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The Agri-Food Data Space Demonstrator for Sovereign Data Sharing and Artificial Intelligence Services​

This demonstrator is conceived with a significant staff allocation for advisory and use case development to support participants who have shown interest but have not had the opportunity or capacity to submit their use cases separately for this call.

Furthermore, it involves a broad and diverse network of participants interested in being part of the demonstrator, broadly representing the different types of actors involved in the agri-food sector, especially the productive side, as close collaboration is sought with the future Common European Agricultural Data Space (CEADS), which focuses on this sector.

The data space will be governed by an explicit governance code, ensuring greater transparency, with special attention to preserving participant fairness and non-discrimination, as well as its sustainability.

Participants will play different roles, including data producers and consumers, data consumers and service providers, IT service providers, and data space ecosystem service operators. Computing providers will also act as data intermediaries, particularly in the role of a trusted third party where information is processed.

Data processing intermediation will be carried out using compute-to-data technology, so that data sovereignty can be guaranteed by design. This service will be contracted with a cloud "data room" provider, who will provide the high-performance environment for data computation, including Artificial Intelligence processes.

The data space governance code will allow for the enactment of resource access and usage policies. It will also define mechanisms to create incentives for sharing data and services, as well as for the sustainability of the data space itself. These mechanisms will be based on an electronic Euro using distributed ledger technologies, without real economic value during the demonstration phase, but which will allow all participants to explore potential data economies for the future sustainability of the data space.

The distributed ledger infrastructure used for data space monetization will also enable tracking of data space transactions and their auditing. Based on this ledger, conflict resolution mechanisms stipulated in the governance code itself will also be deployed.

The demonstrator will be based on FAIR principles to facilitate the discovery and access to shared resources through it, and to make them interoperable and reusable. To this end, all resources will have descriptions of their characteristics and conditions of use, using semantic technologies that facilitate their automatic processing.

The data space will host both proprietary resources (data and services for their processing) shared under terms of use, as well as open data sources, especially high-value and highly relevant datasets in the agri-food sector (Chamorro-Padial, García, Gil, 2024). Especially open data sources relevant to the agri-food sector such as those generated by the Galileo and Copernicus programs.

Services shared through the data space will include algorithms that implement mechanisms to validate the data quality level provided by participants. These algorithms, for example, Exploratory Data Analysis (EDA), can be applied to data to calculate quality metrics while ensuring its sovereignty. This will be due to the very design of the data space, which implements compute-to-data mechanisms that can ensure the owner does not lose control over their data.

To facilitate the interoperability and reusability of data and services, the data space will integrate data transformation services into representations based on semantic technologies that will refer to formalizations such as ontologies of common agri-food domain vocabularies.

The proposed demonstrator will be deployed using the components of the Pontus-X1 data space ecosystem. These components are open source, and any new development or improvement made during the project will be shared in the same way as in the Pontus-X open-source repositories.

The services of a company providing Pontus-X components will be contracted to facilitate the integration of the demonstrator with other data spaces already underway in this ecosystem. Furthermore, this company will provide the components in a dedicated manner for the trial version of the data space, which will operate independently. These components, both in their shared and dedicated versions, provide the following technologies:

  1. "Compute-to-data" technologies to ensure data privacy and sovereignty by design, so that data can be guaranteed to be processed in a protected and confidential manner. They also enable the implementation of federated learning.

  2. Mechanisms for sharing data, but also data processing services, preferably encapsulated as containers (Docker and Kubernetes) with all their code and dependencies to facilitate their portability and execution in the "compute-to-data" environment. These services include advanced descriptive, predictive, and prescriptive analytics tools.

  3. Distributed ledger technologies that allow tracing all transactions carried out in the data space ecosystem, and therefore multiple connected data spaces.

  4. Smart Contract technologies that enable the implementation of data, service, and computational cost monetization mechanisms of the "compute-to-data" mechanism. Distributed ledger and smart contracts based on the EVM (Ethereum Virtual Machine) standard. They facilitate the independence of the underlying technological solution, enabling its portability and deployment across different infrastructures.

  5. Digital Wallet technologies to ensure participant sovereignty and self-management of identity-related attributes.