Leveraging Data Spaces in Digital Twins for Smart Cities Deployment: How Digital Twins Powered by Data Spaces Can Help Us Build Inclusive, Sustainable Smart Cities

Introduction

Digital twins as digital representations of physical objects, systems, or processes - can be used to simulate the behavior of real-world objects, systems, or processes in a virtual environment. This can help us understand how these objects, systems, or process’s function, and identify potential improvements or issues.

In the context of smart cities, digital twins can be used to create digital models of urban environments. These digital models can be powered by data from a variety of sources, including sensors, IoT devices, and other data sources. By integrating this data into a digital twin, city planners and decision makers can gain a better understanding of how the city is functioning and identify areas for improvement.

For example, a digital twin of a city's transportation system could be used to simulate the flow of traffic and identify bottlenecks or congestion. This information could be used to develop strategies for improving the efficiency of the transportation system, such as implementing new routing algorithms or building additional infrastructure.

In addition to improving the efficiency of city systems, digital twins can also be used to help create more inclusive and sustainable smart cities. By analyzing data from a variety of sources, city planners can identify areas where certain groups of people may be underserved or disadvantaged, and develop strategies for addressing these issues. For example, a digital twin of a city's energy system could be used to identify areas where access to clean, renewable energy is limited, and develop plans for expanding access to these resources.

Overall, digital twins powered by data spaces can be a powerful tool for helping us build more inclusive and sustainable smart cities. By providing a virtual representation of urban environments, and integrating data from a variety of sources, digital twins can help us understand how cities function, identify areas for improvement, and develop strategies for addressing those challenges (Gauss Centre for Supercomputing, 2020).

Digital twins technology is directly related to data spaces.

A dataspace refers to a type of data relationship between trusted partners where each apply the same standards and rules for storing and sharing their data. However, central to the concept of a dataspace is that the data is not stored centrally, but rather distributed at the respective source, and is therefore only shared as needed in the context of common use cases. Data spaces focus on domains (economic areas, industrial sectors or other specialist application fields) and make metadata available for potential innovative services while maintaining data sovereignty, i.e., the greatest possible control and dominion over their own data. Domain-specific data spaces can also connect (federate) with other data spaces, such as a mobility data space with a tourism data space (Prinz, Rose, and Urbach, 2022).

Building a digital twin requires coordinating many components into a coherent whole. Most of the data needed for the creation of the digital twin is stored somewhere within a company. Building complex digital twins representing smart cities, food supply chain systems, logistics, and energy networks requires interoperability and collaboration with many participants and competitors. The world is beginning to make progress in developing the data spaces, a concept that takes care of coordinating the technical, business, and legal aspects of data sharing.

The focus topics in the development of the Data Spaces are on the one hand the technical operations, such as the establishment of procedures, and the improvement of the user experience. On the other hand, the expansion of the community for the identification of innovative use cases and the development of business models is the second important building block for further development. Thirdly, internationalization is under consideration, so that initiatives are also being driven forward at global level (Grove, 2020).