# Building Cyber-Resilient Smart Grids with Digital Twins and Data Spaces
## 2 Digital Twins and Data Spaces
### Data Spaces  
The European data strategy is geared towards the creation of a single, unified data market to boost Europe's competitive edge while preserving its data sovereignty. This strategy encourages the establishment of shared European data spaces, which are designed to enhance data accessibility for economic and societal benefits while ensuring that data producers, whether businesses or individuals, retain control and rights over their data. The management of the European data space adheres to core European values and complies with pertinent legislation, such as the General Data Protection Regulation (GDPR) and the recently updated Network and Information Systems Directive (NIS2). These regulations are pivotal in guaranteeing a secure and seamless data flow within a safeguarded ecosystem. Moreover, initiatives like the International Data Spaces Association (IDSA), GAIA-X, and FIWARE Foundation are pivotal in driving the adoption of data-centric technologies and establishing data sovereignty. FIWARE has also emerged as a key platform that propels the development and uptake of innovative, data-centric technologies. It is an open-source platform that comes equipped with an extensive suite of standards, APIs, and tools tailored for crafting and managing intelligent applications and services. FIWARE's main objectives are to ensure the interoperability, reusability, and scalability of applications across a variety of sectors. With FIWARE, developers are empowered to devise and implement applications that leverage real-time data from diverse sources, such as sensors, IoT devices, and pre-existing systems. It provides a sturdy infrastructure for data handling, processing, and analysis, and also supports smooth integration with cloud services and other external platforms. Utilizing FIWARE enables developers to create state-of-the-art applications that exploit the full potential of real-time data, fostering innovation and operational efficiency across various industries. To encapsulate the concept of the data space (\(\mathcal{DS}\)), in a FIWARE-compliant view, we introduce the following notation:  
\[\mathcal{DS}=\langle D,P,S,St,G\rangle \tag{5}\]  
where:  
* \(D=\{d_{1},d_{2},\ldots,d_{n}\}\) represents a set of datasets. * \(P=\{p_{1},p_{2},\ldots,p_{m}\}\) denotes a set of policies governing the data space. * \(S=\{s_{1},s_{2},\ldots,s_{k}\}\) is a set of services that facilitate data processing and analysis. * \(St=\{st_{1},st_{2},\ldots,st_{j}\}\) indicates a set of stakeholders involved in the data space. * \(G:\mathcal{S}\rightarrow\{\textit{compliant},\textit{non-compliant}\}\) is a governance function for the data space that is responsible for evaluating the compliance of services with the established regulatory and policy framework of the data space. This function examines each service to ensure it adheres to regulations such as the General Data Protection Regulation (GDPR) and the Data Act, maintaining secure and sovereign data operations. The following Algorithm 1 evaluates whether a data service adheres to the Data Act's regulatory framework by conducting a streamlined compliance check.