Skip to main content

About

Agri-food data space demonstrator for sovereign data sharing services and Artificial Intelligence.​

This demonstrator is proposed with a significant staffing load for the advising and development of use cases to support participants who have shown interest but have not had the opportunity or the capacity to present their use cases separately for this call.

In addition, it involves a wide 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 part since it wants to maintain a close collaboration with the future European Common 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 the equity of the participants and their non-discrimination, as well as their sustainability.

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

Intermediation for data processing will be done using compute-to-data technology, so that data sovereignty can be ensured by design. This service will be contracted with a cloud "data room" provider, which will provide the high-performance environment to perform data computing, including Artificial Intelligence processes.

The data space governance code will allow the enactment of policies for access and use of resources. 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 that uses distributed ledger technologies, without real economic value during the demonstration phase, but which will allow all participants to explore possible data economies for the future sustainability of the data space.

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

The demonstrator will be based on FAIR principles to facilitate the search for 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 conditions of use, and open data sources, especially high-value and highly relevant datasets in the agri-food sector 1. Especially open data sources relevant to the agri-food sector such as those generated by the Galileo and Copernicus programs.

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

To facilitate the interoperability and reuse 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 vocabularies of the agri-food domain.

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 code repositories.

The services of a company that provides the Pontus-X components will be contracted to facilitate the integration of the demonstrator with other data spaces that are already in operation in this ecosystem. In addition, this company will provide the components in a dedicated way for the test 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 guarantee data privacy and sovereignty by design, so that it can be ensured that data is processed in a protected and confidential manner. They also allow federated learning to be implemented.

  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, therefore multiple connected data spaces.

  4. Smart Contract technologies that allow the implementation of data monetization mechanisms, services and computational costs 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 the sovereignty of participants and the self-management of attributes related to their identity.

Footnotes​

  1. Chamorro-Padial, J., García, R., & Gil, R. (2024). A systematic review of open data in agriculture. Computers and Electronics in Agriculture, 219, 108775. DOI: 10.1016/j.compag.2024.108775 ↩