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Development of Use Cases in Agri-Food Data Spaces

This guide outlines the key steps to design and implement use cases within an agri-food data space. Inspired by the model proposed by the Oficina del Dato, it provides a practical approach to developing solutions based on ethical, secure, and federated data sharing.

Use cases aim to address specific challenges in the agri-food sector by leveraging the value created through data sharing among multiple stakeholders. They rely on common technical infrastructures and collaborative governance models that ensure interoperability, trust, and data sovereignty.

What is a use case?​

A use case is a concrete application of data shared between different stakeholders to solve a sectoral or societal need. In the agri-food context, this could include initiatives to reduce fertilizer use, monitor animal welfare, or generate sustainability certifications based on real data.

Within the AgrospAI project, several real examples of use cases developed in the agri-food data space can be found in the Use Cases section.

Phases of use case development​

The development of a use case in a data space follows a structured model with 8 phases [1]. These phases ensure that the solution is viable, scalable, and sustainable, and aligned with the principles of interoperability, trust, and data sovereignty.

Fig. 1. Use case development process in a data space. Visual representation of the process. (source: [1])

1. Definition of the business problem​

A group of participants identifies a common opportunity to share and exploit data. This opportunity may focus on:

  • New products or services.
  • Improved operational efficiency.
  • Joint resolution of sector-specific challenges.

2. Data-driven modeling​

Relevant information is structured to support informed decision-making. This phase includes:

  • Defining a data model.
  • Incorporating tools such as AI or advanced analytics.
  • Focusing the development on data-driven decisions.

3. Consensus and requirements​

A collaboration model is built among participants:

  • Agreement on participation rules.
  • Establishment of shared policies.
  • Definition of a governance and trust model.

4. Technical design of the use case​

A technical blueprint is created based on the solutions and agreements reached. This blueprint may rely on:

  • Existing models.
  • Reusable templates or components.
  • Common technical recommendations from the data space.

5. Solution development​

The solution is built based on the blueprint. The use case may reuse or adapt existing technologies for efficiency.

6. Technological development​

The necessary tools are selected and integrated to enable the data lifecycle:

  • Platforms and infrastructures.
  • Interoperability components.
  • Tools for access, governance, traceability, etc.

7. Integration and deployment​

  • The use case is integrated into the data space (if one already exists).
  • Functional and acceptance tests are performed.
  • Compliance with agreements and requirements is ensured before launch.

8. Operation and scaling​

The use case is operational and generates real value:

  • It may scale to other stakeholders or similar cases.
  • The data space grows in a federated and sustainable way.
  • A continuous improvement model is activated.

Use case evaluation and design​

Once the key phases of use case development in a data space are understood, it is essential to rely on methodological tools that help evaluate its feasibility and design it properly. For this purpose, the Oficina del Dato has published two complementary guides [2]:

  • One to assess the feasibility of a use case.
  • Another to design its implementation.

These guides help transform an initial idea into a scalable, sustainable use case aligned with the principles of data spaces.

Feasibility assessment​

This guide enables the generation, description, and evaluation of use case ideas involving data sharing. It proposes a methodology with five key steps, whose final goal is to decide whether the scenario is feasible:

  1. Use case generation: identifying a specific need that could be addressed through data sharing.
  2. Scope definition: outlining goals, involved stakeholders, and expected benefits.
  3. Potential evaluation: analyzing the added value in social, economic, or environmental terms.
  4. Interaction complexity analysis: assessing the required level of collaboration among stakeholders.
  5. Final feasibility decision: deciding whether to move forward with the design and implementation.

Fig. 2. Use case feasibility assessment. (source: [2])

📄 The guide includes a spreadsheet template with key questions to systematically complete each step. Download feasibility assessment template.

Use case design​

If the use case is deemed feasible, the next stage is its detailed design, focusing on scalability and future reuse.

The guide approaches design through the following actions:

  • Clearly define the objective and scope.
  • Identify the functionalities needed to share and exploit data.
  • Establish the technological, organizational, and legal enablers.

Fig. 3. Use case design. (source: [2])

📄 A spreadsheet with guiding questions is also provided to support the design, along with real-world examples. Download use case design template.

Conclusion​

The two guides published by the Oficina del Dato offer a clear, practical, and applicable methodological framework to develop use cases in data spaces—from the initial idea to implementation.

Together, they ensure that use cases are not only feasible but also scalable, sustainable, and applicable in real contexts. This is especially relevant in the agri-food sector, where collaboration and data sharing are essential to drive a fair and efficient digital transformation based on sovereignty and trust.

Thus, any entity interested in participating in a data space has a structured path to evaluate, design, and deploy use cases that deliver real value.

References​

[1] Use case development model for data spaces – datos.gob.es. Available at: https://datos.gob.es/es/blog/modelo-de-desarrollo-de-casos-de-uso-para-espacios-de-datos

[2] How to evaluate and design use cases for data spaces – datos.gob.es. Available at: https://datos.gob.es/es/blog/como-evaluar-y-disenar-casos-de-uso-para-espacios-de-datos-guias-para-facilitar-el-camino