ISCN Online Advisory Programme #12: From Urban Data Platforms to Urban Data Spaces

After having focused on Urban Data Platforms in India and Data platforms on multiple geographic levels (Buenos Aires, Flanders and Lyon) in the previous editions, the development towards Data Spaces couldn’t be timelier.  
 
But first: What is an Urban Data Space? By now, the concept of data platforms has become known – even though there remains room for interpretation – as digital infrastructures to manage data (i.e. data catalog) or real-time data (i.e. urban data platform). An Urban Data Space, however, is a decentralized approach to data sharing. An approach to allow different stakeholders of different organizations to share data in a sovereign way. Sovereign in this context means that the data owner remains the owner and in full control over who has access to which data and in some cases for how long and for what purposes. 

The recently founded Data Spaces Support Centre defines a data space as follows:  
“A distributed system defined by a governance framework that enables secure and trustworthy data transactions between participants while supporting trust and data sovereignty. A data space is implemented by one or more infrastructures and enables one or more use cases.” 

Urban Data Spaces enable data sharing between stakeholders who until now haven’t been sharing data before. That can be the local public transport company sharing data about real-time locations of buses with the mobility department of the city. Or the city shares specific data with a research institute only for a specific project. In the future, it is even possible to sell data and enable new business models. As such, Data Spaces are a concept that can bridge the usual dichotomy between Open Data and closed or proprietary data. If the goal for some processes in Smart Cities is to become end-to-end and largely automated, then Urban Data Spaces can facilitate the streamlining of architecture and reduce the number of points of friction. 
 

Sophie Meszaros, Researcher at imec and Project Manager at Open & Agile Smart Cities (OASC) introduced us to the topic of data spaces. She described them as an instrument to support data sharing and interoperability and bring together data from different silos and different sectors. An illustrative example that Sophie gave during the talk was the idea of combining real-time data on passenger arrivals and departures from a local airport and data from hotels on their reservations, to optimize public transportation or other resource allocations.  
She offered an insight into the Blueprint for the European Data Space for Smart Communities. The blueprint provides guidelines and frameworks that help in making the next steps towards an Urban Data Space. 
A pilot deployment phase is planned and there are still opportunities for cities and regions that want to participate and pilot the Urban Data Space framework. All information is available here:
 https://www.ds4sscc.eu/expression-of-interest 

Tim Cleffmann, project coordinator of the research project “Municipal Data Space” with the Mainz Utility Company pitched the current implementation of the Urban Data Space around mobility data in Mainz, Germany. There, a collaborative effort among a mobility company, the government, and the local utility company gave rise to a pioneering initiative—a data space aimed at fostering sustainable urban mobility through informed decision-making. After having understood the concerns and uncertainties of the stakeholders involved regarding which data could be shared, they managed to establish a sophisticated role and rights management system, which ensured that the interests of all parties were met. We took away that “beyond legal structures, the credibility and integrity of the entities involved play a pivotal role”, as Cleffmann underlined. A second key learning is that stakeholders are more eager to share their data, once the “benefit of data sharing has been proved in specific use cases”. 

During the workshop sessions, all participants discussed the risks and potentials of data spaces. Most participants embraced data sharing's transformative potential for better decision-making and governance quality. Data Spaces emerged as a catalyst for breaking down sectoral silos, fostering innovation through reciprocal data exchange among stakeholders like businesses, research institutions, and governance bodies. 

Despite widespread interest, some participants expressed reservations about data spaces, particularly regarding privacy concerns and the secure sharing of critical infrastructure data. City representatives highlighted uncertainty about shared data's extent and interoperability, emphasizing the need for equitable conditions to encourage voluntary data sharing. 

The results highlighted the importance of a common framework including robust legal structures as well as roles and rights within data spaces to build trust among stakeholders.  

Finally, Javier Orozco-Messana, provided a comprehensive overview of upcoming funding opportunities for cities and regions to develop Urban Data Spaces as well as associated applications: 

• CitiVerse: Developing hybrid worlds for Citizens (First Call closed, other calls are planned) 
• Data Space Deployment Call of DS4SSC
• Towards networked Local Digital Twins and the implementation of the Local Digital Twin Toolbox (currently in development) 

The new EU Call in the Comissions Work Plan 2024 “Towards networked Digital Twins in the EU” consolidates results and actions from the European Data Space for smart communities and its deployment Local Digital Twin (LDT) toolbox procurement. Furthermore, it aims at moving towards an ecosystem of mature and connected Local Digital Twins in the EU. Under this programme, existing LDT will be connected to reinforce interoperability. Besides, new LDT should be created while AI-based tools were to be added to the LDT toolbox already established. The overall goal is to help communities with different levels of maturity achieve economies of scale when developing data platforms and Local Digital Twins and to create an EU ecosystem of LDTs, sharing means and ways of handling data and making predictions.