The emergence of novel technologies is significantly contributing to the study of new approaches to the development of energy Cyber-Physical systems. Technologies like IoT, Big Data, Machine Learning and AI are becoming so tightly coupled to be considered as a singular technological framework. Such a framework is at the basis of the Digital Twin technology, which allows to interact with a real-world asset by referring to its digital counterpart. Being potentially applied to any kind of physical asset, the Digital Twin approach can create a synergy for a comprehensive modeling, monitoring, and forecasting of the same asset. In the energy domain, Digital Twins can facilitate the decision making by providing interactive dashboards to the stakeholders within a metaverse instance. These dashboards can support what-if analyses, forecasts on energy demand and production, and remote control of the physical assets to optimize their performance. This paper proposes a framework for developing a Cyber-Physical solution in the energy domain. The framework consists of three building blocks called Physical Asset, Data Infrastructure, and Digital Twin. The Physical Asset and the Digital Twin blocks correspond to the typical counterparts of a Cyber-Physical system, whilst the Data Infrastructure is delegated to support their synchronization and/or interaction. To assess the proposed framework, a real testbed was developed as Cyber-Physical system to implement the digital twin of a smart photovoltaic station.

Data spaces are driving smart city innovation by promoting interoperability, standardization, and predictive analytics, enabling proactive urban management and fostering innovation by creating a collaborative data ecosystem. The European Community is strongly promoting data spaces design initiatives. However, designers face complex challenges in complying with legal data regulations due to the lack of mature, unified solutions.This study aims to fill a gap in data space design literature by gathering key factors and scouting compliant implementations. It introduces European initiatives and their joint ventures, and identifies overlaps and lack of coordination between their proposals. Using these results, we formulate suggested actions and organize them into seven areas. For each given area, the most suitable European data space initiatives in terms of technical specifications and implementations are finally proposed to DS developers. The recommendations are intended to assist DS developers in identifying and navigating European DS design initiatives before selecting the most suitable proposal.

The growing importance of data spaces, which promote the exchange of data across various domains, has generated considerable attention. The existing body of research on the adoption of data space and federated data sharing has predominantly focused on technological factors. However, there is an increasing acknowledgment of the need for a more holistic perspective. This study presents an exploratory investigation based on the Grounded Theory methodology-based survey, that incorporates interviews with professionals from different sectors. Through this research, the most significant data key factors that drive the data space design as support for an Urban Digital Twin Platform. The findings obtained from this research indicate 4 main characteristics and 11 subcategories that are obtained in compliance with the European reference specifications in data space design. These findings can be used for matching the needs perceived from professionals with the European reference specifications. Regarding the matching results, some final considerations are provided.

Digital Twins (DTs) are the novel paradigm for the development of Cyber-Physical systems. The state of art presents several use cases in different domains, and one of the most complex examples is represented by the Urban Digital Twin (UDT), which aims to virtualize urban assets (e.g., buildings, mobility infrastructures, energy grids, waste management facilities, etc.) and build advanced analysis and prediction services upon a city’s digital representation. UDTs represent a formidable example of system of systems, as they are structured into a hierarchy of interconnected DT instances that process and share a huge amount of data subject to different access and usage policies.Regarding data management in complex distributed scenarios, Data Spaces are an emerging paradigm that aims at building a secure and privacy-preserving infrastructure to pool, access, share, process and use data. As a matter of fact, existing DTs solutions (not only in the urban domain) do not present a clear software architecture characterization and, moreover, they pay little attention to the data management aspects.To bridge this gap, in this paper we present the Digital Twin Space, an architectural proposal that aims to instantiate Data Spaces into DTs according to the guidelines set by relevant international projects. We use the UDT as a running example and we validate the model in the case of a smartPV panel, showing that the model matches the real cyber-physical system.