GSS EU Science Funding Gateway

Building on the Data Space for Smart Communities and the EU Local Digital Twin (LDT) Toolbox, both supported by the WP 2021-2022, and in synergy with the action “Developing CitiVerse” (see 2.3.2), the main objective of this action is to consolidate existing results and move towards an ecosystem of mature and networked LDTs across the EU to help cities and communities achieve economies of scale when developing their data platform and LDT services.

The selected proposal will manage a community of projects selected by cascading funding mechanism. The work of these projects will be implemented through three main work strands:

Work strand 1: Connect existing LDTs at EU level and lay down the foundations of an EU LDT ecosystem. When connecting LDTs, and their related data sets, projects should align with the smart cloud-to-edge middleware platform Simpl to achieve interoperability and make use of horizontal services available under the Digital Europe programme such as the Smart Communities dataspace blueprint, the EU data cloud infrastructure and the EU LDT toolbox.

Work strand 2: Launch new pilot LDT services based on common needs of cities and communities to enhance interoperability and collaboration. The services should be tested in real-life conditions and expand the EU LDT ecosystem by making use of and contributing to the development of the EU LDT toolbox catalogue. The pilots should include at least the following activities:

• designing real life use cases based on open and interoperable data sets across sectors. The use of these data sets should follow requirements of the data space for smart cities and communities’ blueprint;
• building and deploying the pilot services on LDT platforms at city/community level with real use case data;
• defining roadmaps for making available the LDT-based services on the EU LDT toolbox catalogue.

Work strand 3: Add new complex AI-based components to the forthcoming EU LDT toolbox to address the needs of cities/communities:

• Develop and deliver new AI-based services to create simulations, predictive models and forecast in a variety of sectors and use cases amongst which the New European Bauhaus, public services and communities’ resilience;
• Develop and deliver solutions for designing, optimising, and testing urban policies in dynamic complex environments with several interwoven sectors (e.g., traffic volume and pollution levels). AI classical optimization may be complemented with self-organised bottom-up solutions that will offer the necessary adaptability and robustness;
• Develop and deliver new complex AI-based services related to citizen’s engagement, with or without the use of eXtended Reality technology to address aspects of the New European Bauhaus initiative and implement a sustainable, democratic and citizen-centric CitiVerse.

To maximize the scale-up and reusability of the new services, these should be designed in such a way that they can be adopted by different maturity levels LDT architectures.