Urban Data Platform

Description

Urban data platforms build the basis for a multitude of applications in a Smart City. An urban data platform intends to collate, map, store and integrate data from different stakeholders of the Smart City ecosystem (e.g. public entities, businesses, citizens or other organisations). The data can be offered to other service providers, can be analysed or visualised, and published. Such an urban data platform can be the basis for a lot of smart city solutions as it offers a stable and flexible base for data-driven solutions. An urban data platform can constitute a holistic system, connecting various services around a city by bringing all data together. A multisided market approach can support small and medium enterprises (SMEs) as data is available without any high initial investments. The main concern when it comes to urban data platforms is security, privacy and transparency, which places special focus on the responsibility and the reliability of the operator of the platform.

Problems to be solved:

City Context

The following aspects contribute to the implementation of an Urban Data Platform:

• Access to relevant data from various sources or the existence of data collected.
• An innovative environment in the city promoting the development of skills and interest in working with data.
• The presence of collaboration between institutions facilitating data access and exchange.

Operating Models

Ownership and management

As presented by Sheombar et al. (2020) Urban Data Platforms can be owned and managed by the same or different types of actors. Platform Owners “have legal control over the technology and intellectual property”, a role that could be played by governments, public-private partnerships, private actors, or citizens. Platform Managers maintain, run, and develop the platform within the guidelines provided by the Platform Owners, and it could be done by governments, private actors or public-private partnerships.

Possible combinations of platform ownership and management. Source: Sheombar et. al., 2020.

According to a survey conducted in 2019 with about 85 European cities, showed that more than 60% of Urban Data Platforms are both owned and managed by the public sector, and only a fraction has public-private ownership (18%) or management (17%). Privately owned platforms account for 10% of the surveyed cities and privately managed for 15% (Sheombar et al., 2020).

Furthermore, a growing number of municipalities are experimenting with new governance arrangements that give the citizens a more central role in making decisions about their data (see data commons models, data trusts, and data stewardship). As these initiatives grow in number, they will have a substantial impact on how urban data platforms are designed and governed.

Funding

Potential options include:

• Municipal financing from capital or operational budget,
• Public grants or competition funds,
• Industry Research Development and Innovation,
• Industry Public-Private Partnership,
• Market funds (loans, equality, concession)
• Crowdfunding

Following the results of the aforementioned survey, 38% of the cities have financed their platforms with capital budget from the municipality, 22% with operational budget, and 23% with public grants or competition funds. In total, 83% of the platforms have been financed by public money, which also aligns with the current understanding that Urban Data Platforms are core critical infrastructure and their business case aligns with other urban infrastructure (Sheombar et al., 2020).

Cost Structure

Required resources to design and operate an Urban Data Platform (BABLE, 2021)

Business Model

Under the project RUGGEDISED, four business models have been identified in the market of Urban Data Platforms, which include:

1. Data for sale: data collected by any urban stakeholders can be exchanged and sold via the UDP. Intermediaries may play an important role here, especially if data is collected directly by the citizens.
2. Data collection and aggregation as a service: data is collected from a variety of sources to be published as open data. In order for this data to be re-usable, additional services may be needed, like cleaning, filtering, processing, and aggregation. This service may be provided to an UDP manager or similar who may be interested in accessing good quality data from diverse sources, supporting a better understanding of the issue in question.
3. Data analytics and use as a service: analysing data based on the demands of a client for a price or co-creating data-driven solutions and improving them in an open-source manner. The type of business models may entail Business to Business (B2B), Business to Cities/Clients (B2C), and Peer-to-Peer (P2P).
4. Multi-source data mash-up and analysis: this model aggregates all others into one, where data is collected, aggregated and analysed.

Typology of Business Models on the UDP Source: Sheombar et. al., 2020.
 

Revenue Model

Urban Data Platforms may offer access to data for a price, especially the “Marketplace” variants. In those cases, there are pricing catalogues and/or mechanisms to mediate the buying and selling of data or data access on the platform.

In addition, more advanced versions may be able to offer a portfolio of advanced platform tools such as training, catalogues, collaboration, etc. (Sheombar et. al., 2020).

Furthermore, since most cities pay for the maintenance and operations costs of the platforms and these support the development of other services, the costs could be calculated in the services fee.

Market Potential

“The EU open data market is a key building block of the overall EU data economy. According to a study conducted for the creation of the PSI Directive, the total direct economic value of public sector information is expected to increase from a baseline of €52 billion in 2018 for the EU27 + UK, to €194 billion in 2030” (European Commission, 2021).

The value of the data economy of EU27 was almost €325 billion in 2019, representing 2.6 % of GDP. The same estimate predicts that it will increase to over €550 billion by 2025, representing 4 % of the overall EU GDP (European Commission, 2020).

Examples of industrial and commercial data use and its economic benefits (European Commission, 2019)

Stakeholder Mapping

Stakeholders relations in an Urban Data Platform (BABLE, 2021)

Government Initiatives

• There is substantial funding coming from the EU, especially in the Horizon2020 funding scheme, that supports the implementation and exploitation of data platforms and ecosystems. Besides that, the EU has an Open Data Portal, which serves as the European gateway to open data resources. The European Open Data Portal shares, among many other things, the most viewed data sets. For further information have a look at the portal.
• National Governments across Europe are increasingly investing in programmes that put data at the centre of the strategies and development. They include developing capacities to work with data, cooperating with important actors from the ecosystem, and setting up the right infrastructure to do it.
• Local governments are also progressively dedicating more human and monetary resources to set up data platforms and to build capacity and increase interest in their local ecosystems.

Supporting Factors

• A definition of specific use cases decreases complexity and simplifies citizen engagement.
• Professional and content-related discussions enhance the development of data-sharing agreements. People want to understand what value they receive in return for sharing their data.
• A collaborative approach with several municipal departments can facilitate access to data held by other entities.
• Public tenders may include requirements for partnering entities to share their project data, giving the city the right to publish it (sometimes it may only be shared privately) (Smarter Together, 2019).
• A strong and transparent governance model with clear roles and responsibilities guaranteeing data quality and maintenance.
• Transparency/Ethical guidelines regarding how data is handled and used (especially if there’s citizens’ data involved).
• Policies and regulations facilitating and easing the exchange of data.

Legal Requirements

• EU General Data Protection Regulation (GDPR): The EU General Data Protection Regulation (GDPR) replaces the Data Protection Directive 95/46/EC and was designed to harmonise data privacy laws across Europe, to protect and empower all EU citizens data privacy and to reshape the way organisations across the region approach data privacy. The key articles of the GDPR, as well as information on its business impact, can be found throughout this site.
• Regulation on European Data Governance (proposal, not yet approved): this instrument aims to foster the availability of data for use by increasing trust in data intermediaries and by strengthening data-sharing mechanisms across the EU. Fundamental definitions in this proposal include: 
  • Portable services – enabling the reuse of data held by the public sector more widely, including sensitive data.
  • Data spaces – which will be technological infrastructure and governance mechanisms facilitating the exchange of data across the EU in a trustworthy and low-cost manner.
  • Data altruism – making it easier for individuals and companies to make data available for the benefit of the whole society (see Draft proposal).
• EU Directive on open data and the re-use of public sector information: “introduces the concept of high-value datasets (associated with important benefits for the society and economy). They are subject to a separate set of rules ensuring their availability free of charge, in machine-readable formats, provided via Application Programming Interfaces (APIs) and, where relevant, as bulk download”. In addition, this Directive strengthens the transparency requirements for public-private agreements involving public sector information (European Commission, 2020).

Data and Standards

The EU funded project Syncronicity has created a framework for categorising different standards depending on the main goal the support achieving. Examples relevant for the development of Urban Data Platforms are presented below (Syncronicity, 2020) (Standards Library, 2021):

1. Define Something:
   1. ITU-T Y4051 for common vocabulary for smart cities
   2. ISO/IEC 20546:2019 provides a set of terms and definitions needed to promote improved communication and understanding of Big Data.
   3. Data Catalog Vocabulary (DCAT)
2. Understand something: 
   1. PD8100 defines a smart city.
3. Design something: 
   1. ISO/IEC 30141:2018 Reference ICT Architecture
   2. DIN SPEC 91357 - Reference Architecture Model “Open Urban Platform” defines components and the architecture for an ICT architecture.
4. Manage something:
   1. PAS183 provides a decision-making framework for sharing data,
   2. ISO/IEC TR 10032:2003 establishes a framework for coordinating the development of existing and future standards for the management of persistent data in information systems,
   3. ISO/IEC 30182:2017 offers guidance for interoperability between system components by aligning ontologies,
   4. ISO/IEC AWI 38507 describes governance implications of the use of AI by organisations,
   5. PAS 185:2017 specifies for establishing and implementing a security-minded approach.
5. Measure something:
   1. ISO 37122 defines indicators for smart cities.