – Looking ahead to 2020 and Beyond that presents the major opportunities and challenges of becoming a smart city but also the main objectives, projects and tangible actions (Mairie de Paris, 2020[3]). The strategy shows the city’s main assets, the progress made so far and the action to transform Paris into an open, connected and sustainable city.
In the United States, New York City developed the New York City Internet of Things Strategy that describes the efforts the city has made to increase local governance and co-ordination as well as the steps the city needs to follow to make the most of the IoT technologies to increase levels of well-being (Box 1.9).
Box 1.9. New York City Internet of Things Strategy
In March 2021, New York City, United States, published its Internet of Things Strategy to establish a set of critical near-term actions toward creating a healthy, cross-sector IoT ecosystem in the city – one that is productive, responsible and fair. The strategy is built around six key principles: governance and co-ordination; privacy and transparency; security and safety; fairness and equity; efficiency and sustainability; and openness and public engagement.
The strategy identifies a range of challenges and opportunities in fostering a healthy IoT ecosystem. For example, within city government, there is room for improvement in building the capacity to use and innovate with IoT, fostering collaboration among agencies, boosting partnership opportunities across sectors and strengthening governance and co‑ordination throughout the city. In the private and non‑profit sectors, the strategy has identified opportunities to support industry standards and best practices around IoT, co‑ordinate emerging workforce and IoT literacy needs, and support local economies and communities. The strategy suggests there is greater potential for engagement and empowerment of residents in their interactions with IoT across society as consumers, residents or workers.
To address these issues and meet the development gaps, the strategy outlines five broad goals for near-term city action:
Foster innovation by creating structures and programmes that support research, testing and experimentation with IoT technologies. Key actions include: the launch of a rapid IoT data collection programme and the development of a municipal testbed.
Promote data sharing and transparency around city IoT use by engaging residents in IoT initiatives and aggregating information and data from the city’s actions to make them available across agencies and for the public. Key actions include: the launch of a Smart City Catalog to share information publicly about city projects and request community’s feedback on the strategy.
Improve governance and co‑ordination of the city’s use of connected technologies through new policies and processes. Key actions include: the launch of a Smart City Collaborative for City agencies and a biannual IoT forum for city agencies; and a citywide IoT device inventory.
Derive value from cross-sector partnerships by supporting and pursuing new opportunities for collaboration. Key actions include: setting up an online channel calling for expressions of interest from academic, community and industry partners, subject to city procurement rules.
Engage with industry and advocate for communities by creating new channels for exchange and advocating for digital rights. Key actions include: conducting research to better understand the need for IoT skills among local employers.
Source: NYC Government (2021[52]), IoT Strategy - The New York City Internet of Things Strategy, https://www1.nyc.gov/assets/cto/downloads/iot-strategy/nyc_iot_strategy.pdf.
Private companies like Hitachi in Japan have developed their own vision of smart cities (Box 1.10). Hitachi is looking to build digital smart cities using data from people and cities. The company aims to ensure the secure exchange of data held by public and private institutions and link it with Japan’s My Number identification system. The way Hitachi envisages digital smart cities as part of the infrastructure of society involves establishing both urban management and an urban OS for the appropriate handling and use of personal information.
Box 1.10. Hitachi – Creating digital smart cities through data
Hitachi, a manufacturing company in automotive systems, construction machinery and defence systems, seeks to create digital smart cities to improve quality of life using digital technologies (IoT and AI) for the co-creation of people-centric services that add value. Its vision of a resilient digital smart city entails the use of digital technologies to create a people-centric society that integrates the real and cyber worlds and maintains a stable economy and way of life.
The higher complexity of urban infrastructure and its maintenance, along with the shortage of human resources with equipment maintenance skills, has led Hitachi to focus on supplying expertise in IT and operational technology (OT) (e.g. elevators and escalators, surveillance cameras and air conditioning systems) through global businesses in the form of Infrastructure as a Service (IaaS). IaaS serves as a platform for digital services that provide people with places where they can live and work in comfort while maintaining economic viability taking the environment into account.
To create digital smart cities, Hitachi collects, analyses and utilises the various forms of data held by cities to provide services for improving people’s quality of life and the services for urban management that underpin that way of life. The urban OS, developed by the national Cabinet Office, will be seminal in the creation and deployment of new services for overcoming societal challenges (e.g. ageing population). The OS facilitate the use of cross-industry data as it improves operational compatibility through system interconnectivity and the exchange of data held by government agencies and private sector businesses across different sectors and industries. Hitachi is testing smart city initiatives through co-creation with different stakeholders that include local and national governments, private sector businesses and academia.
Source: Nakano, H. et al. (2021[53]), “Hitachi digital smart cities featuring continuous value creation by people and digital technology”, https://www.hitachi.com/rev/archive/2021/r2021_01/01a01/index.html.
Institutional arrangements for smart cities
A central body co-ordinates the implementation of the SCNF
The adoption of an SCNF requires specific governance arrangements for its implementation. One of these arrangements is the designation of a central administrative body responsible for co-ordinating the implementation of the SCNF (Table 1.2). According to OECD work on digital government, setting up an organisation in charge at the centre signals the highest political support for the digital government agenda and provides the opportunity to mainstream digitalisation in the public sector modernisation strategy (OECD, 2021[54]). There is no rule about who is better positioned to lead the SCNF; this depends on the particular administrative arrangements of every country and the main focus of the strategy. For example, the Swiss Federal Office of Energy (SFOE) leads the Smart City Switzerland strategy because it focuses on areas of smart environment and intelligent mobility. In Canada, Infrastructure Canada is the lead body for smart cities due to the large focus on infrastructure investments to build cities, promote innovation and enhance quality of life. In Japan, the Digital Agency may be considered the lead body as the focus is on strengthening the digitalisation of the country.
Table 1.2. Examples of administrative bodies in charge of SCNFs
Source: Argentina: Argentinian Government (n.d.[55]) Servicios y País Digital, https://www.argentina.gob.ar/jefatura/innovacion-publica/servicios-y-pais-digital; Australia: Australian Government, (2016[56]), Smart Cities Plan, https://www.infrastructure.gov.au/sites/default/files/migrated/cities/smart-cities/plan/files/Smart_Cities_Plan.pdf; Brazil: Government of Brazil (n.d.[57]), Decreto nº 9.854, de 25 de Junho de 2019, http://www.planalto.gov.br/ccivil_03/_ato2019-2022/2019/decreto/D9854.htm; Colombia: Government of Brazil (n.d.[58]), Ciudades y Territorios Inteligentes, https://gobiernodigital.mintic.gov.co/portal/Iniciativas/Ciudades-y-Territorios-Inteligentes/; Germany: German Government (n.d.[59]), “Smart Cities: Urban development in the digital age”, https://www.bmi.bund.de/EN/topics/building-housing/city-housing/national-urban-development/smart-cities-en/smart-cities-en-node.html; Japan: Digital Agency (n.d.[60]), Homepage, https://www.digital.go.jp/en/, 25 January 2023; Korea: Smart City Korea (n.d.[61]), Homepage, https://smartcity.go.kr/en/, 26 January 2023; Switzerland: SwissCom (n.d.[62]), Human Smart City, https://www.swisscom.ch/en/about/innovation/smart-city.html; United Kingdom: Smart Cities UK (n.d.[63]), Homepage, https://smartcityuk.com/ 20 January 2023.
However, no single ministry or agency alone can implement the strategy. As Table 1.2 shows, in some countries, numerous national ministries contribute to smart city efforts. In the United Kingdom, no single department leads the implementation of the Smart City plan, as the implementation of the latter depends on the efforts of different departments across the national government that have a direct or indirect impact on the achievement of smart city goals. Some countries, such as Japan, have created specific agencies to lead digitalisation efforts, including by guiding the development of smart cities in co-operation with relevant ministries.
Countries use partnerships to strengthen their smart city initiatives
Smart city policy frameworks generally outline ways in which governments can build partnerships and co‑ordinate activities and investments with the private sector, stakeholders from non-governmental organisations (NGOs), academia and the community as a whole. According to research, the private sector largely participates in smart city projects in a sort of PPP, which “…consist of mutual adjustments and long-term relationships aiming to define and achieve common goods, such as the reduction of carbon dioxide emissions, economic growth, and industrial development” (Pianezzi, Mori and Uddin, 2021[64]). For example:
In 2019, the national government of Brazil introduced the National Chamber of Cities 4.0 as part of the Internet of Things Plan to bring together a wide array of stakeholders from the private sector, academia and governments to discuss the best technologies to serve people and cities. The Ministries of Regional Development (MDR) and Science, Technology and Innovations (MCTI) co‑ordinate the Chamber. This forum aims to raise the quality of life in cities through the adoption of technologies and practices that enable the integrated management of services for citizens and the improvement of mobility, public security and use of resources (Government of Brazil, 2022[65]).
In 2016, Germany’s federal government set up the Smart Cities Dialogue Platform to address the opportunities and challenges of digitalisation for urban development and identify the opportunities and risks of digital technologies at the local level. The platform is composed of 70 experts from municipalities, district and local authorities, federal ministries, state ministries for urban development, research organisations and civil society. Participants developed a mutual understanding of the values and goals for smart cities comprised in the Smart City Charter and elaborated guidelines and recommendations for action supporting its members in their implementation (Government of Germany, n.d.[66]).
In Japan, the Smart City Public-Private Partnership Platform was established in 2019 with the aim of accelerating smart city initiatives, with companies, universities and research institutions, local authorities and relevant ministries and agencies as members. As of 2022, there were 931 participating organisations. The platform is engaged in providing priority support for smart city projects by government agencies, organising subcommittees on issues and themes faced by members, supporting information sharing and matching among members such as companies, universities, research institutions and local authorities, and promoting the spread of smart cities both domestically and internationally.22 Moreover, the Smart City Institute Japan (SCI-Japan) is a private sector-led non-profit organisation founded by thinktank Mitsubishi UFJ Research and Consulting and newspaper company Nikkei in 2019. It was created as a knowledge and public-private-academic partnership platform to promote the expansion and advancement of smart cities in the country. Since its creation, SCI-Japan has expanded rapidly, showing that there is a high demand for smart cities in Japan. Currently, SCI-Japan has over 490 members and reached 500 members in 2022. Members of the institute are from various organisations, such as national government ministries, corporations, universities and non-profit organisations. Among its tasks, SCI-Japan collects, analyses and shares the latest information on the world’s leading smart cities and know-how for promotion, formulates proposals and advice on the promotion of smart cities and facilitates the exchanges of knowledge and networking between various entities related to smart cities. For the promotion of smart cities, SCI-Japan develops training programmes for Smart City Architects, develops and promotes key performance indicators (KPIs) for liveability and well-being, and promotes the use of My Number Card (Smart City Institute Japan, 2022[67]).
The United States federal government set up the Smart Cities and Communities Task Force to co-ordinate federal action and partnerships with academia, industry, local cities and communities to enable cities of all types to access networking and information technologies and services (ITF, 2020[22]).
In 2023, in the Netherlands, the national government introduced an initiative called Dutch Metropolitan Innovations (DMI) as a PPP to facilitate the sharing and use of data in a responsible manner through mutual trust and open standards. The DMI ecosystem aims to accelerate the rollout of data-driven solutions for major societal challenges that currently beset the country, such as providing affordable housing, transport solutions and a sustainable environment. The partnership is composed of the Dutch business community, knowledge institutes, municipalities (including the 45 of the largest cities in the country), provinces and the national Ministries of Infrastructure and Water Management and of the Interior and Kingdom Relations under a joint set of agreements (see Box 2.29) (Government of the Netherlands, 2023[68]).
The experiences of Brazil, Germany and the United States suggest that building smart cities is a collaborative effort of different national-level bodies in co-operation with local governments, the private sector, academia and civil society. This requires sound governance arrangements that facilitate co‑ordination, communication and the implementation of national policy across all levels of government.
Partnerships for smart cities are also created at the local level. Leading smart cities worldwide have designated a specific organisation to lead and co-ordinate the different stakeholders (e.g. local governments, private sector corporations, universities and research institutions, local businesses and residents) in smart city projects. These public-private joint councils or consortia are designed as permanent organisations with full-time staff. They not only arrange meetings but roll out smart city initiatives by utilising the funding and know-how of the public and private sector stakeholders participating in the project. Amsterdam Smart City is an example of an initiative to build partnerships for smart city projects in a wide variety of areas (Box 1.11).
Box 1.11. Amsterdam Smart City
Amsterdam Smart City is the innovation platform of the Amsterdam Metropolitan Area. It is a partnership between businesses, authorities, research institutions and residents. The city’s residents have a central role in all projects and initiatives so that ideas and solutions for the city are created together. The Amsterdam Smart City initiative aims for sustainable economic growth, efficient use of natural resources and high quality of life. Amsterdam Smart City has grown to be a platform with over 100 partners active in more than 70 innovative projects. It challenges companies, citizens, the municipality and knowledge institutions to submit and apply innovative ideas and sustainable solutions to urban challenges. Areas of interest for developing projects, ideas and new business models are smart housing, open data, smart grids, home energy storage, connectivity and smart mobility.
Source: Discover Amsterdam (n.d.[69]), Amsterdam and Partners, https://www.iamsterdam.com/en/our-network/municipal-government/amsterdam-smart-city#:~:text=The%20aim%20of%20the%20Amsterdam,storage%2C%20connectivity%20and%20smart%20mobility.
Data and standardisation for smart cities
For data to be shared effectively, a comprehensive common standard or a unified ontology (i.e. understood as a definition of concepts and their relationships) must be developed and adopted across the board to handle data from different sources and fields. The problem is that multiple service providers and government organisations oversee city management in cities. Separate programme offices and operation units generate data and use communication systems that are not connected by a common membership or structure. The different components of the smart city ecosystem are managed independently and evolve on their own, making it harder to share data and enhance policy co-ordination and pursue a common vision for the smart city. For example, it is common to find a surveillance system deployed by city police, an ambulatory system deployed by hospitals and e-governance systems developed by a municipal government, all developed and operating independently based on the specific objectives of their managing organisation. In Canada, for example, provincial governments have oversight of digital identification (ID) and rules governing data vary in each province and territory. This may complicate the sharing of information among jurisdictions (SCC, 2021[70]).
Countries are developing smart city standard frameworks to facilitate data sharing and management. In the United Kingdom, for example, the British Standards Institution (BSI) developed PD 8100 as the British standard for guiding the planning and implementation of smart city strategies and providing guidance on the applicability of smart city approaches to smart cities. It covers the role of data and technology in the development of smart cities. Standards are based on good practice from successful smart city initiatives. The BSI framework categorises standards into three main levels:
Strategic level (level 1) – Standards at this level aim to provide guidance to city leadership (i.e. anyone in a strategic position within a city whose decisions have an impact on how the city functions) and other bodies on the process of developing a clear and effective overall smart city strategy. They guide the identification of priorities, the development of a roadmap for implementation and the monitoring and evaluation of the strategy.
Process level (level 2) – Standards focus on procuring and managing smart city projects, particularly on those that cross organisations and sectors through best practices and associated guidelines.
Technical level (level 3) – Standards cover the myriad technical specifications that are needed to implement smart city products and services and contribute to the general objectives of the smart city strategy and vision (BSI, 2015[20]; Lea, 2016[71]).
The PAS 181 Smart City Framework (SCF), developed by the United Kingdom (UK) Department for Business, Innovation and Skills, highlights good practices for city leaders to develop, agree and deliver smart city strategies that can help transform their cities’ ability to meet current and future challenges. Current innovative practices are distilled into consistent and repeatable patterns that cities authorities can use to develop and deliver their own strategies. It does not present nor provide a one-size-fits-all model for the future of cities but stresses the enabling processes by which the use of data and technology together with organisational change can assist diverse cities to become more efficient, effective and sustainable. The SCF emphasises the importance of leadership and governance, culture, business model innovation and how a diverse array of stakeholders can take part in the creation, delivery and use of city spaces and services (BSI, 2022[72]).
In India, the Bureau of Indian Standards (BIS) has developed a data exchange framework to facilitate data management and regulate their use. The Data Exchange Framework describes the data reference architecture, interfaces of data exchange components and the usage cases that are enabled in the smart city ecosystem. It constitutes a set of services that enables the consumption of resources, such as data by a consumer from one or more resource servers, based on explicit consent obtained from the provider of the resources (BIS, 2019[73]). It covers a catalogue of services that provides a framework to manage metainformation about resources, authorisation services to manage the authorisation to access resources and the service that provides a standardised way to access resources.
In Canada, the Standards Council of Canada (SCC) established the Canadian Data Governance Standardization Collaborative in 2019. The collaborative is a group of 220 actors across government, industry, civil society, Indigenous organisations, academia and standards development organisations. The purpose is to accelerate the development of industry-wide data governance standardisation strategies. Standardisation is regarded as a tool to support innovation and ensure companies remain competitive. In 2021, the SCC issued the Canadian Data Governance Standardization Roadmap (SCC, 2021[70]), which describes the current and desired standardisation landscape and makes 35 recommendations to address gaps in the field and explore new areas where standards and conformity assessment are needed. The roadmap intends to use standardisation to build trust and increase confidence in government’s data management. This framework does not refer to the development of smart cities per se but provides valuable lessons on how standards can be developed and the issues that need to be taken into account, such as identifying key challenges and setting priorities.
In general, the case of Canada, India and the United Kingdom show that there should be increased standardisation of data rules to facilitate greater interoperability across the country, including cities. It is essential that standards are aligned across jurisdictions. Standards should be the result of a collaborative effort of actors from different domains and be built on the experience of national and local actors in developing standards as well as smart city best practices. Common terminology and definitions should be agreed upon to ensure that all actors speak the same language. Standards should also outline the roles and responsibilities of the various entities involved in the data exchange ecosystem. Data governance practices should be adapted to the different sizes and types of organisations and, in particular, cities. Standards should be updated regularly, adapting to changes in the context where smart cities operate.
Moreover, the International Organization for Standardization (ISO), a worldwide federation of national standards bodies, has developed a set of standards for smart cities and communities. The objective is to provide a series of evaluation axes and indicators to measure the state of cities worldwide. ISO 37122: “Sustainable cities and communities – Indicators for smart cities” provides a set of indicators for measuring the performance of cities across a number of areas.23 It allows them to draw comparative lessons from other cities around the world and find innovative solutions to the challenges they face. ISO 37122 complements ISO 37120: “Sustainable cities and communities – Indicators for city services and quality of life”, which outlines measurements for evaluating a city’s service delivery and quality of life.24 ISO 37122 and ISO 37120 also intend to assist cities in achieving the United Nations Sustainable Development Goals by assessing their performance.
ISO 37122, when used in conjunction with other indicators, intends to help cities implement smart city policies, programmes and projects to address challenges such as climate change, ageing populations and economic instability, among others. The indicators are designed to use data and digital technologies to improve public services and quality of life, and promote sustainability in a more innovative manner. ISO 37122 is composed of 15 sectors covering areas from economy, education, energy, environment and climate change to housing, public transport, water and urban planning. Table 1.3 provides a summary of the indicators included in ISO 37122.
Table 1.3. Indicators for smart cities assessment - ISO 37122
Source: Based on Kristiningrum, E. and H. Kusumo (2021[74]), “Indicators of Smart City using SNI ISO 37122:2019”, https://doi.org/10.1088/1757-899X/1096/1/012013.
ISO 37150 series and other standards developed under ISO TC 268/SC 1 and SC 2 dealing with “Smart community infrastructures and transportation” are useful resources for smart cities investment and development, in particular as regards infrastructures. While ISO/37151:2015: “Smart community infrastructures – Principles and requirements for performance metrics” defines the metrics to evaluate the “smartness” of community infrastructures, ISO/37153:2017: “Smart community infrastructures – Maturity model for assessment and improvement” provides a methodology to assess smartness maturity of community infrastructures. Moreover, ISO 37155-1 and -2 provide a framework for the integration and operation of smart community infrastructures, which can be used for the lifecycle management of smart cities. ISO 37160:2020 is a unique standard that specifies measurement, reporting and verification (MRV) for low-carbon operations of power generation plants. Other types of standards cover IT infrastructure, mobility and transportation, and resilience and disaster reduction for smart cities and communities. Table 1.4 provides a summary of the standards developed by ISO TC 268/SC 1 and SC 2.
Table 1.4. ISO standards on smart community infrastructures and mobility
Source: ISO (n.d.[75]), Standards by ISO/TC 268/SC 1: Smart Community Infrastructures, www.iso.org/committee/656967/x/catalogue/p/1/u/0/w/0/d/0; ISO (n.d.[76]), Standards by ISO/TC 268/SC 2: Sustainable Cities and Communities – Sustainable Mobility and Transportation, www.iso.org/committee/8742800/x/catalogue/.
Table 1.5 shows that there is a wide range of standard activities related to smart cities. This list is not intended to be comprehensive but provides an overview of the different international standards that can be used for the development of smart cities and inform data governance. All these standards can be used to inform the process of developing a smart city and data strategy, guide the process of implementation of smart city projects and provide technical guidance on the implementation of smart city projects.
Table 1.5. Classification of standards activities related to smart cities
Source: The classification of standards activities is based on Lea, R. (2016[71]), “Smart City Standards - An overview. Trying to make sense of Smart City standardization activities”, https://urbanopus.net/smart-city-standards-an-overview/ (accessed on 16 January 2023).
Local authorities should review smart city and data projects systematically
To evolve and improve, smart city policies and programmes need continuity and regular updates. The case of Korea suggests that the development of smart cities requires experimentation and adaptation to be able to mature and evolve (Box 1.12). A key lesson is that the development of smart cities requires specific guidelines to facilitate more efficient implementation of high-technology facilities and systems in new towns. Moreover, the governance framework needs to be revised and adapted to make it fit for purpose. For example, sharing data and information across sectors and among cities may be constrained by regulations regarding privacy protection and, to facilitate this data-sharing process, it is sometimes necessary to explore different collaboration and co-operation instruments such as a memorandum of understanding (MoU). However, signing MoUs with individual agencies and local governments may be a long, complex process; therefore, the enactment of a specific law for this purpose could make co-operation for data and information sharing more effective. A legal framework mandating private actors, including citizens, to grant access to data of public interest to the government under conditions of privacy and security may be the way forward.
Box 1.12. The evolution of smart cities in Korea
Since the early 2000s, Korea has pursued smart city programmes and became a pioneer in the adoption of the concept of the smart city. Since then, smart city programmes have evolved and matured as the country gained experience from its pilot projects and reviewed its goals and legal framework. This evolution can be divided into three periods:
The construction stage (2003-13) focused on creating a new growth engine by combining ICT with the construction industry. During this period, smart city development concentrated on new towns such as Dongtan, where ICT was incorporated into urban planning and the government enacted the Act on the Construction of Ubiquitous Cities (U-City Act) in 2008, focused on infrastructure, technology and services, aiming to competitiveness and quality of life.
The connecting stage (2014-16) focused on connecting smart city services and building governance structures. This period focused on the integration of information and systems that used to operate independently from each other, public transport and crime prevention for example. For that purpose, the government developed smart city platforms through national R&D programmes, which provided the technical basis to integrate U-City solutions that local governments had been operating. Smart city governance and regulations were also revised. Korean government bodies signed a series of MoUs to facilitate sharing of information, institutionalise co-operation and build a smart city governance framework.
The enhancement stage (2017-20) focused on innovative smart cities and creating a smart city ecology that incorporated concepts such as citizen participation, sustainable development and better governance into aspects of smart city projects. Moreover, smart cities were considered a key element for innovative job creation as part of the Fourth Industrial Revolution and not just as a way to solve urban problems. In 2016, the U-City Act was revised into the Law for Smart City Creation and Promotion of Industries (Smart City Act) to facilitate the participation of a wider range of stakeholders in smart city projects. Smart cities were not only used to build new cities but to revitalise deteriorating ones, which are now being transformed into smarter environments.
Source: OECD (2018[84]) Housing Dynamics in Korea: Building Inclusive and Smart Cities, https://dx.doi.org/10.1787/9789264298880-en; OECD (2020[12]) Smart Cities and Inclusive Growth, https://www.oecd.org/cfe/cities/OECD_Policy_Paper_Smart_Cities_and_Inclusive_Growth.pdf.
Stakeholders involved in smart cities and data governance
Smart cities and data governance involve the participation of multiple actors such as national and subnational governments, individuals, organisations and private sector companies that impact smart city projects and the way data are governed. All these actors are key players in the development of smart cities because they not only create and handle data but also benefit from well-governed data. The large number of actors involved in smart cities and, thus, data collection makes it necessary for national and local governments to be clear about the roles and responsibilities of every actor to deliver a successful smart city strategy and ensure the efficient and effective use of data. National and local governments need to address the “politics of data” as many actors may compete to govern data. The reason may be that each of the actors has multiple interests, goals, capacity and strategies. Data governance is not just a matter of rule making and enforcement. It requires social interaction, negotiation and co-operation among a wide range of public and non-public stakeholders (Micheli et al., 2020[85]).
Private sector companies are actively involved in building smart cities
Building a smart city requires the co-operation of many agencies, support by ICT infrastructures and the integration of sustainable development, green growth and collaboration between multi-stakeholders on multiple levels (Kaluarachchi, 2022[86]). Private sector companies are in some cases leading the way in the development and implementation of smart city projects and data collection and management. Their role in data governance tends to focus on protecting and classifying data, securing IT infrastructure, ensuring that data management follows the agreed standards, ensuring the protection of sensitive data and providing technical support for data quality, among others.
National and local governments tend to open up to private sector competition to unleash investment in smart cities. This shows that, in smart cities, the government does not have a leading role or a monopoly on the use of data and digital tools (Franke and Gailhofer, 2021[87]). For example, India’s National Smart Cities Mission (NSCM), introduced in 2015, involves the participation of 100 cities. As part of this initiative, cities that complete their projects are intended to serve as demonstrative examples for their peers of the power of incorporating smart city innovations. However, the ultimate goal of these projects is to spark a wave of public-private investment in the further development of smart cities without the need for direct intervention from the central government and, by 2021, the NSCM had sparked USD 24.6 billion in tendered investment from public and private circles for its projects across participating cities (Bajpai and Biberman, 2021[88]).
The advantages of having private sector companies taking a leading role, together with local authorities, in smart city development are access to cutting-edge technology, funding and financial resources (Mirzaee and Sardroud, 2022[89]), highly skilled human resources (UK Government, 2020[90]) and their extensive experience in the technological development field. For example:
In Korea, the central government is promoting smart city development as it is considered one of the major growth engines for the country’s economy in the near future. Currently, there are two national test beds, Busan and Sejong, and smaller smart renewable city projects initiated by local and regional organisations (OECD, 2018[84]). The focus areas of the green field developments are water management and robotics in Busan and smart mobility and AI in Sejong. Both the private and public sectors are contributing to smart city projects and together invested approximately KRW 3.7 trillion (USD 3.29 billion) on smart city development in 2021.25
In the United Kingdom, the central government acknowledges that collaboration with the private sector is critical in smart city projects, given their complexity (UK Government, 2020[90]). Thus, private technology companies, together with the public sector, lead smart city projects in cities across the country and even abroad due to the technological expertise of their human capital. Companies like Connected Places Catapult in London, Sensor City in Liverpool and the Open Innovations institute in Leeds, combined with projects like Bristol is Open and testbeds like the Digital Health Living Lab in Brighton, support the UK government’s continued investment in its national smart cities vision.
However, partnerships do not only include private companies. Mexico City, for example, is working with a non-profit organisation around earthquake detection.26 Moreover, private companies alone will not be able to contribute to smart city development, as they require the participation of the public sector’s knowledge of the city and of residents’ needs. A potential issue is that most of these projects are prototypes and they are generating enough data to be scaled up and improved, but this begs the question of who owns the data generated by these projects.
In Japan, for example, private companies have been active in the promotion, building and implementation of smart city projects. For cities to attract private sector investment, they need to garner local support and this can be obtained when some clear social benefits and projects appeal to businesses’ social responsibility goals, such as climate change and ensuring citizens’ well-being. For example:
In 2010, the Japanese government funded the Next-Generation Energy and Social Systems demonstration projects in cities. The cities of Keihanna District, Kitakyushu, Toyota and Yokohama received JPY 126.5 billion for these pilot projects, with two-thirds coming from the national government and one-third from the private sector. Private companies, endorsed by local governments, directed their proposals on energy efficiency projects to the national government (Pianezzi, Mori and Uddin, 2021[64]).
In 2014, following the completion of these pilot projects, new smart city projects were launched under the FutureCity programme by the national government. The projects were carried out without a solid promise of funding from the central government. However, several projects were launched and, in 2019, the Cabinet Office, the Ministries of Internal Affairs and Communications, of Economy, Trade and Industry and of Land, Infrastructure, Transport and Tourism established the Smart-City Public-Private Partnership Platform. The platform has over 130 projects and more than 300 companies listed.
Since the Ministry of Economy, Trade and Industry selected the city of Yokohama as part of the Next-Generation Energy and Social Systems Demonstration Area in 2010, the local government has been working with several private companies (e.g. energy-related operators, electronics manufacturers and construction companies) to promote the Yokohama Smart City Project (YSCP), aiming to optimise energy supply and demand balance in urban areas. In 2015, the Yokohama Smart Business Association (YSBA) was established as a public-private co-operation organisation to advance smart city projects and transform Yokohama into an energy-recycling city, resistant to disasters and economically strong, and expand its accumulated technology and experience both inside and outside Japan.27
Japanese private companies have also developed a smart city vision in co-operation with real estate companies and local governments. For example, Hitachi, a Japanese multinational conglomerate, aims to use digital technologies to create a people-centric society that integrates the real and cyber worlds and maintains a stable economy and way of life (Nakano et al., 2021[53]). Box 1.13 shows some examples where private companies have been involved in the development of smart city projects in Japan. Although local governments take part in all smart city projects, most of the current smart city projects are entirely initiated and almost entirely funded by private companies, for example the Fujisawa Sustainable Smart Town set up by Panasonic and the Hitachi Smart Industrial Town led by Hitachi (Pianezzi, Mori and Uddin, 2021[64]; Sakurai and Kokuryo, 2018[91]). A key message from those local experiences is that cities need to develop their capability to use technology to benefit from it.
Box 1.13. Examples of private sector involvement in building smart cities in Japan
In the Kanagawa prefecture, the Fujisawa Sustainable Smart Town (Fujisawa SST) is a joint project between 18 different businesses, universities, local governments and residential organisations, and opened in 2014. The main feature of the project is to develop a town underpinned by advanced technology-based infrastructure but based on actual lifestyles on a 100-year vision. Electronics company Panasonic targeted areas such as energy, security, mobility, wellness and community. The aim was to reduce carbon dioxide (CO2) emissions by 70%, reduce water consumption by 30% and have renewable energy account for 30% of the total energy used. The homes were also tested against a magnitude 1.8 times stronger than the Great East Japan Earthquake of 2011.
In the Fukushima prefecture, Accenture, a professional service firm, and the University of Aizu have been working with the authorities of Aizuwakamatsu City since 2011 on smart city projects. The local government is promoting smart city initiatives in a wide variety of fields: mobility, commerce, education, healthcare, energy, agriculture, tourism, manufacturing, disaster prevention, government and infrastructure. Accenture, the University of Aizu and local authorities are also promoting horizontal deployment for smart cities in Japan, using the town case as a case study. The University of Aizu has been training data scientists and collaborating with private companies to address the problems of the city.
Near Mount Fuji, Toyota, a Japanese car manufacturer, is building a prototype “city of the future” called Woven City. It is set to be a fully connected ecosystem powered by hydrogen fuel cells and is expected to accommodate 2 000 residents and researchers who will test and develop technologies such as autonomous cars, robots, smart homes, etc. All homes will be equipped with the latest in human support technologies, from sensor-based AI that monitors people’s health to taking care of basic needs and enhancing daily life. The project is an opportunity to deploy connected technology with security.
The Osaka prefecture faces challenges such as an ageing and shrinking population, the need to revitalise buildings and the threat of natural disasters. Plug and Play, a global venture accelerator, is helping the city of Osaka to tackle those issues. The company will carry out an accelerator programme focused on smart life and construction, travel and experiences, urban mobility and clean technology, hospitality and health and will be carried out at Knowledge Capital in Grand Front Osaka in co‑operation with Osaka Prefecture and Osaka City.
In the Fukuoka prefecture, the messaging application LINE has been working with Fukuoka City to improve services such as residential tax payment, large garbage collection, natural disaster notifications and infrastructure reports; more recently, they introduced LINE Pay’s QR code into public facilities and even an umbrella sharing scheme. The aim is to connect local government authorities, companies and residents to solve local problems and create new services through the use of technology.
In the Takeshiba district, the Tokyu Land Corporation and the SoftBank Corp. have been working since 2019 on a smart city model case that utilises cutting-edge technology. The project involves the creation of a data distribution platform that enables real-time utilisation of data such as people flows, user profiles, road and traffic conditions, water levels, etc. The aim is to improve mobility, reduce congestion and strengthen disaster prevention.
Source: For all cities: Tokyoesque (2022[92]), “Smart cities in Japan: Practical innovations for conscious future living”, https://tokyoesque.com/smart-cities-in-japan/; Fujisawa: Fujisawa SST (n.d.[93]), About Fujisawa SST, https://fujisawasst.com/EN/project/; Aizuwakamatsu: Muroi (2021[94]), “Initiatives and vision for Smart City Aizuwakamatsu”, Information provided by the government of Aizuwakamatsu City, Aizuwakamatsu, and OECD (2021[8]), OECD Economic Surveys: Japan 2021, https://dx.doi.org/10.1787/6b749602-en; Woven City: Toyota (2020[95]), “Toyota to build a hydrogen-powered city of the future”, https://mag.toyota.co.uk/toyota-woven-city-hydrogen-power/; Osaka: PRNewswire (2020[96]), “Plug and Play Japan to open its new office "Plug and Play Osaka"”, https://www.prnewswire.com/news-releases/plug-and-play-japan-to-open-its-new-office-plug-and-play-osaka-301103175.html; Fukuoka: LINE Fukuoka (n.d.[97]), Line Smart City for Fukuoka, https://smartcity.linefukuoka.co.jp/ja/project/smartcityproject?hsLang=ja-jp; Takeshiba: Smart City Takeshiba (n.d.[98]), Homepage, https://smartcitytakeshiba.com/ 4 September 2022.
At the national level, the Nippon Telegraph and Telephone Corporation (NTT Group) is participating in the development of smart cities working on urban digital twin computing (DTC) to provide new value by optimising services provided in cities. The objective is to capture environments, objects and people that are associated with each service provided in a community, create their digital twins and use DTC to link the twins across different industries. By combining urban DTC with the four-dimensional (4D) digital platform, which is being developed separately, NTT Group aims to create a data-driven and optimised smart city (Yamamoto et al., 2021[99]). In this way, the value of services made available by service providers in a district is enhanced and offers new services. An additional example is NEC Corporation, a Japanese multinational information technology and electronics corporation, which participates in the elaboration of the city OS platform of several smart city projects. NEC aims to contribute to the revitalisation of city management and resolve local issues by contributing to cross-domain data collaboration.
While countries and cities intend to build a demand-driven and citizen-based smart city ecosystem, they are encountering some barriers. For example, although the participation of private corporations in smart city projects has allowed cities to access their technology and expertise, generally, locally driven initiatives face issues of project scalability and sustainability. Private corporations might not be willing to invest in activities or projects with few prospects of short-term returns and may implement projects that only solve problems partially or focus on specific areas of a city. Certainly, private corporations have limited amounts of R&D budgets and governments must select projects based on available budgets; it is, however, important that each stakeholder consider the opinions and needs of all other stakeholders.
In countries like Japan, private sector corporations participate in smart city projects without the expectation of recouping their investments from the government. According to Pianezzi, Mori and Uddin (2021[64]), local governments’ financial contribution to smart cities projects is rather limited in Japan, as their role is to encourage private companies to propose projects aligned with national agendas on issues such as carbon emissions and climate change, and to play a co-ordinating role. Local governments use their image to attract private companies to participate in smart city projects: it is indeed important for private companies to be associated with national and local governments. All smart city projects are experimental in character and revolve around areas such as energy management, transport, crime prevention, etc. Companies are therefore invited to experiment with innovative technologies in cities while contributing to national goals on energy saving and emissions reduction. Companies use this opportunity to test their technologies, establish a space for themselves in the future and sell their technologies on international markets with the central government’s support.
Citizens’ participation in smart city projects needs to be strengthened
To create value for citizens and society as a whole, governments must be able to access, aggregate and use data about their citizens, including data from private companies. A critical issue in data governance is that using data-based technologies and data analytics for urban public services often means handing over the data and governance of urban environments to private contractors, increasing surveillance of urban spaces and cutting off citizens from the control of and participation in urban planning and governance (Chawla and Divij, 2021[100]). This problem was exemplified in the case of Toronto’s Quayside smart city project, where centralised decision-making processes to drive data collection and analysis and the predominance of collaborations with or outsourcing to private actors prevented residents from taking part in decision-making processes on how their data should be managed. This situation led to the project being cancelled. (Box 1.14). Toronto’s experience shows the risks of having a weak communication strategy and centralised decision-making processes to drive data collection and analysis or just outsourcing to the private sector without including citizens’ views.
Similarly, India’s DataSmart Cities strategy (see Chapter 2) and city data policies promote highly centralised information systems, such as the Integrated Command and Control Centers for city surveillance. These initiatives generate data that are treated as the property of specific departments or offices and executive officials are responsible for deciding what data should be made available, to whom and how but without citizens’ involvement. There is no consideration about how city residents might have a say about how and what information about them is generated, processed and shared or how it should be commoditised. This begs the question of the values data governance seeks to promote.
Box 1.14. Toronto’s Quayside smart city project
In 2017, Waterfront Toronto, the government agency in charge of developing 800 acres along the city’s eastern seaboard, selected Sidewalk Labs, an urban planning and infrastructure subsidiary of Google, as the winner of a public bidding process with a project to develop a 12-acre lot on the waterfront called Quayside as a global hub for urban innovation. The project was intended to create 3 900 direct jobs and a one-time construction impact of CAD 1.6 billion for the Canadian economy. The project included digital technology deployments such as sensors to capture data to inform better decisions in housing and traffic policies, trash management and delivery of other city services, environmentally friendly public transit options including autonomous cars, biking and walking trails, high-speed public Wi-Fi, parks and recreation spaces, and more. It also promised a rigorous data privacy and governance regime and agreed not to sell citizen data without consent unless it was aggregated and anonymised. Sidewalk Labs’ project had been selected due to its extensive engagement with local leaders, holding town halls and public roundtable meetings and setting up a residents’ panel and advisory boards of local experts to help shape the project.
However, the Quayside project faced opposition because Sidewalk Labs had apparently planned to develop a larger area than that originally contemplated. Residents and local leaders became suspicious after the press reported in 2019 that Sidewalk Labs had plans that extended beyond Quayside to a much larger area estimated at 350 acres. That bigger plan included opportunities to generate revenues from real estate development and advisory services, financing for a light rail extension and underground infrastructure on that property. Press articles brought about concerns about how big companies could use their influence and power in a way that could damage democracy and public interest. As a result, a social media campaign against the project erupted. In June 2019, Sidewalk Labs released its Master Innovation Development Plan for the Toronto project to show full disclosure. The plan aimed to create an Innovative Design and Economic Acceleration (IDEA) District – not contemplated in the original agreement – in 2 phases over 20 years, including a 67-acre parcel called the River District, and trigger private investment of CAD 38 billion. The project promised some 93 000 jobs, including 44 000 full-time direct jobs, 34 000 housing units, of which 40% would be at below-market rates, CAD 4.3 billion in annual tax revenue and CAD 14.2 billion in annual gross domestic product (GDP) for Canada. However, after the publication of the plan, Waterfront Toronto’s Digital Strategy Advisory Panel raised many concerns over the Sidewalk Labs project. In 2020, Sidewalk Labs decided to terminate its participation in the project.
In 2022, a new plan for Quayside, called Quayside 2.0, developed by a group of international architects, was published. The new project promotes a hybrid notion of an urban neighbourhood as natural and manmade.
Source: Sidewalk Labs (2017[101]), Toronto Tomorrow: A New Approach for Inclusive Growth, https://www.torontopubliclibrary.ca/detail.jsp?Entt=RDM3820301&R=3820301; Wachter, S. (2019[102]), “What’s fueling the smart city backlash?”, https://knowledge.wharton.upenn.edu/article/whats-behind-backlash-smart-cities/; Jacobs, K. (2022[103]), “Toronto wants to kill the smart city forever”, https://www-technologyreview-com.cdn.ampproject.org/c/s/www.technologyreview.com/2022/06/29/1054005/toronto-kill-the-smart-city/amp/; Chown Oved, M. (2019[104]), “Google’s Sidewalk Labs plans massive expansion to waterfront vision”, https://www.thestar.com/news/gta/2019/02/14/googles-sidewalk-labs-plans-massive-expansion-to-waterfront-vision.html.
Moreover, citizens only provide and allow access to data when they trust actors in charge of data management. Citizens are wary about how city governments and big technology companies involved in smart city projects track and collect data about their daily activities and the selling of data without their consent. Big data are intrinsic to smart cities and, invariably, they create concerns over data privacy and security.
The experience of Vancouver, Canada, suggests that smart cities engage the broad public in the city‑making process, leading to better answers and deeper public ownership of their future (Toderian and Glover, 2014[105]). Citizens not only use public services provided via the different applications and smart technologies: they are the main producers and providers of data (Franke and Gailhofer, 2021[87]). Citizens’ participation could be promoted through the organisation of online town hall events to engage citizens via social media outlets (e.g. Facebook, X [formerly Twitter]) for scheduled time periods, allowing the use of smartphones to access city services such as waste collection schedules, recreation services and locations, and building inspections (e.g. Surrey in Greater Vancouver, Canada), the creation of participatory consensus-building platforms (e.g. the city of Kakogawa, Japan) and expanding online consultation.
Smart city governance frameworks need to be flexible enough to combine top-down policies with bottom‑up initiatives on smart city development. So far, existing governance frameworks are, in general, rather rigid as local governments are largely executors of central governments’ policies.
Living labs are being used to involve citizens in smart city projects. They are innovation ecosystems in real-life environments that use iterative feedback processes to create sustainable impact by focusing on co-creation, rapid prototyping, testing and scaling up innovations and citizens (Box 1.15).28
Box 1.15. Examples of living lab projects in OECD cities
In Milan, Italy, the San Raffaele Hospital (HSR) has set up the City of the Future Living Lab as a virtual and real research environment and community. The lab is managed and organised by eServices for Life and Health, a department of HSR specialised in the application of ICT to health. The aim is to develop and deliver services to the hospital’s infrastructure and foster innovation across numerous domains and disciplines. Several stakeholders and partners work together and share knowledge in a wide variety of ICTs, creating a fertile ground for innovation and cross-disciplinary research and communication.
In the city of Bodrum, Türkiye, the Bodrum Living Lab aims to create economic and social value by developing, prototyping, testing and implementing innovative products and services related to agriculture, tourism, well-being, health and maritime verticals developed in co-ordination with its stakeholders.
In Saint Etienne, France, the Design Creative City Living Lab involves users at an early stage of the development phase of the innovation process by creating a trusted environment where small and large business stakeholders can meet to test out innovative products, services and business models. It also provides a platform for exploring societal and policy goals related to ICT and human-adapted design innovation in an urban context.
In Copenhagen, Denmark, the local government has authority over childcare, primary education, senior citizens’ welfare, healthcare and public services. To facilitate dialogue with citizens and promote innovation, local authorities created the Copenhagen Solutions Lab as an incubator for smart city initiatives to develop smart city projects. The Copenhagen Solutions Lab identifies and co-ordinates smart city needs across the municipality’s departments and matches them with existing knowledge and solutions on the market. In this way, the lab acts as a bridge between external partners and the local government’s initiatives concerning smart city development. Through collaborations with the research community and the market, the city gains access to the innovation power that is needed to create new and effective urban solutions.
Source: For Milan: Ospedale San Raffaele (n.d.[106]), Advanced Technology in Health and Wellbeing, https://research.hsr.it/en/search/index.html?q=eservices+; For Bodrum: Bodrum Living Lab (n.d.[107]), Homepage, https://bodrumlivinglab.com/en/home/, 8 December 2022; For Saint Etienne: Cité du Design (n.d.[108]), Pôle Entreprises & innovation à destination des entreprises, https://www.citedudesign.com/archives/fr/entreprises/; For Copenhagen: Nordic Smart City Network (n.d.[109]), Copenhagen Solutions Lab, https://nscn.eu/Copenhagen.
Challenges to promote smart cities and data governance
The development of smart cities provides an opportunity for the use of real-time data with the ultimate goal of solving critical urban problems. However, the effectiveness of digital solutions and technology-led innovations depends on access to data from a wide variety of sources, raising questions on data ownership, privacy, storage and security of data.
Governing data in smart cities may be fraught with regulatory and management challenges
With smart cities collecting massive amounts of generally heterogeneous data, local policy makers are challenged to determine what data are necessary and sufficient to ensure the functioning of smart city projects. Rules need to clarify how and when data can be collected and shared. Data management is subject to specific regulations and may vary depending on whether it is about personal or corporate data, data collected through digital technologies or data provided by citizens. Furthermore, smart city projects are subject to specific regulations depending on their domain of operation, such as transport, telecoms, water or energy supply. Moreover, smart city data prompted concerns about consent to capture, process and store data. Data that identify a particular individual (i.e. location, health records, daily activities) belong to that person but they can be legally shared or accessed if the entity receiving it has a legitimate reason. Local governments and private companies may act as data controllers or processors as part of their smart city projects but the challenge is to make sure they comply with the legislation to avoid breaching the law and being challenged on their data use.
National and local governments have enacted vast legislation to ensure adequate management of data and data safety. Technological innovations call for more guidance to clarify the reach of new technology developments and explain to individuals how they can protect their data more effectively. However, excessive regulation may hamper efforts to protect data and ensure privacy. Most countries have issued general regulations to protect data and personal information but this general regulation is also supplemented with secondary laws and guidelines that regulate data and information in specific domains. Data privacy protection and data security are particularly sensitive to excessive regulation, given that the latter may impact trust in data management practices and smart city projects. Appropriate regulation and the rule of law can strengthen trust but excessive regulation has the opposite effect when it makes it harder for public and private organisations and companies to comply with fragmented pieces of legislation. Over‑regulation may also threaten the capacity of cities and their city OS to collect, store and share data. For example, regulations may require cities or partners to store large amounts of data that must be reported, which in turn will create a data overload and lead to high costs of maintaining large amounts of data.
The funding and financing mechanisms of smart city and data projects also largely impact their success. Funding is at the heart of any smart city investment project; the challenge is that cities rarely have enough resources to invest in smart city projects and require resources from other government and private sector levels. Ensuring enough funding demands cities to be skilful in using different budget streams to build synergies among several investment programmes and to be flexible enough to collaborate with neighbouring cities to ensure sufficient financial resources. The experience of India’s National Smart City Mission (NSCM) suggests that design flaws in the financing mechanisms have a negative impact on the capacity of the city to meet the deadlines in the implementation process and undermine the trust among partners (Box 1.16). A smart city requires clear rules about funding and flexible-but-solid budgetary practices that facilitate the movement of resources among programmes and across jurisdictions.
Box 1.16. Funding smart city projects in India
In 2015, the national government of India introduced the National Smart City Mission (NSCM) to fund smart city projects in 100 cities across the country. Cities were invited to submit smart city project proposals for funding. Once a city was chosen through a competitive process, it was required to set up a special-purpose vehicle (SPV) to co-ordinate financing and implementation.
To obtain funds from the national government and matching funds from the state government, the SPV was required to obtain the remainder of funding via other means: municipal bonds, land use conversion charges, user fees, synergies with other programmes, sale of government assets and private sector participation. However, the SPVs found managerial, technical and financial difficulties in implementing and completing projects according to the project timeline due to delays in the disbursement of funds from the national and state governments. Part of the reason for the delays was the failure of cities and states to mobilise the counterpart funding required according to the guidelines of the NSCM.
Moreover, the siloed competitive grant process prevented projects from building synergies within or between cities. The Urban Local Bodies (ULBs) in charge of developing the project proposals proposed projects that are more likely to obtain funding than those that respond to cities’ development priorities. Another problem was that the definition of what constitutes a smart city was blurred, leading to inefficient use of resources.
Projects funded under the umbrella of the national smart city strategy do not necessarily fit into what is considered “smart” as they lack the technological and data elements. For example, In India, the city of Agra used the funds granted under the NSCM to build handicraft training centres for traditional embroidery; the city of Coimbatore invested in developing food kiosks, open plazas and fountains; and Prayagraj installed a plastic-to-diesel conversion plant. There was no metric to ensure that individual projects selected for funding met cities’ needs apart from being aligned to the NSCM’s goals.
Source: Bajpai, N. and J. Biberman (2021[88]), “India’s Smart City program: Challenges and opportunities”, https://csd.columbia.edu/sites/default/files/content/docs/ICT%20India/Papers/ICT_India_Working_Paper_62.pdf.
Across OECD countries and cities moving towards smart city initiatives, data, and in particular big data,29 are expected to unleash innovation to solve social, economic and environmental challenges. However, a key challenge is that data are still often stored in silos. For example, data from sensors monitoring vehicles and pedestrian movements may not mean much unless they are combined with other types of data, such as weather and road conditions. Releasing data from silos and sharing them may enhance their value and produce social and economic benefits.
Governing and managing data require the involvement of different actors that might often have conflicting interests due to their different roles in creating positive outcomes. Citizens’ concerns derive from their role as voters, consumers, employees, students, drivers, etc. City administrations perform the functions of a decision-maker, law enforcement body, data donor, etc. Private sector bodies (i.e. enterprises) have a role as job creators, investors, data generators and providers and business makers. All these different interests must be reconciled to be able to benefit from data-enabled projects and manage possible risks that data management entails. Governing smart city data should thus focus on the co-ordination of all these actors on an organisational and technical level (von Grafenstein, Wernick and Olk, 2019[110]). In the public sector, the data strategies of the different levels of government may not always be sufficiently linked (e.g. those of national governments and those of local and regional governments), which may prevent the creation of synergies.
Sharing data and information across city departments and among cities is another challenge for smart data governance. In general, each government and each city agency typically have their own silo of confidential or public information. In some cases, they are reluctant to share what might be considered proprietary data. In addition, some data may be governed by certain privacy conditions that make them hard to share across different entities. The challenge for smart cities is finding ways to prevent or reduce the barriers to seamless information sharing and exchange among different stakeholders (Al Nuaimi et al., 2015[111]). Many countries, such as Germany and the Netherlands, face difficulties in combining and analysing data from the mobility, housing and urban planning domains, and the development of data-intensive applications is lagging behind. Moreover, it is not always easy to locate data sources and users. The experience of the city of Vienna, Austria, suggests that knowing what data are available and who is responsible for them is a key challenge in the implementation of the local data strategy (see Chapter 2). For this, the city government has set up a data catalogue, which includes technical data descriptions available on the intranet and is currently being developed into a data map.
In many cases, smart city applications use data from a variety of sources, including IoT devices as well as data from multiple industries or platforms and some require cross-industry data aggregation. Thus, smart city projects require governance protocols that facilitate sharing of data in a dynamic manner. Initiatives such as the LinkNYC programme in New York City, which focuses on replacing payphones with Wi‑Fi‑enabled kiosks, require inputs from three different companies to provide data, hardware and network capabilities.
Data sharing could uncover problems with refinancing. Public sector data tend to be open and made available for minimal prices or even free of charge, making it difficult for public sector bodies to refinance all of the processes of data collection, reproduction, transfer, dissemination and storage, limiting the possibilities of investing in innovative digital applications. The free transfer of data from public sector bodies to private companies may result in global companies benefitting from open data approaches, as they will be able to generate benefits without any need to co‑operate with the public data holder. This discourages the establishment of viable data co-operation and corresponding business models. Moreover, making data available to third parties could be costly and administratively cumbersome due to the need for bilateral tailor-made agreements, or data sharing should be conducted via a central platform, which could lead to a loss of control over one’s own data.
Adherence to traditional administrative processes may hinder the use of data and, in consequence, digitalisation. Japanese cities, for example, are shifting from a stage of competition for investment and recognition, working in isolation and short-term strategies, to one of co-operation and a long-term development vision. However, unwieldy procurement processes, fragmented administrative systems and dependency on legacy systems could hinder these efforts.
Equipping vulnerable groups (e.g. the elderly, low-skilled workers) with basic digital skills is becoming a key policy priority for countries and cities as it can boost their opportunities to benefit from services offered in smart cities. The reason is that digital skills are permeating societies and labour markets across all jobs ad sectors, not only ICT-related occupations. The OECD Skills Outlook 2019 report found that 15% of adults lack basic digital skills and 13% lack basic digital, numeracy and problem-solving skills, while 14% of jobs on average are likely to be automated in the coming years (OECD, 2019[112]).
Smart city data are prone to security and privacy risks
A critical issue for smart cities and data strategies is to protect people’s privacy, as data collection may disclose sensitive information. Protecting people’s data privacy is a complex domain as several interrelated privacy forms need to be considered. For example, identity, bodily, territorial, locational and movement, communications and transactions privacy are some of the privacy forms that can be threatened and breached, producing different forms of harm to individuals (Kitchin, 2016[23]). In the context of smart cities, privacy may be understood as “…the preservation of the information that is collected, processed and disseminated that relates to an individual’s person, behavior, habits, communication, location, associations or feelings” (Curzon, Almehmadi and El-Khatib, 2019, p. 78[113]). Data governance succeeds when data protection and action are both realised and balanced and when the benefits are equitably distributed.30
Smart city national frameworks (SCNFs) should enhance data protection. Smart cities need to access and use big data but the latter also raise privacy concerns. The SCNFs generally stress the importance of managing data with care, ensuring the security and privacy of individuals. Countries enact legislation on data protection that supports SCNFs and data strategies in their quest to protect the security of data and the privacy of individuals. In Canada, for example, smart city projects need to comply with the Personal Information Protection and Electronic Documents Act (PIPEDA) (Privacy Commissioner of Canada, 2019[114]). In the European Union, between July 2018 and April 2023, 1 616 fines amounting to around EUR 2.7 billion were handed out to different individuals (mostly large high-technology companies) for not complying with General Data Protection Regulation (GDPR) (CMS, 2023[115]). The most common violations have been the insufficient legal basis for data processing, not complying with general data processing principles, insufficient technical and organisational measures to ensure information security and insufficient fulfilment of data subjects’ rights.
Across countries and the research community, a large part of discussions on data governance focuses on data sharing and access, considering that data keep flowing internally/externally in the process of collecting and using data. These flows necessarily entail issues of what is being shared and accessed by whom, which involve both the source of data (i.e. concerns about privacy, competitiveness, etc.) and the destination (i.e. openness and ownership). Table 1.6 summarises the risks of data sharing into four items. While trust/privacy and transaction costs concern difficulties and errors in realising data sharing due to technological and regulatory limitations, competitive concerns and lost financial opportunity are more fundamental scepticism about the usefulness of sharing data.
Table 1.6. Four risks of data sharing
Source: Based on Candelon, F. et al. (2020[116]), “Simple governance for data ecosystems”, https://www.bcg.com/publications/2020/simple-governance-rules-for-data-ecosystems.
Some of the data governance agendas focus on overcoming technological limitations in implementing control measures. For example, data anonymisation is considered an essential step to ensure privacy and security and needs to be done prior to sharing data. However, countries such as Australia have concluded that there is no such thing as anonymisation because there is no complete guarantee that individuals in datasets considered anonymised cannot be found. Research has also pointed out that complete anonymisation, to the extent that it does not harm the usefulness of data, is essentially impossible in many fields (von Grafenstein, Wernick and Olk, 2019[110]). Efforts to embed the anonymisation in the data collection stage, i.e. anonymisation by design, could also be hampered (PwC, 2019[117]). A more accurate term than anonymisation would be de-identification of data according to the New South Wales, Australia, Government Data Strategy (NSW Government, 2021[118]).
To protect data privacy, smart city technologies request the notice and consent of users to collect their data. However, researchers argue that this could be an empty exercise due to issues of datafication, inference, repurposing and even opacity (Kitchin, 2016[23]). Citizens do not always have the time, knowledge and awareness to manage their own data in an informed manner. In many instances, citizens provide their consent for their data to be collected and used without realising the extent and consequences this may have for them and society as a whole. In general, privacy policies are more a liability disclaimer for businesses than assurances of privacy for citizens (Tene and Polonetsky, 2013[119]). Certain digital technologies, such as smartphones applications do not even request consent for data collection and application developers may even change the terms and conditions without notice.
The re-identification of anonymous data is another potential threat to privacy. Smart cities use digital technologies that promise the anonymisation of data using pseudonyms or aggregation. However, new computational techniques can make the re-identification of data a straightforward exercise. Inference and linking the pseudonyms to other accounts and datasets means that it is possible to re-identify individuals unless data are completely de-identified, which is rarely the case (Kitchin, 2016[23]). Research has shown that using a generative model of data re-identification, 99.9% of Americans would be correctly re-identified in any dataset using 15 demographic attributes, even in heavily sampled anonymised datasets (Rocher, Hendrickx and de Montjoye, 2019[120]).
Sharing and repurposing data in a way that was not originally intended are an additional threat to data privacy. In smart cities, data are collected for a specific purpose and use, and retained for only as long as needed but this cannot always be guaranteed. The reason is that data markets seek to generate large volumes of data to extract additional value (Kitchin, 2016[23]). Data can be repackaged, sold and repurposed in different ways that are different to the original purpose of the data collection exercise without the need for people’s consent. Data repurposing is likely to breach data privacy laws and have an impact of citizens’ life.
Data management should determine the extent and details of data control. While it is essential to prevent vulnerabilities, excessive control might undermine the usefulness and efficiency of data. Many factors may determine the relative benefits and loss of (loosening) control, such as domain characteristics, perceptions of the types of data (personal/impersonal), and technologies and tools used (van Zoonen, 2016[121]). The UK National Data Strategy acknowledges the risks of using data. When data are misused, it could harm people or communities, nurturing people’s mistrust. Equally, misplaced government reluctance to securely share and use data undermines the performance of public services and risks causing harm by missing opportunities to help those most in need. Moreover, unnecessary barriers to technological innovation could drive inefficiencies and slow down growth (UK Government, 2020[122]).
The relative benefits and losses are also affected by situational factors. For example, the COVID-19 crisis has become a catalyst for loosening control of privacy for public interests. Many countries, including Australia and the United Kingdom, have initiated data-sharing practices between different departments of the public sector as well as between the public and private sectors to curb the spread of the disease (Hickman, Pierson and Comstock, 2021[123]). While the UK government has shared data from the National Health Service with technology companies to develop a COVID-19 database, in Australia, the New South Wales government has analysed the impact of the pandemic and benefitted from anonymised transaction data provided by a bank. Some countries have adopted trusted third-party systems that make decisions regarding the opening/closing of data on a case-by-case basis, rather than setting up a universal rule (Delcroix, 2017[124]). While this method can increase flexibility and maximise benefits, it may raise other concerns, such as who should constitute the party and where the party should be positioned within the hierarchy of decision-making entities (von Grafenstein, Wernick and Olk, 2019[110]).
Data governance also concerns data protection from rule violations and cyberattacks. The European Union implemented the GDPR, which entails severe penalties for data breaches – fines of up to 4% of annual revenue.31 As a result, major companies such as British Airways, Google, H&M and Marriott were charged massive fines for personal data violations. For example, in Japan, the handling of personal information in smart city projects must comply with the 2003 Act on the Protection of Personal Information (APPI) (Government of Japan, 2003[125]) and other laws.
Each domain of smart cities has different cybersecurity concerns. For instance, Ma (2021[126]) has identified security-related challenges of smart buildings, which include concerns related to smart meter functions or vulnerabilities found in the process of communicating with smart grids, such as changing or repeating consumption messages. Other than domain-specific concerns, cybersecurity challenges derive from the integrative and communicative characteristics of smart cities. In other words, integration/communication between the physical and cyber worlds, between old and new systems/platforms, across various domains entails vulnerable intersections (Pandey et al., 2019[127]).
The lack of digital skills and capacity for data management at the national and local levels weakens data governance in smart cities
The shift to a digital society requires an increase in the capacity to use and manage data. More generally, public and private sectors’ digital skills (i.e. the ability to find, evaluate, use and create content and value using digital devices),32 capacity, talent and knowledge are core elements of good data governance and of broader public sector reforms, including digitalisation and fostering innovation. National and local governments need to ensure data literacy in relation to urban development as one of the required staff capabilities (BBSR, 2021[128]). Developing a digitally savvy public workforce requires a cultural change supported by a holistic strategy that encourages a more flexible and adaptable working environment; enables staff to adopt a more proactive approach to change and identifies and develops the necessary talent and skills needed for the proper functioning of the public sector (OECD, 2021[129]). The recruitment of data-savvy staff should be a key part of cities’ recruitment and training strategies.
In countries like Brazil, Colombia, Estonia, India, Japan and the United Kingdom, a key problem in enhancing digitalisation and data management has been the lack of access to skilled, qualified experts in data management and analytics, particularly in small local governments. A part of the problem is competition with the private sector: people who are highly trained in data and technology may prefer to work there (i.e. banking, retail, etc.) for the more competitive salaries. The public sector, thus, must compete to access those skills.
In some countries, there is also an insufficient supply of smart city architects or experts. Cities need professionals who work as producers and co-ordinators of smart city development and have knowledge of digital technologies, regulation, business models and local government affairs (Valtasaari, 2022[130]). The lack of such professionals is preventing cities from guiding the development and management of smart city projects. Smart city architects should work with urban planners in close co-operation with subject matter experts, citizens and national and city authorities. In countries like Colombia, Japan, Mexico and many others, there is a lack of institutions that train and form a wider pool of smart city (data) experts and allow the creation of networks that help secure enough professionals for the future. In India, for example, cities did not invest in building the capacity of the different stakeholders to engage with the data flows generated by project infrastructure, diminishing the impact of the data (Bajpai and Biberman, 2021[88]). Bridging the capacity gaps would require setting up collaboration frameworks among cities and, in some cases, support from the national government would be needed.
According to estimates of the European Commission for 2019, the number of data professionals in the member countries of the European Union (EU27) plus the United Kingdom reached 76 million (3.6% of the total workforce), an increase of 5.5% over the previous year. However, there is an imbalance between the demand and supply of data skills, with a data skills gap of 459 000 unfilled positions in the EU27 plus the United Kingdom, which amounts to 5.7% of total demand (EC, 2020[131]).
Digital skills are critical for enabling economic growth across all sectors of the national and local economies, not only the ICT sector. The lack of access to a workforce with the necessary digital skills is a problem for both the public and private sectors. In the United Kingdom, for example, 23% of employers consider their workforce lacking basic digital skills and 37% say they lack advanced digital skills (WorldSkills UK, n.d.[132]). In the public sector, the UK government estimates that 90% of senior civil servants need to be upskilled in digital and data essentials as the government lacks the digital skills to support digital transformation (Aldane, 2022[133]). In Japan, there are around 1 700 local governments of different sizes in the country and the small ones in particular do not have access to skilled specialists in data management. In large cities like Tokyo, the smart city industry provides large amounts of data that can be used by the numerous businesses installed in the metropolitan area. However, in smaller municipalities with shrinking populations, there are no businesses that could make use of data published by local governments. Access to technology is not necessarily a challenge for Japanese local governments but access to specialists is. According to the IMD World Digital Competitiveness report (IMD, 2022[134]), Japan has a low rate of digital talent (those who master technologies and transformation expertise), with only 1% of the workforce with adequate skills. And this limited digitalisation is also reflected in the digital maturity of the government, as Tokyo, for example, ranked only 84 in the IMD Smart City ranking in 2021 and the digital adoption rate is only 7.5% (Broeckaert, 2022[135]).
The OECD (2019[136]) has concluded that the lack of data-related skills is a challenge across all policy sectors and may prevent the effective reuse of data, even if made available via open access. While data skills refer to the full range of basic, technical, governance and other skills needed by practitioners to maximise the usefulness of data, technical skills range from programming, data visualisation, analysis and database management to core skills such as problem solving, project management and communication.33 Investing in digital and data skills is more important than ever to build resilient and inclusive smart cities as well as to provide public and private organisations with the right workforce to adjust to an ever-changing world. Different actions have been taken to diagnose the problem and suggest solutions, for example:
In Japan, a critical element of the Data Strategy is the human resource management aspect in all elements of the architecture to ensure capacity. Thus, Japan’s strategy aims to develop the digital human “resoudigital” (resource and digital) transformation of local companies and industries, and ensure that all staff in government (national and local) have the fundamental digital skills and that there are sufficient professionals to analyse data and design.
In New Zealand, the government requires skills for digital leadership, data analysis, cybersecurity specialists and architects (New Zealand Digital Skills Forum, 2018[137]). In 2017, the New Zealand Digital Skills Forum conducted a survey to understand the demand for digital skills in the public and private sectors. The results showed that both the public and private sectors underinvest in the development of digital skills of their staff due to the perceived available time and the difficulty of prioritising training above business-as-usual activities (New Zealand Digital Skills Forum, 2018[137]; OECD, 2019[25]). Estimates suggest that there is a need to double digital leadership capacity across government in the short term and additional investments are needed in critical skills such as cybersecurity and service delivery.
Estonia’s Digital Agenda promotes innovation in the field of online governance, cybersecurity and information society; therefore, it includes actions and investments in the development of advanced ICT skills for the public sector and fosters digital literacy and lifelong learning for all citizens. The aim is to increase the ability of public sector institutions to capitalise on the benefits brought by innovative solutions in the ICT field.34 The main goal of Estonia’s Digital Agenda is to create a well‑functioning, safe and secure environment which has the capacity to develop and create the innovative ICT solutions that Estonian society and economy need (EC, 2021[138]). To this end, the strategy puts emphasis on the development of digital skills for all citizens and for ICT professionals (Box 1.17). This is of key relevance in a country where 99% of all government services are provided on line, 99% of the population has an electronic ID and 98% of medical prescriptions are issued digitally.35 The message from Estonia’s experience is that the government needs to focus not only on the skills of government officials but also on those of citizens who are the final intended beneficiaries of digital services. In addition, funding research and skills development of ICT professionals should be part of a national data strategy.
Box 1.17. Key actions for developing the digital skills of citizens and ICT professionals in Estonia
Actions for developing citizens’ digital skills:
Improving the quality of public services, together with user experience with the aim of facilitating access to public services and spread awareness of their advantage to build digital citizenship skills for everyone.
Increasing the ability of public sector institutions to capitalise on the benefits brought by innovative solutions in the ICT field.
Fostering lifelong learning and digital literacy and bridging the digital skills gap through increased awareness of ICT solutions’ impact on quality of life, well-being, use of public services and others.
Enhancing the uptake of digital identity and services amongst foreign nationals and expanding the national e-Residency programme.
Actions for developing the digital skills of ICT professionals:
Organising networking events and workshops as well as partnerships between IT managers and service providers to improve knowledge and co-operation.
Promoting the development of advanced digital skills in traditional sectors.
Developing and implementing sector-specific ICT strategies and allocating additional state funding for IT development.
Introducing measures to improve knowledge flows and skills transfer between mid- and top-level employees in the public and private sectors.
Supporting the management and implementation of ICT development projects through the national government’s guidance and quality requirements.
Increasing funding for research in the field of connectivity, 5G technology, AI, cybersecurity and big data.
Source: EC (2021[138]), Estonia - Digital Agenda for Estonia 2020, https://digital-skills-jobs.europa.eu/en/actions/national-initiatives/national-strategies/estonia-digital-agenda-estonia-2020.
London’s experience also suggests that one way of attracting talent and skills is to explain the social impact of working in certain roles in the public sector and to offer flexible working conditions such as teleworking. For skills in high demand, teleworking could be a particularly relevant solution as modelling and working with data can be done remotely.
Vienna’s biggest challenge to implement its data strategy is the lack of staff trained in data analysis, preventing a deep understanding of the potential of data in the administration and the usage of that data. For this reason, the city administration uses data visualisation to tell stories and show the potential use of data while offering simple tools and interfaces.
In Italy, the National Strategy for Digital Skills aims to bridge the digital divide that affects the entire population. It intends to do so by supporting digital inclusion and the development of e-skills through higher education and training cycles to increase the number of ICT specialists and ensure the working-age population has the basic digital skills to enter the job market (Box 1.18). Italy seeks to equip 70% of the population with at least basic digital skills, double the rate of people with advanced digital skills to reach 78% of young people with higher education, 40% of workers in the private sector and 50% of civil servants, and increase fivefold the share of the population using public digital services to reach 64% by 2025 (Jakobsone, 2022[139]).
Box 1.18. Italy’s National Strategy for Digital Skills
In Italy, the National Strategy for Digital Skills has been drafted jointly with the collaboration of ministries, regions, provinces, municipalities, universities, research institutes, companies, professionals, the national public broadcasting company and several public sector organisations.
The strategy identifies four lines of intervention:
Higher education and training – for the development of e-skills for young people within the mandatory education cycles.
Active workforce – to ensure adequate e-skills in both the private and public sectors, including e-leadership skills.
ICT specialist skills – to enhance the country’s ability to develop skills for new markets and new jobs, with a specific focus on emerging technologies and key competencies for future jobs.
Citizens – to develop the digital skills needed to exercise citizenship rights and promote active participation in democratic life.
For each line of intervention, there are associated priorities and 41 lines of action through 111 actions. A dashboard of over 60 indicators monitors the impact of the 4 lines of intervention. Each action also includes appropriate milestones, result indicators and target values.
Source: Jakobsone, M. (2022[139]), Italy – National Strategy for Digital Skills, https://digital-skills-jobs.europa.eu/en/actions/national-initiatives/national-strategies/italy-national-strategy-digital-skills.
India’s DataSmart Cities strategy calls for building an ecosystem with a more capable city government, aware and engaged citizens as well as collectives of non-state actors to continue building mutual trust and collaborating to seek solutions to challenges associated with data. In India, the implementation of the DataSmart Cities strategy requires regular capacity building for data officers at all levels, such as city data officers, data champions and co‑ordinators and members of the City Data Alliance (Table 1.7). The 2021 Salesforce-YouGov survey on digital skills in India found that 93% of managers in public and private sectors considered that the COVID-19 pandemic accelerated the need for digital skills in their organisations and that the skills in the most demand were in digital marketing (48%), social media (47%) and data analytics (37%) (Salesforce YouGov, 2021[140]). India’s strategy suggests that capacity building for local government officers needs to be done in a peer-to-peer manner, where various stakeholders of the data ecosystem can collaborate, exchange data and learn. A 360-degree capacity-building mechanism needs to be put in place to ensure a learning system where a wide range of stakeholders can benefit from the content and strategies created in one place. India is using its National Urban Learning Platform (NULP), which can create a resource-rich ecosystem of learning and knowledge sharing for city managers and primary stakeholders in the national data ecosystem. The aim is to facilitate information exchange and collaboration between city administration, professionals, industry, academia, researchers and start-ups striving to solve data challenges with state-of-the-art technologies. The key aspects of this strategy are to ensure that training is tailored to local needs, content is agreed upon through a discussion process, the use of online tools and a certification of new skills acquired.
Table 1.7. Capacity-building features of data officers in India
Source: Based on Government of India (n.d.[141]), DataSmart Cities: Empowering Cities Through Data, https://smartcities.data.gov.in/sites/default/files/DataSmart_Cities_Strategy_Print.pdf.
The OECD (2021[129]) has developed a framework that proposes a series of pathways for developing a digital public workforce and supporting digital transformation in the public sector (Box 1.19). City governments could apply the actions suggested in this framework to guide their policies and strategies to acquire and develop the digital skills and competencies needed to design and implement smart city projects and enhance their data management strategies.
Box 1.19. The OECD framework for digital talent and skills in the public sector
Acquiring, developing and retaining the digital talent and skills needed for digital transformation in the public sector requires leaders and organisations to take action in three main areas:
Building the right environment by:
Being aware of the workforce’s digital skills requirements to keep pace with digital evolution.
Communicating a clear and understandable vision of the role of digital and the benefits of digital government.
Endorsing and actively participating in the rhythm of digital delivery, reducing hierarchical layers and delegating decision making.
Focusing on digital professions that are user-centred and have specific objectives and roles.
Developing a culture of learning that encourages and provides safety for employees to experiment.
Establishing the skills for a digitally enabled state by:
Developing a broader digital skills strategy for society as a whole.
Equipping public servants with the digital user skills that support digital government maturity.
Setting diverse and multidisciplinary teams consisting of well-trained digital and non-digital professionals to design and deliver services with user needs in mind.
Ensuring leaders actively shape the environment to create a digitally enabled state.
Creating a path to a digital workforce by:
Implementing proactive recruitment strategies promoting the public sector as an attractive and transparent employer.
Developing and implementing fair, trusted and attractive reward systems that support clear career planning.
Ensuring that managers promote multidisciplinary teams to promote job growth and professional development.
Offering regular feedback loops and mentoring programmes, and providing training through formal and informal mechanisms.
Ensuring job mobility is encouraged and public servants are offered a diversity of career choices.
Source: OECD (2021[129]), “The OECD Framework for digital talent and skills in the public sector”, https://doi.org/10.1787/4e7c3f58-en.
SMEs have limited participation in smart city projects and data governance
Although SMEs constitute the backbone of the economy (they account for 60% of total employment and 50-60% of the national value-added),36 their participation in smart city projects is still limited. Improving data governance arrangements could potentially help SMEs to scale up (OECD, 2022[142]). Governance arrangements that provide SMEs access to and facilitate the use of data and data-related technologies and skills could increase their capacity to innovate and their possibilities to scale up by achieving greater cost-efficiency. Innovative funding mechanisms for SMEs and start-ups are needed as well as training in data management. For cities to be better managed and more liveable for citizens, national and subnational governments and SMEs need to work together to develop smart cities. Governments have been implementing different strategies to support SMEs in the transition to the digital era (Box 1.20) (OECD, 2021[143]).
However, this transition is taking place at different speeds depending on the sector and size of the firms. Outdated data infrastructures, data silos and management practices that are not conducive to innovation are some of the barriers SMEs face in a data-driven economy (OECD, 2022[142]). Moreover, not all SMEs have the capacity to shift to digital services, particularly smaller ones, and they are more likely to limit their work to basic services. Certainly, the COVID-19 crisis heightened the importance of SME digitalisation and served as an accelerator, as firms had to move operations on line rapidly and implement smart working solutions during lockdowns to remain in business. OECD research has found that although countries are placing a stronger focus on reinforcing SMEs’ internal capacity to use data (72% of 487 mapped policies), less attention is given to enabling SMEs access to external data (28% of mapped policies) through data‑sharing infrastructure (OECD, 2022[142]).
Box 1.20. Governments’ actions to support SMEs’ digital uptake – Country examples
In 2020, the Australian government announced a package of AUD 800 million to update the regulatory framework to boost the capability of small businesses and back the uptake of technology across the economy.
In Canada, the government initiated the Go Digital Canada initiative in co-operation with Shopify to help small business sales grow on line through free training courses and the use of digital marketing channels.
In 2020, the French government earmarked EUR 100 million to support small businesses in building up on line operations. The government platform FranceNum, intended to connect SMEs willing to digitalise with a network of specialised consultants, became a platform for live information on support initiatives from national and local governments and the private sector.
In Ireland, authorities implemented the digital Trading Online Voucher Scheme for a total of EUR 3.3 million (USD 4 million). Micro enterprises can get a EUR 2 500 voucher for online training.
The New Zealand government created a “revive and thrive” tool accessible from its business.govt.nz platform to give businesses access to tailored support and information on how to do commerce digitally.
In Slovenia, the government supports SMEs through the Digitalisation and Digital Transformation Programme, which provides vouchers of up to EUR 10 000 for strategy formation, digital marketing development, enhancing digital competencies or digital security development.
In Türkiye, the Small and Medium Enterprises Development Organisation (KOSGEB) has focused on the digitalisation of SMEs in the manufacturing industry. Projects aim to help SMEs in the sector adapt their production and business processes to digital technologies, such as data mining, the IoT, AI, etc. USD 38 million were provided to SMEs.
Source: OECD (2021[144]), OECD SME and Entrepreneurship Outlook 2021, https://doi.org/10.1787/97a5bbfe-en.
The emergence of smart cities means an exponential production of data, which involves considerable political, economic, commercial and technological stakes. The enormous production of data offers large companies and SMEs opportunities to better understand markets, competitors and clients. Although data can offer clear benefits for SMEs, not all of them produce data nor have the capacity to benefit from data as they lack the skills to conduct data analytics, for example. Moreover, it is still unclear to what extent SMEs are the leading actors of smart city projects. Preliminary findings suggest their role is limited but more research is needed. The COVID-19 crisis showed that most SMEs are agile, flexible and adaptable, as they can change rapidly depending on the circumstances. However, they lack the resources to initiate smart city projects and there are few examples where SMEs are part of the partnerships between governments and large corporations in the development of smart city projects. In particular, although SMEs can exploit big data, the difficulty lies in the capacity of knowing which data to exploit and the expertise to turn it into a competitive advantage (Rochdane and Hamdani, 2018[145]). Investing in human capital in SMEs will therefore be a key component in the transition to smart urban development and effective data governance and management.
Managing smart data involves technical challenges for cities
Smart city projects allow for collecting and utilising large amounts of real-time data for decision-making processes at the national and local government levels. This has potential benefits for cities and citizens as services and products can be tailored to specific needs. However, although the collection of different types of data from heterogeneous sources provides a more accurate profile of the city (or parts of it), this creates problems in collecting, standardising and storing large amounts of data.
Collecting smart data is a complex process in itself due to the multiple sources with different formats and types and different usages and access policies (Al Nuaimi et al., 2015[111]). The unstructured nature of data makes it difficult to categorise and organise it in a way accessible for stakeholders to use. For example, collecting data on traffic flows requires including smart traffic lights and signals as a part of a smart city project. Analysis of data should take into consideration different factors, such as the city map, cars and smart signals as well as the distribution of the sensor and traffic light network.
Technical challenges in managing big data in smart cities are related to the volume, variety, velocity, variability and value of data (Al Nuaimi et al., 2015[111]). The emergence and use of cloud computing, IoT and location-based services has led to the challenge of storing large amounts of real-time data (Zheng et al., 2015[146]). Research suggests that there is no easy solution for smart cities to process mass quantities of sensor data as the infrastructure is not yet ready for increasing data at an accelerated rate (Schafroth, 2018[147]). There is no efficient model to stream data, as multiple systems that are not interconnected make it difficult to process and manage databases. Moreover, data collected from different sources, such as smartphones, computers, sensors, cameras, etc., may create a problem of heterogeneous data that are not interoperable. Moreover, knowledge about data quality, applications, scaling up and commercialisation possibilities are very limited across many cities and among stakeholders, and the knowledge on how to use data remains theoretical as practical experience often lags.
Ensuring the quality of data is a fundamental aspect of big data management and a challenge for smart cities. Data are captured by different agents through different sources under special regimes and stored in distinctive databases but without standard formats. Thus, relying on crowdsourcing and collaboration of multiple data providers may result in data that lacks structure and consistency, with high levels of disparity and heterogeneity (Al Nuaimi et al., 2015[111]). This is why earlier research warned that “[w]ithout a new generation of sensor data management platforms […] the adoption and benefits of the smart city will be substantially reduced. Particularly as challenges in collaboration and data heterogeneity breed an increasingly fragmented patchwork of systems and data unable to exploit the benefits of multi-resolution and multiscale data analysis compounded by the inherent disparity of data, its uncertainty and potential untrustworthiness” (Lee et al., 2013, pp. 101-102[148]).
Big data applications for smart cities require large processing capability to perform data analytics. For this purpose, cities need scalable and reliable software and hardware platforms. The challenge is to ensure access to software platforms that offer high-performance computing capabilities, that are optimised for the hardware being used, are stable and reliable for the different data-intensive applications and are supported by well-trained and capable civil servants and personnel from partnering agencies.
Collecting and storing data not only represent a technical problem but a financial one. For example, acquiring the technology to monitor energy use may force governments to use new systems, components or applications to monitor and record information, which may be costly. Moreover, if a project has not been implemented correctly from the beginning, even when devices to collect, share and store data may be affordable, this may result in very high costs and the image of the city and stakeholders being affected negatively.
Caveats on smart city data governance from international experience
The use of (digital) technology has its limits
In countries such as the United States, there has been some resistance to the use of smart city solutions. The use of biometrics, particularly facial recognition and 5G cell towers, has come under scrutiny in some cities due to concerns about privacy and law enforcement. For example, San Francisco banned the use of facial recognition technology due to concerns about potential abuse by the police and other agencies (Raval, 2019[149]).37 Oakland (California) and Sommerville (Massachusetts) have also issued similar legislation38 and other cities, such as Cambridge (Massachusetts), are considering similar moves. Civic leaders are also seeing escalating fears about AI because of its potential impact on jobs and data security, and since it may open their cities to cyberattacks. The takeaway from the United States experience is that local governments have a duty to set standards for new and upcoming surveillance technology on how to use it. National and local governments may need to decide on whether to add people’s images to the facial recognition databases with or without their knowledge and consent, for example. However, even providing detailed information on how personal data would be collected, there could be opposition. For example, the city of San Diego installed 3 200 intelligent sensors on streetlights that generate data to help with easing congestion, parking, public safety and environmental monitoring, among other benefits.39 The local government detailed information on how the data gathered would be collected and used and the benefits it would produce for the city and its residents; but still, there has been considerable resistance from some residents.
Smart city projects should not merely focus on what technology can do but respond to identified social needs
With the emphasis on controlling and optimising every aspect of city life through technology, smart cities may be damaging city life. Research suggests that smart city projects should concentrate on priorities such as shortening commuting times, speeding up the construction of affordable housing, improving the efficiency of public transport and reducing carbon emissions (Jacobs, 2022[103]). The lesson from Toronto’s Quayside project (Box 1.14) is that, although smart city projects are sometimes widely consulted with stakeholders, their solutions largely focus on what technology can do, when they should actually focus on how technology will respond to people’s needs and produce benefits. This is why Japan’s SCRA has adopted a human-centred approach. By leveraging technology and the services it enables, Japan seeks to satisfy the needs of an ageing and shrinking population.
Smart city projects should take into account the concerns of the local service industry
This is particularly the case in smaller cities where local businesses may fear being taken over by large corporations. Some central city areas are declining due to the disappearance of SMEs because of the expansion of large corporations. The protection and development of local commerce and industry should be part of a smart city project as an effort to contribute to regional revitalisation.
Smart city projects require an efficient communication strategy
Gaps in communication could potentially backfire in a smart city project, regardless of its thoroughness. The experience of Toronto’s Quayside project in Canada shows how poor communication management could put an end to a smart city project (Box 1.14). The resistance to the Sidewalk Labs project in Toronto shows that residents may be sceptical about the involvement of large private companies in urban projects and express significant concerns about the government handing over significant amounts of money or resources to them to control the governance of public life. This could be a warning for other countries as large private companies are involved in several smart city projects, mostly as residents are wary about how city governments and large-scale technology companies involved in the projects will manage the data they collect on their daily activities.
Cities strive to be hyperconnected rather than just smart
To unlock the full economic, social, environmental and business value from technology, cities need to leverage technology to transform and securely interconnect key areas of their urban ecosystems: technology, data and analytics, cybersecurity and citizens (ESI ThoughtLab, 2022[150]). This means using the latest technologies to connect key areas from roads to cars, buildings to energy grids, citizens to government and cities to cities. A hyperconnected city facilitates real-time interaction among residents, businesses and government entities and services. An example is the city of Stockholm, Sweden, which has launched a strategy for a smart and connected city (City of Stockholm, 2017[151]). Based on its accumulated experience and in order to stimulate, guide and co-ordinate different digitalisation projects, the city of Stockholm has issued a strategy to become smart and connected (Box 1.21). However, to be hyperconnected, all new investments in the city must be based on the needs of residents and visitors, drawing on a wide variety of data to provide value to different stakeholders. This includes traditional data gathered from city departments, local businesses and citizen surveys to new types of data from IoT, AI and social media. The experience of Stockholm suggests that data and technology should work in parallel and build synergies.
Box 1.21. Stockholm’s strategy to become a smart and connected city
In 2017, the City Council of Stockholm adopted a strategy to transform Stockholm into a smart and connected city developed in collaboration with public employees, residents, businesses and academia. The aim of the strategy is to provide residents with the highest quality of life and build the best entrepreneurial climate. To achieve these objectives, the strategy aims to foster innovative solutions, transparency and connectivity. The strategy mainly focuses on the opportunities that arise from areas such as the IoT, big data and analysis. The smart city is made possible through connectivity and open data, integrated platforms, sensors and other technologies. The strategy concentrates on Stockholm as a physical place rather than the organisation of the city of Stockholm.
The strategy defines enabling factors divided into three main areas: operations, technology (including applications and services, digital platforms and IT infrastructure, information security and privacy) and principles for cost distribution. To guide the technology that enables the smart city, the strategy contemplates seven strategic enabling principles:
Solutions are built on common digital platforms.
Systems exchange data through central platforms.
Technical solutions are based on open standards.
Technical solutions are built modularly.
Agreements enable development and innovation.
Security and privacy protection is ensured.
Data are made available internally and externally as open data.
The implementation of the strategy consists of three main angles: co-ordination and collaboration (internally and externally), communication (and dialogue with residents), and prioritised projects. To guide and co-ordinate the implementation of the strategy, the city developed eight principles for implementation:
Initiatives are based on the needs of citizens.
Development builds on what is already in progress.
Prioritising is done in line with the target picture.
Development is done through internal and external collaboration.
Long-term perspective permeates all investments.
Information is collected with regard to others.
Digitisation is included in urban planning processes.
Change is driven by internal and external communication.
Source: City of Stockholm (2017[151]), Strategy for Stockholm as a Smart and Connected City - Summary, https://international.stockholm.se/globalassets/ovriga-bilder-och-filer/smart-city/summary-of-the-strategy-for-stockholm-as-a-smart-and-connected-city.pdf.
Building and deploying successful big data applications will require addressing such challenges, having well-trained human resources and being well prepared and supported by the governing entities. With all success factors in place and a better understanding of their limitations, making a city smart through the use of data will be a sustainable goal.
Annex 1.A. Towards data-enabled smart cities in Japan
Japan’s policy framework for smart cities
To guide the development of smart city initiatives across Japan and share the accumulated experience of existing initiatives, the Japanese government formulated the Smart City Reference Architecture (SCRA), which is a standard design framework of smart cities and the basic components they should have. The SCRA systematically organises the components of a smart city for it to contribute to resolving regional issues. In this sense, it enables the efficient construction of smart cities in each region based on standardised methods and rules.
The SCRA aims to ensure interoperability between the wide range of components that are expected to make up smart cities and facilitate the design of smart cities by researchers, industry professionals and city planners. The SCRA is built under four basic concepts considered indispensable for promoting smart cities in Japan:
User-oriented principle, by which all stakeholders involved in a smart city project must be aware of the users (residents, visitors and businesses) of the services provided through the initiative.
Role of city management refers to the overall and comprehensive management of the smart city project under holistic and comprehensive management. It states the need to maintain sustainable management of smart cities and develop citywide governance and management mechanisms.
Role of the city OS, which states that data and services must be federated efficiently.
Interoperability refers to the need to ensure interoperability with other regions and systems to make the development of smart cities more efficient throughout the country and ensure that data are shared seamlessly across regions.
According to the reference architecture, smart cities should have the following six foundational components:
Smart city strategy. This describes the roadmap of how each region or city achieves its goals. Developing a strategy is mandatory and should present the key challenges faced in the city or region and set high-level goals. It should be based on a quantitative assessment in the form of key goal indicators (KGIs) and key performance indicators (KPIs).
Smart city rules. Regulations on smart cities should include issues on privacy prevention as well as data utilisation. Region-specific rules are considered important in governing and managing region-specific services and regional collaboration councils.
City management. Smart cities should be managed through a collaborative organisation composed of a wide number of stakeholders, thus enabling the sustainable management of the smart city that defines who does what. There should be a business management model led by a regional consortium composed of public and private sector stakeholders.
Smart city service. This refers to what is provided to users by federating and/or integrating data and other services via the city OS. There should be clarity on the services to be deployed as part of the smart city initiative and that respond to the local needs.
City OS. This is a set of system functionalities that enable access to a variety of data provided by smart city assets as well as external systems. It should be characterised by interoperability (connect), data exchange (flow) and scalability (future-proof).
Smart city assets. These refer to the property and resources of the city, which could be converted into data required to solve issues and controlled via the city OS.
Japan aims to build data-enabled cities
Japan’s national vision is for a data-driven, human-centric, next-generation society that uses AI, big data and IoT. Society 5.0 provides the foundations to use technology to enhance social cohesion. Japan aims to build smart (super) cities around an information co-ordination platform, which is expected to allow all citizens and businesses to participate in urban life. The platform will collect and manage all kinds of urban data, taking into account citizens’ perspectives and providing complex and personalised services while ensuring data interoperability and distribution capability that can be extended to other cities.40 The data-driven smart cities that Japan is working on involve a bottom-up approach achieved by integrating digital transformation (DX) that is underway in various policy fields while ensuring privacy and security.
Japan bases the building of data-driven smart cities on three pillars:
Eco-cities, environmentally symbiotic cities which focus on low carbon, resource recycling and reduction of environmental burden.
Transit-oriented development (TOD) aims to reduce traffic congestion and upgrade urban functions through urban development with a focus on public transport.
Building disaster-resilient cities (disaster prevention) focuses on using technology for predicting and preventing disasters, building warning systems and using technology to minimise disaster damage in urban development.
The difference between a “smart city” and a “super city” is that, in the former, the data combination will gradually change to a data linkage platform, while in the latter, the development of a cross-disciplinary data linkage platform is made all at once.41 A super city covers at least five of these areas: mobility, logistics, payment, administration, healthcare and nursing care, education, energy and water, environment and refuse collection, crime prevention and disaster prevention and safety. The Society 5.0 initiative and a data-driven society aim to create super smart cities by integrating cyberspace and physical space through the maximum use of ICT while tackling economic and social problems through a human-centred approach. In a super smart city, data linkage platforms will promote data connection services between multiple fields (Annex Figure 1.A.1).
Japan and other OECD countries are now entering into a new “smart” society of sustainable and inclusive socio‑economic systems that are powered by big data analytics, AI, IoT and robotics, where digital and physical spaces are tightly integrated. In this context, data take a central role as they could optimise entire societal and welfare systems to improve their quality of life by meeting people’s needs at the time and place required, tailored to their particular needs. For Japanese authorities, smart city data refer to data from residents, public administration and service providers, among others, obtained from various IoT sensors via the network and include metadata, static data, dynamic data, geospatial data and personal data.
Japanese smart cities produce large amounts of data through the use of IoT. The central government is encouraging cities to use data to move towards Society 5.0 as trade, industrial production and societal functions depend more than ever on efficient access to data. OECD research has found that life satisfaction is positively linked to cities where stakeholders and residents are engaged in data collection and openly share their data (OECD, 2021[30]). However, not all city governments know how to or have the capability to transform data into inputs for decision making and, subsequently, into benefits for residents. This is an issue that has to be addressed as tackling challenges such as pandemics and ageing societies requires open and trusted data flows for societies (WEF, 2020[2]).
Annex Figure 1.A.1. “Super city” according to Japan’s National Strategic Special Zones system
Source: Government of Japan (n.d.[152]), Japan’s Smart Cities: Solving Global Issues Such as the SDGs, etc. through Japan’s Society 5.0, https://www.kantei.go.jp/jp/singi/keikyou/pdf/Japan%27s_Smart_Cities-1(Main_Report).pdf.
Data utilisation within a city is expected to: facilitate the optimal management of energy, water supply and sewerage and recycling within cities; build a cashless society; provide transport services anywhere and at any time; improve e-learning and long-distance education; enhance safety and security; extend healthy life expectancy; and ensure a prompt evacuation from and restoration of disaster zones by providing information in real time (Japanese Cabinet Office, 2022[50]). Cities like Aizuwakamatsu, Takamatsu, and Toyama have been working on projects to use IoT tools as part of their smart city projects to enhance disaster prevention, boost tourism and improve welfare and well-being. The city of Tsukuba is accelerating online medical services in collaboration with various start-ups.
In the case of Japan and several other OECD countries like Korea, Poland and Spain, data reuse and sharing among government entities across different levels of government can tackle an ageing society and public health challenges with more accurate preventive care, mitigating increasing costs. Data flows can help address pollution, climate change and other sustainability objectives by minimising waste and increasing traceability across sustainable supply chains (WEF, 2020[2]). Data are another critical element for enabling the delivery and tracking progress in achieving the United Nations Sustainable Development Goals.
Japan is promoting a human‑centric approach to smart cities and data governance to manage the challenges brought about by digitalisation and data. These challenges are related to the use of digital technologies and may create or exacerbate digital gaps in society. For example, some residents may not have the digital skills to use the technological gadgets that are needed to access and benefit from these services.
Super cities are the next generation of smart cities in Japan
While Japanese cities are managing their transformation into smart cities, the central government has assumed a leading role to accelerate and co-ordinate the development of smart cities across the country. This is a welcome development because in the development of smart cities, even the most capable cities in the country, such as larger metropolitan areas, face challenges that they are not able to overcome on their own. For example, cities rely on central government funding to cover part of the whole of infrastructure projects, they are not equipped to develop interoperable systems to share data across their jurisdictional boundaries and they lack the resources to fund R&D for smart cities. Cities are responsible for making the main decisions and investments that lead to their smart city transformation. However, the central government, through the Ministry of Land, Infrastructure, Transport and Tourism and the newly created Digital Agency, has a role in addressing the problems cities cannot tackle on their own, provide a co‑ordinated approach to the development of smart cities across the country and make the most of available resources. Moreover, the central government’s participation in smart city projects would provide policy certainty that may incentivise more private sector participation.
In 2013, the government enacted the National Strategic Special Zones Act to establish the National Strategic Special Zones, where regulatory reforms and other measures such as tax incentives were promoted for projects carried out jointly by the central and local governments as well as the private sector with the aim of enhancing economic growth. In June 2020, Japan’s government enacted the Act to Amend the National Strategic Special Zone Act, known as the Super City Act. The 2020 amendment enables governments to create another National Strategic Special Zone referred to as a super city. This new law aims to improve the collaboration between the public and private sectors for the digital transformation of cities. Cities selected as super cities will deploy AI and big data in medical care, education, energy, crime prevention and transportation, including the development and use of autonomous vehicles.
A super city is understood as a city that changes people’s way of life by utilising AI, IoT and big data, allowing the provision of cutting-edge services (e.g. autonomous cars, cashless payments, remote medical care and distance education) (Hiramoto, 2022[49]). To establish a super city, Japan requires broad regulatory changes to ease the challenges of dealing with multiple government agencies. The 2020 amendment introduced a top-down approach by which if a municipality wins residents’ approval for super city plans and applies to the central government, the national government can then direct agencies to make exceptions to the relevant regulations as needed. In super cities, data-linking platforms collect and organise various kinds of data from administrative organisations. The super city authorities appoint experts called “architects” to co‑ordinate services and technology in their localities. Their task will be to ensure that siloed agencies co‑operate and that systems are interoperable across different jurisdictions. A municipality that wishes to become a super city must organise discussion fora with private companies to discuss the super city development plans, draw up those plans and make applications to the National Strategic Special Zones Secretariat after obtaining approval from local residents.
Japan has very specific challenges that it seeks to address via smart city projects. While cities across the world are using smart city solutions to solve issues related to public safety, water and air quality, mobility and waste management, Japanese cities are mostly using smart city strategies to address the challenges of an ageing and shrinking population, the threat of natural disasters and the impact of COVID-19. If Japan fails to respond to these challenges, it may face economic contraction and problems in maintaining living standards and even infrastructure. Thus, national and local authorities are exploring the potential smart cities have to face those challenges. In this context, the Cabinet Office approved the Basic Policy on Economic and Fiscal Management and Reform 2021 (Grand Policies 2021), which proposes to build 100 diverse and sustainable smart cities by 2025 (Annex Box 1.A.1) (Government of Japan, 2021[153]).
Between 2017 and 2021, about 280 smart city demonstration projects were in approximately 170 geographic areas. Nowadays, almost 40 smart city pilot projects are being implemented across the country. For example, Aizuwakamatsu, a city with a population of 121 000 inhabitants, has a comprehensive smart city strategy through which it provides a wide variety of services in collaboration with several stakeholders. The city of Maebashi, with a population of over 340 000 inhabitants, uses smart city projects for evidence-based policy making on issues such as urban regeneration, healthcare and community activities. Kakogawa, with almost 260 000 inhabitants, has a smart city strategy for disaster and crime prevention and resilience as well as looking after the elderly and children (Ishida, 2021[154]).
Annex Box 1.A.1. Four driving forces for economic and fiscal management and reform 2021 in Japan
The Basic Policy on Economic and Fiscal Management and Reform 2021 sets out four driving forces of sustainable growth in the post-pandemic period:
Realisation of a green society to be achieved by stimulating private investment and innovation through a green growth strategy, promoting energy and resource policies toward decarbonisation and utilising carbon pricing that contribute to growth.
Acceleration of digitalisation by public and private sectors by establishing the digital government, fostering the acceleration of DX in the private sector and promoting the development of digital human resources, elimination of digital divide and cybersecurity measures.
Revitalising Japan as a whole through the creation of vibrant local regions by promoting the new flow of people to rural areas supporting the creation of dynamic mid-sized enterprises, SMEs microenterprises boosting economy through wage increases revitalising tourism turning agriculture, forestry fishery industries into growth industries including export growth, accelerating multicore co-operation based on smart cities.
Overcoming the declining birth rate and building a society that makes it easier to have and raise children by forging a society that enables marriage and raising children and creating an environment to ensure the security of children who will bear the future and measures against child abuse.
Source: Government of Japan (2021[153]) Basic Policy on Economic and Fiscal Management and Reform 2021, https://www5.cao.go.jp/keizai-shimon/kaigi/cabinet/2021/2021_basicpolicies_en.pdf (accessed on 27 June 2022).
Rural areas in Japan are more deeply affected by a shrinking and ageing population, deterioration of public transport and industries than cities; some of them are even at risk of disappearing. Thus, those places are considered to need more smart city projects than large cities but authorities in many of those localities consider smart city initiatives to be only for large urban areas (Ishida, 2021[24]). In reality, many of the municipalities applying for support to become a super smart city are located outside metropolitan areas.
Investments in smart initiatives can be expected to continue rising in Japan and worldwide as public services, information and means of participation and cultural resources are digitalised. In the post‑pandemic period, investment in smart projects like smart grids, intelligent traffic management, autonomous vehicles, smart lighting, e-governance services and data-enabled public safety and security, are gaining momentum. Technologies like AI and big data will be in high demand to combat future pandemics and other threats like climate change, with growing opportunities for crowd analytics, open data dashboards and online city services. This is a similar trend followed across the world as cities are investing more in digital technology to provide key public services and boost economic activity. According to estimates, by 2025, smart cities’ spending on (digital) technology will reach USD 327 billion, 22.7% more than in 2019 (Valente, 2020[155]).
References
[111] Al Nuaimi, E. et al. (2015), “Applications of big data to smart cities”, Journal of Internet Services and Applications, Vol. 6/1, pp. 1-15, https://doi.org/10.1186/S13174-015-0041-5/FIGURES/3.
[133] Aldane, J. (2022), “UK government outlines skills challenges in digital transformation plan”, Global Government Forum, https://www.globalgovernmentforum.com/uk-government-admits-lack-of-digital-skills-holds-back-transformation-as-it-sets-out-reform-plan/ (accessed on 3 October 2022).
[55] Argentinian Government (n.d.), Servicios y País Digital, https://www.argentina.gob.ar/jefatura/innovacion-publica/servicios-y-pais-digital.
[56] Australian Government (2016), Smart Cities Plan, https://www.infrastructure.gov.au/sites/default/files/migrated/cities/smart-cities/plan/files/Smart_Cities_Plan.pdf.
[88] Bajpai, N. and J. Biberman (2021), “India’s Smart City program: Challenges and opportunities”, ICT India Working Paper, No. 62, Center for Sustainable Development, Columbia University, https://csd.columbia.edu/sites/default/files/content/docs/ICT%20India/Papers/ICT_India_Working_Paper_62.pdf (accessed on 1 February 2023).
[128] BBSR (2021), Data Strategies for Common Good-oriented Urban Development, Federal Institute for Research on Building, Urban Affairs and Spatial Development, https://www.smart-city-dialog.de/wp-content/uploads/2021/12/data-strategies-common-urban-development-dl-1.pdf (accessed on 9 May 2023).
[73] BIS (2019), Smart Cities - Data Exchange Framework: Part 1 Reference Architecture, Bureau of Indian Standards, https://iudx.org.in/portfolio/smart-cities-data-exchange-framework-part1-reference-achitecture/ (accessed on 16 January 2023).
[107] Bodrum Living Lab (n.d.), Homepage, https://bodrumlivinglab.com/en/home/ (accessed on 8 December 2022).
[7] BrighterAI (2023), How Video Data in Smart Cities Plays a Pivotal Role in Safeguarding the Welfare of Citizens, Brighter AI, Berlin, https://brighter.ai/ (accessed on 3 May 2023).
[135] Broeckaert, L. (2022), Digital Transformation in Japan - Assessing Business Opportunities for EU SMEs, MINERVA EU-Japan, EU Japan Centre for Industrial Cooperation, https://www.eu-japan.eu/sites/default/files/publications/docs/Digital-Transformation-Japan-Assessing-opportunities-forEU-SMEs.pdf (accessed on 3 October 2022).
[72] BSI (2022), PAS 181 – Smart Cities Framework Guidance, British Standards Institution, https://www.bsigroup.com/en-GB/smart-cities/Smart-Cities-Standards-and-Publication/PAS-181-smart-cities-framework/ (accessed on 5 October 2022).
[20] BSI (2015), PD 8100:2015 Smart Cities Overview. Guide, British Standards Institution, https://knowledge.bsigroup.com/products/smart-cities-overview-guide/standard (accessed on 16 January 2023).
[81] BSI (2014), PAS 182 – Smart City Concept Model. Guidance to Establishing a Model for Data, British Standards Institution, https://www.bsigroup.com/en-GB/smart-cities/Smart-Cities-Standards-and-Publication/PAS-182-smart-cities-data-concept-model/ (accessed on 16 January 2023).
[80] BSI (2011), BS 8904:2011 Guidance for Community Sustainable Development, British Standards Institution, https://knowledge.bsigroup.com/products/guidance-for-community-sustainable-development/standard (accessed on 16 January 2023).
[42] Bundgaard, L. and S. Borrás (2021), “City-wide scale-up of smart city pilot projects: Governance conditions”, Technological Forecasting and Social Change, Vol. 172, p. 121014, https://doi.org/10.1016/J.TECHFORE.2021.121014.
[34] Businesswire (2021), “Data creation and replication will grow at a faster rate than installed storage capacity, according to the IDC global DataSphere and StorageSphere forecasts”, https://www.businesswire.com/news/home/20210324005175/en/Data-Creation-and-Replication-Will-Grow-at-a-Faster-Rate-Than-Installed-Storage-Capacity-According-to-the-IDC-Global-DataSphere-and-StorageSphere-Forecasts (accessed on 2 May 2023).
[116] Candelon, F. et al. (2020), “Simple governance for data ecosystems”, https://www.bcg.com/publications/2020/simple-governance-rules-for-data-ecosystems (accessed on 7 September 2022).
[100] Chawla, A. and J. Divij (2021), “Smart Cities in India: Of data governance and democratic deficits”, Bot Populi, https://botpopuli.net/smart-cities-in-india-of-data-governance-and-democratic-deficits/ (accessed on 1 February 2023).
[104] Chown Oved, M. (2019), “Google’s Sidewalk Labs plans massive expansion to waterfront vision”, Toronto Star, https://www.thestar.com/news/gta/2019/02/14/googles-sidewalk-labs-plans-massive-expansion-to-waterfront-vision.html (accessed on 4 July 2022).
[29] Chyi, N. and Y. Panfil (2020), “A commons approach to Smart City data governance: How Elinor Ostrom can make cities smarter”, New America, https://www.newamerica.org/future-land-housing/reports/can-elinor-ostrom-make-cities-smarter/ (accessed on 13 July 2022).
[1] Cisco (2020), Cisco Annual Internet Report (2018–2023) White Paper, Cisco, https://www.cisco.com/c/en/us/solutions/collateral/executive-perspectives/annual-internet-report/white-paper-c11-741490.html (accessed on 2 August 2022).
[108] Cité du Design (n.d.), Pôle Entreprises & innovation à destination des entreprises, https://www.citedudesign.com/archives/fr/entreprises/.
[14] City of Portland (2018), Establish a Priorities Framework for the City of Portland’s Smart City PDX Initiative, https://efiles.portlandoregon.gov/Record/12067443/.
[151] City of Stockholm (2017), Strategy for Stockholm as a Smart and Connected City - Summary, https://international.stockholm.se/globalassets/ovriga-bilder-och-filer/smart-city/summary-of-the-strategy-for-stockholm-as-a-smart-and-connected-city.pdf (accessed on 4 July 2022).
[115] CMS (2023), GDPR Enforcement Tracker - List of GDPR Fines, GDPR Enforcement Tracker, https://www.enforcementtracker.com/ (accessed on 3 May 2023).
[47] Copenhagen Connecting (n.d.), Copenhagen Smart City: The Challenge, https://www.almanac.in-jet.eu/downloads/M2M_Workshop_Presentations/Session%204/Mia_Copenhagen_smart_city_2015.pdf.
[36] COR (n.d.), Centro de Operações Rio, Centro de Operações Rio, https://cor.rio/ (accessed on 3 February 2023).
[113] Curzon, J., A. Almehmadi and K. El-Khatib (2019), “A survey of privacy enhancing technologies for smart cities”, Pervasive and Mobile Computing, Vol. 55, pp. 76-95, https://doi.org/10.1016/J.PMCJ.2019.03.001.
[41] De Pater, M. (2016), Energy Atlas, https://amsterdamsmartcity.com/updates/project/energy-atlas.
[124] Delcroix, G. (2017), “Smart Cities and innovative uses for personal data: Scenarios for using data to restore the balance between public and private spheres”, Journal of Field Actions 17, pp. 75-79, https://journals.openedition.org/factsreports/4489 (accessed on 28 July 2022).
[60] Digital Agency (n.d.), Homepage, https://www.digital.go.jp/en/ (accessed on 25 January 2022).
[69] Discover Amsterdam (n.d.), Amsterdam and Partners, https://www.iamsterdam.com/en/our-network/municipal-government/amsterdam-smart-city#:~:text=The%20aim%20of%20the%20Amsterdam,storage%2C%20connectivity%20and%20smart%20mobility.
[138] EC (2021), Estonia - Digital Agenda for Estonia 2020, Digital Skills & Jobs Platform, European Commission, https://digital-skills-jobs.europa.eu/en/actions/national-initiatives/national-strategies/estonia-digital-agenda-estonia-2020 (accessed on 10 August 2022).
[131] EC (2020), The European Data Market Monitoring Tool, European Commission, https://op.europa.eu/en/publication-detail/-/publication/9fb0599f-c18f-11ea-b3a4-01aa75ed71a1/language-en (accessed on 3 October 2022).
[150] ESI ThoughtLab (2022), Building a Hyperconnected City, https://econsultsolutions.com/wp-content/uploads/2019/11/ESITL_Building-a-Hyperconnected-City_Report.pdf (accessed on 4 July 2022).
[19] Fietkiewicz, K. and W. Stock (2015), “How “smart” are Japanese cities? An empirical investigation of infrastructures and governmental programs in Tokyo, Yokohama, Osaka, and Kyoto”, 48th Hawaii International Conference on System Sciences, https://doi.org/10.1109/HICSS.2015.282.
[87] Franke, J. and P. Gailhofer (2021), “Data governance and regulation for sustainable Smart Cities”, Frontiers in Sustainable Cities, Vol. 3, p. 148, https://doi.org/10.3389/FRSC.2021.763788/BIBTEX.
[93] Fujisawa SST (n.d.), About Fujisawa SST, https://fujisawasst.com/EN/project/.
[27] German Government (2020), The New Leipzig Charter: The Transformative Power of Cities for the Common Good, https://www.bmi.bund.de/SharedDocs/downloads/EN/eu-presidency/gemeinsame-erklaerungen/new-leipzig-charta-2020.pdf?__blob=publicationFile&v=8 (accessed on 2 May 2023).
[59] German Government (n.d.), “Smart Cities: Urban development in the digital age”, https://www.bmi.bund.de/EN/topics/building-housing/city-housing/national-urban-development/smart-cities-en/smart-cities-en-node.html.
[45] González Morales, L. and T. Orrell (n.d.), Data Interoperability: A Practitioner’s Guide to Joining Up Data in the Development Sector, https://www.data4sdgs.org/sites/default/files/services_files/Interoperability%20-%20A%20practitioner%E2%80%99s%20guide%20to%20joining-up%20data%20in%20the%20development%20sector.pdf (accessed on 23 January 2023).
[65] Government of Brazil (2022), Câmara das Cidades - Português (Brasil), https://www.gov.br/mcti/pt-br/acompanhe-o-mcti/transformacaodigital/camara-cidades (accessed on 19 September 2022).
[51] Government of Brazil (2021), The Brazilian Charter for Smart Cities, Ministry of Regional Development, Brasilia, https://www.gov.br/mdr/pt-br/assuntos/desenvolvimento-urbano/carta-brasileira-para-cidades-inteligentes/The_Brazilian_Charter_for_SmartCities_Short_VersionFinal.pdf (accessed on 20 September 2022).
[58] Government of Brazil (n.d.), Ciudades y Territorios Inteligentes, https://gobiernodigital.mintic.gov.co/portal/Iniciativas/Ciudades-y-Territorios-Inteligentes/.
[57] Government of Brazil (n.d.), Decreto nº 9.854, de 25 de Junho de 2019, http://www.planalto.gov.br/ccivil_03/_ato2019-2022/2019/decreto/D9854.htm.
[13] Government of Colombia (2019), Smart Cities and Territories Maturity Model, Ministerio de Tecnologías de la Información y las Comunicaciones, https://gobiernodigital.mintic.gov.co/692/articles-179107_recurso_1.pdf (accessed on 14 September 2022).
[66] Government of Germany (n.d.), Smart City Dialog, https://www.smart-city-dialog.de/en/startseite-en (accessed on 19 September 2022).
[141] Government of India (n.d.), DataSmart Cities: Empowering Cities Through Data, Ministry of Housing and Urban Affairs, https://smartcities.data.gov.in/sites/default/files/DataSmart_Cities_Strategy_Print.pdf (accessed on 29 July 2022).
[153] Government of Japan (2021), Basic Policy on Economic and Fiscal Management and Reform 2021, Cabinet Office, Tokyo, https://www5.cao.go.jp/keizai1/basicpolicies-e.html (accessed on 27 June 2022).
[16] Government of Japan (2020), Smart City Reference Architecture White Paper, Cross-Ministerial Strategic Innovation Promotion Programme, Tokyo, https://www8.cao.go.jp/cstp/stmain/a-whitepaper1_200331_en.pdf (accessed on 30 June 2022).
[125] Government of Japan (2003), Act on the Protection of Personal Information, https://www.japaneselawtranslation.go.jp/en/laws/view/4241/en (accessed on 1 August 2022).
[152] Government of Japan (n.d.), Japan’s Smart Cities: Solving Global Issues Such as the SDGs, etc. through Japan’s Society 5.0, https://www.kantei.go.jp/jp/singi/keikyou/pdf/Japan%27s_Smart_Cities-1(Main_Report).pdf.
[68] Government of the Netherlands (2023), DMI-ecosysteem voor mobiliteitsvernieuwing en slimme, duurzame verstedelijking, Dutch Metropolitan Innovations, https://dutchmobilityinnovations.com/spaces/1216/dmi-ecosysteem/0ver-ecosysteem (accessed on 27 April 2023).
[48] Helsinki Partners (2020), “A smart city saves time and produces better services”, https://www.myhelsinki.fi/en/business-and-invest/invest/a-smart-city-saves-time-and-produces-better-services.
[123] Hickman, T., A. Pierson and E. Comstock (2021), “How changing attitudes toward data sharing could accelerate smart city adoption”, Wjhite & Case LLP, https://www.whitecase.com/publications/insight/how-changing-attitudes-toward-data-sharing-could-accelerate-smart-city (accessed on 28 July 2022).
[49] Hiramoto, K. (2022), “Smart cities in Japan”, PowerPoint presentation given to the OECD team, Tokyo.
[83] IEEE SA (2022), IEEE 802.11-2020/Cor 1-2022 Standard for Information Technology - Telecommunications and Information Exchange between Systems, IEEE Standards Association, https://standards.ieee.org/ieee/802.11-2020_Cor_1/10836/ (accessed on 16 January 2023).
[134] IMD (2022), IMD World Digital Competitiveness. Ranking 2022, https://www.imd.org/centers/wcc/world-competitiveness-center/rankings/world-digital-competitiveness-ranking/.
[154] Ishida, H. (2021), Smart Cities in Japan: achievements and challenges, The University of Tsukuba, http://ascnjapan2021.jp/eng/dl/document/ishida_h.pdf (accessed on 30 June 2022).
[24] Ishida, H. (2021), Smart Cities in Japan: Achievements and Challenges, University of Tsukuba, http://ascnjapan2021.jp/eng/dl/document/ishida_h.pdf (accessed on 30 June 2022).
[78] ISO (2014), ISO 37120:2014(en), Sustainable Development of Communities - Indicators for City Services and Quality of Life, https://www.iso.org/obp/ui/#iso:std:iso:37120:ed-1:v1:en (accessed on 16 January 2023).
[77] ISO (2012), ISO - ISO/TC 268 - Sustainable Cities and Communities, https://www.iso.org/committee/656906.html (accessed on 16 January 2023).
[75] ISO (n.d.), Standards by ISO/TC 268/SC 1: Smart Community Infrastructures, http://www.iso.org/committee/656967/x/catalogue/p/1/u/0/w/0/d/0.
[76] ISO (n.d.), Standards by ISO/TC 268/SC 2: Sustainable Cities and Communities – Sustainable Mobility and Transportation, http://www.iso.org/committee/8742800/x/catalogue/.
[82] ISO-IEC (2015), ISO/IEC JTC 1 Information Technology. Smart Cities. Preliminary Report 2014, http://www.iso.org (accessed on 16 January 2023).
[22] ITF (2020), Leveraging Digital Technology and Data for Human-centric Smart Cities: The Case of Smart Mobility, Report for the G20 Digital Economy Task Force, OECD, Paris, https://www.itf-oecd.org/sites/default/files/docs/data-human-centric-cities-mobility-g20.pdf (accessed on 29 July 2020).
[103] Jacobs, K. (2022), “Toronto wants to kill the smart city forever”, MIT Technology Review - Smart Cities, https://www-technologyreview-com.cdn.ampproject.org/c/s/www.technologyreview.com/2022/06/29/1054005/toronto-kill-the-smart-city/amp/ (accessed on 4 July 2022).
[139] Jakobsone, M. (2022), Italy - National Strategy for Digital Skills, Digital Skills and Jobs Platform, https://digital-skills-jobs.europa.eu/en/actions/national-initiatives/national-strategies/italy-national-strategy-digital-skills (accessed on 22 September 2022).
[50] Japanese Cabinet Office (2022), “Japan’s Smart Cities”, Presentation to the OECD, Secretariat of Science, Technology and Innovation Policy.
[46] Japanese Cabinet Office (n.d.), Society 5.0, https://www8.cao.go.jp/cstp/english/society5_0/index.html (accessed on 22 June 2022).
[17] Johnson, J. et al. (2022), “Data governance frameworks for Smart Cities: Key considerations for data management and use”, Journal of Law and Mobility, Vol. 2022/1, https://repository.law.umich.edu/jlm/vol2022/iss1/1 (accessed on 7 October 2022).
[5] Jung, J. and R. Katz (2022), “Impacto del COVID-19 en la digitalización de América Latina”, Documentos de Proyectos (LC/T.2022/177), Comisión Económica para américa Latina y el Caribe (CEPAL), Santiago, https://www.cepal.org/es/publicaciones/48486-impacto-covid-19-la-digitalizacion-america-latina (accessed on 30 January 2023).
[86] Kaluarachchi, Y. (2022), “Implementing data-driven smart city applications for future cities”, Smart Cities, Vol. 5/2, pp. 455-474, https://doi.org/10.3390/SMARTCITIES5020025.
[23] Kitchin, R. (2016), Getting Smarter about Smart Cities: Improving Data Privacy and Data Security, Department of the Taoiseach, Dublin, https://www.researchgate.net/publication/293755608_Getting_smarter_about_smart_cities_Improving_data_privacy_and_data_security (accessed on 3 February 2023).
[35] Kitchin, R. (2014), “The real-time city? Big data and smart urbanism”, GeoJournal, Vol. 79/1, pp. 1-14, https://doi.org/10.2139/ssrn.2289141.
[74] Kristiningrum, E. and H. Kusumo (2021), “Indicators of Smart City using SNI ISO 37122:2019”, IOP Conference Series Materials Science and Engineering, The Electromechanical Society, https://doi.org/10.1088/1757-899X/1096/1/012013.
[71] Lea, R. (2016), “Smart City Standards - An overview. Trying to make sense of Smart City standardization activities”, UrbanOpus, https://urbanopus.net/smart-city-standards-an-overview/ (accessed on 16 January 2023).
[44] Lechner (n.d.), Cargohopper (Environmentally Friendly Urban Goods Transport), http://okosvaros.lechnerkozpont.hu/en/node/232.
[148] Lee, C. et al. (2013), “Building a generic platform for big sensor data application”, IEEE International Conference on Big Data.
[97] LINE Fukuoka (n.d.), Line Smart City for Fukuoka, https://smartcity.linefukuoka.co.jp/ja/project/smartcityproject?hsLang=ja-jp.
[126] Ma, C. (2021), “Smart city and cyber-security: Technologies used, leading challenges and future recommendations”, Energy Reports, Vol. 7, pp. 7999-8012, https://doi.org/10.1016/J.EGYR.2021.08.124.
[3] Mairie de Paris (2020), Smart and Sustainable – Looking Ahead to 2020 and Beyond, https://cdn.paris.fr/paris/2020/02/26/f7dc822a66de6000cd910a145c7fca39.ai (accessed on 19 October 2022).
[6] Makishima, K. (2022), Japan’s Digital Policy, Digital Agency of Japan, Tokyo, https://www.digital.go.jp/assets/contents/node/basic_page/field_ref_resources/0f321c23-517f-439e-9076-5804f0a24b59/6fd24c53/20220519_en_japan_digital_policy_01.pdf (accessed on 1 July 2022).
[31] Marr, B. (2018), “How much data do we create every day? The mind-blowing stats everyone should read”, Forbes, https://www.forbes.com/sites/bernardmarr/2018/05/21/how-much-data-do-we-create-every-day-the-mind-blowing-stats-everyone-should-read/?sh=97c498160ba9 (accessed on 2 May 2023).
[32] McKinsey Global Institute (2015), The Internet of Things: Mapping the Value Beyond the Hype - Executive Summary, https://www.mckinsey.com/~/media/mckinsey/industries/technology%20media%20and%20telecommunications/high%20tech/our%20insights/the%20internet%20of%20things%20the%20value%20of%20digitizing%20the%20physical%20world/unlocking_the_potential_of_the_internet_of_things_executive_summary.pdf (accessed on 2 May 2023).
[85] Micheli, M. et al. (2020), “Emerging models of data governance in the age of datafication”, Big Data & Society, https://doi.org/10.1177/2053951720948087.
[89] Mirzaee, A. and J. Sardroud (2022), “Public–private-partnerships (PPP) enabled smart city funding and financing”, in Smart Cities Policies and Financing, Elsevier, https://doi.org/10.1016/B978-0-12-819130-9.00011-5.
[11] Morikawa, M. (2021), “The productivity of working from home: Evidence from Japan”, RIETI, https://voxeu.org/article/productivity-working-home-evidence-japan (accessed on 22 June 2022).
[94] Muroi, S. (2021), “Initiatives and vision for Smart City Aizuwakamatsu”, Information provided to the OECD by the government of Aizuwakamatsu City, Aizuwakamatsu.
[53] Nakano, H. et al. (2021), “Hitachi digital smart cities featuring continuous value creation by people and digital technology”, Innovations to Improve People’s Quality of Life, Vol. 70/1, https://www.hitachi.com/rev/archive/2021/r2021_01/01a01/index.html.
[137] New Zealand Digital Skills Forum (2018), Digital Skills for a Digital Nation: An Analysis of the Digital Skills Landscape of New Zealand, New Zealand Digital Skills Forum, https://digitalskillsforum.files.wordpress.com/2018/01/digital-skills-for-a-digital-nation-online.pdf (accessed on 22 September 2022).
[109] Nordic Smart City Network (n.d.), Copenhagen Solutions Lab, https://nscn.eu/Copenhagen (accessed on 16 September 2022).
[118] NSW Government (2021), NSW Government Data Strategy, New South Wales, Sydney, https://data.nsw.gov.au/sites/default/files/inline-files/NSW%20Government%20Data%20Strategy_0.pdf (accessed on 27 July 2022).
[52] NYC Government (2021), IoT Strategy - The New York City Internet of Things Strategy, Mayor’s office of the Chief Technology Officer, New York, https://www1.nyc.gov/assets/cto/downloads/iot-strategy/nyc_iot_strategy.pdf (accessed on 16 August 2022).
[4] OECD (2022), Decarbonising Buildings in Cities and Regions, OECD Urban Studies, OECD Publishing, Paris, https://doi.org/10.1787/a48ce566-en.
[142] OECD (2022), Financing Growth and Turning Data into Business: Helping SMEs Scale Up, OECD Studies on SMEs and Entrepreneurship, OECD Publishing, Paris, https://doi.org/10.1787/81c738f0-en.
[38] OECD (2022), Going Digital to Advance Data Governance for Growth and Well-being, OECD Publishing, Paris, https://doi.org/10.1787/e3d783b0-en.
[30] OECD (2021), Innovation and Data Use in Cities: A Road to Increased Well-being, OECD Publishing, Paris, https://doi.org/10.1787/9f53286f-en.
[8] OECD (2021), OECD Economic Surveys: Japan 2021, OECD Publishing, Paris, https://doi.org/10.1787/6b749602-en.
[144] OECD (2021), OECD SME and Entrepreneurship Outlook 2021, OECD Publishing, Paris, https://doi.org/10.1787/97a5bbfe-en.
[10] OECD (2021), “Teleworking in the COVID-19 pandemic: Trends and prospects”, OECD Policy Responses to Coronavirus (COVID-19), OECD, Paris, https://www.oecd.org/coronavirus/policy-responses/teleworking-in-the-covid-19-pandemic-trends-and-prospects-72a416b6/ (accessed on 12 December 2022).
[143] OECD (2021), The Digital Transformation of SMEs, OECD Studies on SMEs and Entrepreneurship, OECD Publishing, Paris, https://doi.org/10.1787/bdb9256a-en.
[54] OECD (2021), The E-Leaders Handbook on the Governance of Digital Government, OECD Digital Government Studies, OECD Publishing, Paris, https://doi.org/10.1787/ac7f2531-en.
[129] OECD (2021), “The OECD Framework for digital talent and skills in the public sector”, OECD Working Papers on Public Governance, No. 45, OECD Publishing, Paris, https://doi.org/10.1787/4e7c3f58-en.
[9] OECD (2020), “Cities policy responses”, OECD Policy Responses to Coronavirus (COVID-19), OECD, Paris, https://www.oecd.org/coronavirus/policy-responses/cities-policy-responses-fd1053ff/.
[12] OECD (2020), Smart Cities and Inclusive Growth, OECD, Paris, https://www.oecd.org/cfe/cities/OECD_Policy_Paper_Smart_Cities_and_Inclusive_Growth.pdf (accessed on 17 February 2021).
[136] OECD (2019), Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across Societies, OECD Publishing, Paris, https://doi.org/10.1787/276aaca8-en.
[112] OECD (2019), OECD Skills Outlook 2019: Thriving in a Digital World, OECD Publishing, Paris, https://doi.org/10.1787/df80bc12-en.
[25] OECD (2019), The Path to Becoming a Data-Driven Public Sector, OECD Digital Government Studies, OECD Publishing, Paris, https://doi.org/10.1787/059814a7-en.
[84] OECD (2018), Housing Dynamics in Korea: Building Inclusive and Smart Cities, OECD Publishing, Paris, https://doi.org/10.1787/9789264298880-en.
[43] OECD/UCLG (2019), 2019 Report of the World Observatory on Subnational Government Finance and Investment - Key Findings, http://www.sng-wofi.org/publications/2019_SNG-WOFI_REPORT_Key_Findings.pdf (accessed on 28 August 2019).
[40] Open Data Soft (2017), “How Amsterdam uses urban data to build a more sustainable city”, https://www.opendatasoft.com/en/blog/amsterdams-energy-atlas-using-urban-data-to-build-a-sustainable-city/.
[106] Ospedale San Raffaele (n.d.), Advanced Technology in Health and Wellbeing, https://research.hsr.it/en/search/index.html?q=eservices+.
[127] Pandey, P. et al. (2019), Making Smart Cities Cybersecure: Ways to Address Distinct Risks in an Increasingly Connected Urban Future, Deloitte Center for Government Insights, https://www2.deloitte.com/content/dam/Deloitte/de/Documents/risk/Report_making_smart_cities_cyber_secure.pdf (accessed on 28 July 2022).
[21] Paskaleva, K. et al. (2017), “Data governance in the sustainable smart city”, Informatics, Vol. 4/4, https://doi.org/10.3390/INFORMATICS4040041.
[64] Pianezzi, D., Y. Mori and S. Uddin (2021), “Public–private partnership in a smart city: A curious case in Japan”, International Review of Administrative Sciences, Vol. 1/16, https://doi.org/10.1177/00208523211051839.
[114] Privacy Commissioner of Canada (2019), The Personal Information Protection and Electronic Documents Act (PIPEDA), https://www.priv.gc.ca/en/privacy-topics/privacy-laws-in-canada/the-personal-information-protection-and-electronic-documents-act-pipeda/ (accessed on 16 August 2022).
[96] PRNewswire (2020), “Plug and Play Japan to open its new office “Plug and Play Osaka””, https://www.prnewswire.com/news-releases/plug-and-play-japan-to-open-its-new-office-plug-and-play-osaka-301103175.html.
[26] PwC (2021), Smart Cities in 2050: Rebuilding the Future of Japanese Cities, Pricewaterhouse Coopers LLP, Delaware, https://www.pwc.com/jp/en/knowledge/thoughtleadership/assets/pdf/smart-city2050-en.pdf (accessed on 16 August 2022).
[117] PwC (2019), The Foundation for Smart City Success - Seven Layers of Data Governance and Management, Pricewaterhouse Coopers LLP, Delaware.
[149] Raval, T. (2019), “Examining the San Francisco facial-recognition ban”, Forbes, https://www.forbes.com/sites/forbestechcouncil/2019/06/21/examining-the-san-francisco-facial-recognition-ban/?sh=7543b4a81d69 (accessed on 4 July 2022).
[145] Rochdane, H. and S. Hamdani (2018), “Role of smart small and medium enterprises in the development of smart cities: Case of Casablanca Smart-City Project - Morocco”, International Journal of e-Education, e-Business, e-Management and e-Learning, Vol. 8/3, pp. 181-186, https://doi.org/10.17706/IJEEEE.2018.8.3.181-186.
[120] Rocher, L., J. Hendrickx and Y. de Montjoye (2019), “Estimating the success of re-identifications in incomplete datasets using generative models”, Nature Communications, Vol. 10/1, pp. 1-9, https://doi.org/10.1038/s41467-019-10933-3.
[91] Sakurai, M. and J. Kokuryo (2018), “Fujisawa Sustainable Smart Town: Panasonic’s challenge in building a sustainable society”, Communications of the Association for Information Systems, Vol. 42/1, p. 19, https://doi.org/10.17705/1CAIS.04219.
[140] Salesforce YouGov (2021), “Digital skills - India”, https://www.salesforce.com/content/dam/web/en_in/www/images/resources/digital-skills-india.pdf (accessed on 4 October 2022).
[28] Sarker, I. (2022), “Smart city data science: Towards data-driven smart cities with open research issues”, Internet of Things, Vol. 19, p. 100528, https://doi.org/10.1016/J.IOT.2022.100528.
[70] SCC (2021), Canadian Data Governance Standardization Roadmap, Standards Council of Canada, https://www.scc.ca/en/system/files/publications/SCC_Data_Gov_Roadmap_EN.pdf (accessed on 16 January 2023).
[147] Schafroth, B. (2018), “Real-time data and smart cities”, LinkedIn, https://www.bryanschafroth.com/post/2018/03/20/real-time-data-and-smart-cities/ (accessed on 20 September 2022).
[101] Sidewalk Labs (2017), Toronto Tomorrow: A New Approach for Inclusive Growth, https://www.torontopubliclibrary.ca/detail.jsp?Entt=RDM3820301&R=3820301 (accessed on 4 July 2022).
[63] Smart Cities UK (n.d.), Homepage, https://smartcityuk.com/ (accessed on 20 January 2022).
[67] Smart City Institute Japan (2022), Homepage, https://www.sci-japan.or.jp/english/ (accessed on 19 September 2022).
[61] Smart City Korea (n.d.), Homepage, https://smartcity.go.kr/en/ (accessed on 26 January 2022).
[98] Smart City Takeshiba (n.d.), Homepage, https://smartcitytakeshiba.com/ (accessed on 4 September 2022).
[37] Stedman, C. and J. Vaughan (n.d.), “What is data governance and why does it matter?”, TechTarget, https://www.techtarget.com/searchdatamanagement/definition/data-governance (accessed on 30 January 2023).
[62] SwissCom (n.d.), Human Smart City, https://www.swisscom.ch/en/about/innovation/smart-city.html.
[119] Tene, O. and J. Polonetsky (2013), “Data for all: Privacy and user control in the age of analytics”, Northwestern Journal of Technology and Intellectual Property, Vol. 11/5, p. 239, https://scholarlycommons.law.northwestern.edu/njtip/vol11/iss5/1 (accessed on 6 February 2023).
[18] Thomas, K. (2019), “Smart cities - Lessons from smart city developments around the world”, Lewis Silkin, https://www.lewissilkin.com/en/insights/smart-cities-lessons-from-smart-city-developments-around-the-world (accessed on 6 July 2022).
[105] Toderian, B. and J. Glover (2014), “10 lessons in more engaging citizen engagement”, Planetizen, https://www.smartcitiesdive.com/ex/sustainablecitiescollective/10-lessons-more-engaging-citizen-engagement/231051/ (accessed on 4 July 2022).
[15] Tokyo Metropolitan Government (2016), New Tokyo, New Tomorrow. The Action Plan for 2020, https://www.metro.tokyo.lg.jp/english/about/plan/documents/pocket_english.pdf (accessed on 5 July 2022).
[92] Tokyoesque (2022), “Smart cities in Japan: Practical innovations for conscious future living”, https://tokyoesque.com/smart-cities-in-japan/.
[95] Toyota (2020), “Toyota to build a hydrogen-powered city of the future”, https://mag.toyota.co.uk/toyota-woven-city-hydrogen-power/.
[122] UK Government (2020), National Data Strategy, Department for Digital, Media, Culture & Sport, https://www.gov.uk/government/publications/uk-national-data-strategy/national-data-strategy#data-1-2 (accessed on 1 August 2022).
[90] UK Government (2020), UK Smart Cities Directory, Department of International Trade, https://eu.eventscloud.com/file_uploads/2ed36ce5867a41381abc8a5861b7fcd7_UKSmartCitiesDirectory.pdf (accessed on 19 September 2022).
[155] Valente, F. (2020), “Smart cities to create business opportunities worth $2.46 trillion by 2025”, Frost & Sullivan, https://www.frost.com/news/press-releases/smart-cities-to-create-business-opportunities-worth-2-46-trillion-by-2025-says-frost-sullivan/ (accessed on 21 June 2022).
[130] Valtasaari, S. (2022), “Japan - A new challenger in the smart city industry”, Open & Agile Smart Cities, https://oascities.org/japan-a-new-challenger-in-the-smart-city-industry/ (accessed on 30 June 2022).
[39] Van Winden, W. and D. Van Den Buuse (2017), “Smart city pilot projects: Exploring the dimensions and conditions of scaling up”, Journal of Urban Technology, Vol. 24/4, pp. 51-72, https://doi.org/10.1080/10630732.2017.1348884.
[121] van Zoonen, L. (2016), “Privacy concerns in smart cities”, Government Information Quarterly, Vol. 33/3, pp. 472-480, https://doi.org/10.1016/J.GIQ.2016.06.004.
[110] von Grafenstein, M., A. Wernick and C. Olk (2019), “Data governance: Enhancing innovation and protecting against its risks”, Intereconomics, Vol. 54/4, pp. 228-232, https://doi.org/10.1007/S10272-019-0829-9.
[102] Wachter, S. (2019), “What’s fueling the smart city backlash?”, Knowledge at Wharton, https://knowledge.wharton.upenn.edu/article/whats-behind-backlash-smart-cities/ (accessed on 4 July 2022).
[79] WCCD (n.d.), WCCD ISO 37120 Series, World Council on City Data, https://www.dataforcities.org/wccd-iso-37120-series-on-city-data (accessed on 16 January 2023).
[33] WEF (2022), Unlocking the Shared Value of Smart City Data: A Protocol for Action, World Economic Forum, https://www3.weforum.org/docs/WEF_Unlocking_Shared_Value_Smart_City_Data_2022.pdf (accessed on 19 April 2023).
[2] WEF (2020), Data Free Flow with Trust (DFFT): Paths towards Free and Trusted Data Flows, World Economic Forum, Geneva, https://www.weforum.org/whitepapers/data-free-flow-with-trust-dfft-paths-towards-free-and-trusted-data-flows/ (accessed on 13 July 2022).
[132] WorldSkills UK (n.d.), Disconnected? Exploring the Digital Skills gap, World Skills UK, Learning and Work Institute, Enginuity, https://www.worldskillsuk.org/wp-content/uploads/2021/03/Disconnected-Report-final.pdf (accessed on 3 October 2022).
[99] Yamamoto, C. et al. (2021), “Data-driven and optimized smart cities using urban DTC”, NTT R&D, https://www.rd.ntt/e/research/JN202011_8272.html (accessed on 29 June 2022).
[146] Zheng, Z. et al. (2015), “Real-time big data processing framework: Challenges and solutions”, Applied Mathematics and Information Sciences, Vol. 9/6, pp. 3169-3190, https://doi.org/10.12785/AMIS/090646.
Notes
← 1. For further information, see: https://www.weforum.org/agenda/2021/04/japan-smart-city-initiatives-digitisation‑economic‑revival‑gtgs/#:~:text=This%20new%20law%20aims%20to,and%20use%20of%20autonomous%20vehicles.
← 2. For further information, see: https://www.outlookindia.com/website/story/outlook-spotlight-how-did-covid-accelerated-digital-transformation-in-india/385365.
← 3. This definition comes from the different interviews the OECD team held with Japanese experts in the course of this project. They provided their own interpretation or understanding of smart cities and this definition encapsulates their common ground.
← 4. For further information, see https://impact.canada.ca/en/node/117.
← 5. For further information, see: https://smartcity.go.kr/en/%EC%86%8C%EA%B0%9C/#:~:text=South%20Korea,enhance%20its%20competitiveness%20and%20livability.
← 6. For further details, see: Kitchin (2016[23]).
← 7. For further information, see: https://loti.london/resources/data-methodology/.
← 8. For further information, see: https://www.marketsandmarkets.com/Market-Reports/internet-of-things-market-573.html#:~:text=The%20global%20IoT%20Market%20size,presenting%20a%20CAGR%20of%2016.7%25.
← 9. For further information, see: https://smartamerica.org/teams/smart-cities-usa/.
← 11. For further information, see: https://www.statista.com/statistics/1244794/japan-factory-iot-market-size/.
← 13. For further information, see: https://www.statista.com/statistics/871513/worldwide-data-created/.
← 14. For further information see: US Department of Transportation, https://www.transportation.gov/smartcity/7-finalists-cities.
← 15. See: https://hub.beesmart.city/en/strategy/how-smart-cities-save-governments-businesses-citizens-money.
← 17. For further information, see: https://www.gihub.org/innovative-funding-and-financing/case-studies/data-monetization-as-a-source-of-funding-for-smart-city-projects/.
← 18. For further information, see: https://www.nycstreetdesign.info/furniture/linknyc-kiosk.
← 19. For further information, see: https://www.smart-energy.com/regional-news/asia/japan-to-install-80m-smart-meters-by-2025/.
← 20. For further information, see: https://www.edisonfoundation.net/-/media/Files/IEI/publications/IEI_Smart_Meter_Report_April_2021.ashx#:~:text=Based%20on%20survey%20results%20and,expected%20by%20year%2Dend%202021 and https://www.eia.gov/tools/faqs/faq.php?id=108&t=3#:~:text=In%202021%2C%20U.S.%20electric%20utilities,electric%20meters%20were%20AMI%20meters.
← 21. For further information, see: https://joinup.ec.europa.eu/collection/nifo-national-interoperability-framework-observatory/1-introduction#1.1 and https://joinup.ec.europa.eu/collection/nifo-national-interoperability-framework-observatory/european-interoperability-framework-detail.
← 22. For further information, see: https://www.mlit.go.jp/scpf/index.html.
← 23. For further information, see: https://www.iso.org/standard/69050.html.
← 24. For further information, see: https://www.iso.org/obp/ui/#iso:std:iso:37122:ed-1:v1:en.
← 25. For further information, see: https://korea.ahk.de/en/services/core-industries/smart-city.
← 26. See: https://www.mckinsey.com/capabilities/operations/our-insights/how-can-the-private-and-public-sectors-work-together-to-create-smart-cities.
← 27. For further information on Yokohama Smart City project, see: https://www.city.yokohama.lg.jp/lang/overseas/climatechange/contents/energypolicy/yscp.html#:~:text=Yokohama%20aims%20to%20be%20an,both%20in%20and%20outside%20Japan.
← 28. Definition based on the information provided by the European Network of Living Labs, https://enoll.org/about-us/what-are-living-labs/.
← 29. Big data refer to the large volumes of (digital) data generated from transactions, production and communication processes through ICT including the Internet. For further information, see OECD (2015), Data-Driven Innovation: Big Data for Growth and Well-Being, http://dx.doi.org/10.1787/9789264229358-en.
← 31. For further information, see: https://www.gdpreu.org/compliance/fines-and-penalties/.
← 32. For further information, see: https://digitalskills.unlv.edu/digital-marketing/what-are-digital-skills/#:~:text=Digital%20skills%20are%20defined%20as,such%20as%20computers%20and%20smartphones.
← 33. For further information on data skills, see OECD (2019[136]).
← 34. For further information, see: https://digital-skills-jobs.europa.eu/en/actions/national-initiatives/national-strategies/estonia-digital-agenda-estonia-2020.
← 35. For further information on digitalisation in Estonia, see: The Digital Economy and Society Index – Countries’ Performance in Digitisation, https://digital-strategy.ec.europa.eu/en/policies/countries-digitisation-performance.
← 36. See: https://www.oecd.org/cfe/smes/msme-week.htm#:~:text=In%20the%20OECD%2C%20SMEs%20account,60%25%20of%20national%20value%20added.
← 38. See: https://www.sfchronicle.com/bayarea/article/Oakland-bans-use-of-facial-recognition-14101253.php.
← 40. For further information, see: https://www.kantei.go.jp/jp/singi/keikyou/pdf/Japan%27s_Smart_Cities-1(Main_Report).pdf.
← 41. Ibid.