ETD

• cybersecurity
• data spaces
• international data spaces

The thesis conducts the design and implementation of an International Data Spaces (IDS)-compliant agricultural data space, with a focus on the European regulatory framework and the Italian agricultural context. Its main objective is to demonstrate how an IDS-based architecture can enable secure, interoperable, and sovereign data sharing in agriculture, addressing the current fragmentation of data infrastructures and reducing administrative burdens on farmers.
The first part introduces the foundational concepts of European data spaces, starting from the Common European Data Spaces (CEDS) initiative, which represents the European Union’s strategic vision for a federated and trustworthy data economy. Within this framework, the IDS model is presented as a mature reference architecture centered on data sovereignty, meaning that data owners retain control over how their data are used even after sharing. The thesis describes the IDS Reference Architecture Model (IDS-RAM), structured into five layers and three cross-cutting perspectives. Subsequently an analysis of the Data Space Protocol (DSP) is presented, which standardizes interactions among participants through connectors, dataset discovery, contract negotiation, authentication, and secure data exchange under agreed usage policies.
The second chapter focuses on the European regulatory framework, highlighting that data spaces are not purely technical systems but also regulations-dependant infrastructures. The analysis covers the General Data Protection Regulation (GDPR), the Data Governance Act (DGA), and the Data Act, showing how these instruments form a layered and complementary legal ecosystem. GDPR establishes strict rules for personal data protection, influencing accountability, transparency, and usage control mechanisms within data spaces. The DGA introduces governance rules to foster trust, regulate data intermediation services, and promote voluntary data sharing through data altruism. The Data Act strengthens users’ rights to access data generated by connected products and makes interoperability a legally binding requirement, directly affecting the design of data-sharing systems.
The third part analyses the agricultural sector in Italy, which is characterized by heterogeneous and fragmented data flows. The thesis proposes an agricultural data taxonomy consisting of four categories: farm structure data, processing-related data, administrative data, and communication data. It then analyzes key data flows, particularly those related to Common Agricultural Policy (CAP) subsidies and machine-generated data from precision farming technologies. The study highlights significant inefficiencies in current administrative processes, where farmers must repeatedly submit overlapping information to multiple authorities, as well as issues of vendor lock-in and limited control over data generated by agricultural machinery.
In the final part, the thesis shows how adopting an IDS-based agricultural data space could substantially mitigate these problems, by enabling controlled access to authoritative data sources under clearly defined and enforceable usage policies. IDS principles can therefore reduce duplication, enhance interoperability, and increase transparency and trust among participants. More concretely, the final chapters present practical use cases and demonstrators, implemented using the official IDS Testbed, following the previously shown data flows.
The implementation follows a reproducible and modular approach: the testing environment is retrieved from the official public repository of the International Data Spaces Association on GitHub, ensuring traceability and version control. The environment, including connectors and supporting infrastructure services, is then deployed using Docker and Docker Compose, allowing an isolated and platform-independent execution. Interaction between connectors, including catalog queries, contract negotiation, and data access requests, is validated through Postman, which is used to test and verify the correctness of the Data Space Protocol interactions and REST API endpoints.