FoodDataQuest

Fuelling the quest for sustainable food systems with data-driven innovations

Abstract Pattern
FoodDataQuest logo.

The FoodDataQuest project aims to bring about more sustainable and healthy diets by involving stakeholders across the food supply chain. More data, including new data sources, unconventional players, and enhanced data sharing will provide insights for the food industry that drive the move to sustainable and healthy diets. The project will tackle social and environmental challenges in the food supply chain, which currently result in food insecurity, unhealthy diets, and environmental harms. Through a multi-actor approach, FoodDataQuest will co-create, and test advanced data-driven solutions powered by Artificial Intelligence (AI) and Machine Learning (ML) algorithms. This initiative stands as a beacon for a fair, healthy, and environmentally friendly food system, balancing data openness with the protection of stakeholders’ private and sensitive information.

FoodDataQuest will pioneer four transformative use cases:

  1.  A DNA-data driven AI system for Food Sustainability and Traceability: Developed by AGROKNOW and BIOCOS, this approach aims to enhance the olive oil supply chain’s sustainability and traceability, valorizing local species and producers while optimizing strategies against climatic challenges.
  2.  Reimagining Food Services in Healthcare: This initiative, led by Intrasoft, SYREON, University Medical Center Maribor, and GS1, focuses on improving patient health and reducing food waste in hospitals and elderly care homes, shifting towards nutritious, sustainable food options.
  3.  F2F Food Sustainability Insights: Led by EV ILVO, GS1, Colruyt Group, Nijsen company, and Palau Project, this use-case promotes a shift to sustainable, healthy diets byprocessing a blend of agricultural and unconventional data to support food quality and consumer choices.
  4.  Enhancing Consumer Awareness of Eco-Friendly Choices: Coordinated by Wageningen University, with Tampere University and Palau Project as partners, this use-case aims to provide consumers with personalized eco-friendly choices through high-density data-driven communication, utilizing AI technologies to guide sustainable lifestyle decisions.

FoodDataQuest has five main specific objectives:

  •  Establish a methodological framework encompassing methods, technologies, and open data standards.
  •  Analyse the current data-sharing landscape, focusing on emerging digital technologies.
  •  Demonstrate effectiveness through co-creation and validation of four use-cases.
  •  Introduce project results to policy-making organizations and standardization initiatives.
  •  Ensure widespread communication and scientific dissemination, including international links, raising awareness, and facilitating technology transfer and rapid uptake.

FoodDataQuest output

Using 4 use cases, the FoodDataQuest project aims to bring about more sustainable and healthy diets by involving stakeholders across the food supply chain. More data, including new data sources, unconventional players, and enhanced data sharing will provide insights for the food industry that drive the move to sustainable and healthy diets.