Partners from Netcompany-Intrasoft published the project’s Deliverable 2.2 (D2.2), which outlines the design of the Reference Architecture and Data Model for FoodDataQuest (FDQ), defining the technical foundation for secure, trustworthy, and interoperable private data sharing across the agri-food value chain. As a central output of Work Package 2 (WP2), it builds on the FDQ Framework from D2.1 and incorporates insights from WP1 on current data practices and challenges. By specifying the architecture, data structures, and component interactions needed to support the four FDQ Use Cases, D2.2 ensures a smooth transition from research in WP1 to implementation in WP3. 

At the heart of D2.2 is the Reference Architecture, designed using the 4+1 View Model to capture the system’s functional, operational, and deployment aspects in a structured and stakeholder-friendly manner. The architecture aligns with the FDQ Framework (D2.1) by embedding key principles, including interoperability, trust, privacy, and ethical data use into each layer. Organized into data source, persistence, business logic, presentation, and Data Space Common Services layers, it delivers modularity, maintainability, and interoperability. Key achievements include adoption of a layered design compatible with EU Data Space initiatives, alignment with technical and legal standards for secure and privacy-preserving data sharing, integration of stakeholder insights and Use Case requirements, and a unified structure supporting sovereign, policy-aware data exchange across diverse agri-food actors. 

Within the FDQ Reference Architecture, the Data Space layer provides a decentralized, federated environment where multiple organizations can exchange and use data securely while retaining control over their own information, focusing on the Agricultural and Smart Communities domains. It builds on the IDSA framework, which standardizes how data assets, participants, and usage policies are described. Drawing from the IDSA Information Model, the D2.2 Data Model extends it with domain-specific ontologies, vocabularies, and metadata to create a semantic, FAIR-aligned structure that enables consistent, interoperable, and machine-readable data exchange across diverse datasets.  

The next step for D2.2 is validating the Reference Architecture and Data Model through a phased, Use Case-driven approach within WP3, where the four Use Cases are implemented. Each Use Case will test specific aspects, from data provenance and semantic interoperability to user-facing features and consent handling. Validation will be closely integrated with WP3 activities, allowing iterative refinement based on feedback from Use Case teams, stakeholders, and legal assessments. Insights from these pilots will guide updates to improve modularity, data flows, and governance features, ensuring the architecture and data model remain robust, scalable, and practical for real-world use. 

If you are interested in the project’s deliverables, you can check and download them on the resource page here.