Critical Entities (CEs), intended as systems providing essential services for maintaining vital societal functions and economic activities, and smart urban communities, which leverage smart technologies to benefit stakeholders and citizens of an interconnected city, represent nowadays two increasingly growing areas for the application of Digital Twins (DTs), which are virtual replicas that allow to simulate and analyse the behaviour of a complex system under different conditions of physical assets as pivotal as transportation, energy, or water systems, thus supporting their effective management in smart cities, industries, and corporations. DTs are especially helpful in the decision-making process as they enable operators to identify potential issues and optimise system performances without disrupting the services provided to the public, as well as to industrial and business stakeholders. In such a scenario, the role of data is pivotal as the accuracy and usefulness of DTs strongly depend on data availability and data quality in order to achieve a true digital resilience of critical infrastructures.

Therefore, the promising integration with dataspaces, intended as virtual spaces for managing and aggregating heterogeneous real-time and historical data sources, can further enhance effectiveness and applicability of DTs for critical entities. Several current initiatives aimed at proposing dedicated architectures (as the International Data Spaces, IDS), collaborative data sharing environments (as the European data strategy), and architectural standards (as the GAIA-X initiative) enabling trusted data exchange in accordance with European data protection guidelines, are nowadays paving the way to adopt dataspaces as a fundamental building block of truly data-driven DTs for critical entities.

The enabling role of dataspaces is rapidly gaining momentum in situations where centralised cloud-based data storage solutions have to be integrated with highly-distributed edge data processing. Furthermore, data sovereignty requirements in dataspaces for DTs for critical entities constitute another engaging challenge, as it is crucial to ensure that data are secured and protected from unauthorised access, misuse, or deletion, particularly when the right of a country or an organisation to keep the ownership and control over its own data is at stake. This aspect is even more relevant in specific geographical regions, as the recent Critical Entity Resilience Directive (CER) of the European Union asks EU Member States to define national resilience harmonisation strategies and risk assessment frameworks, which would greatly benefit from the adoption of data-driven approaches. Moreover, the data generated by a DT for a critical entity usually need to be shared with other stakeholders, such as national and international regulatory authorities or maintenance contracting companies, and data sovereignty must be ensured without hindering data interoperability, sharing, and usage.

Consequently, high-quality dataspaces capable of integrating and managing extremely variegated data sources, allowing data-interoperability among multiple systems and organisations, and supporting data-intensive processing and analytics are needed, with a specific focus on scalability, privacy, and security requirements.

This workshop, previously known under the acronym of DS4DTCCI and now in its second year at the IEEE Big Data flagship conference in the big data sector, aims to bring together researchers and practitioners not only from computer science and data science but also from the industry sector and from governmental bodies. The workshop will represent a fruitful opportunity for discussing the latest research developments and the ongoing challenges in the field, as well as for fostering collaborations and networking.