In an era of increasing environmental challenges and food security concerns, the role of data in shaping sustainable food systems has become more crucial than ever.
The presentations in this session will touch upon the following key themes:
Data and digital innovation in agri-food systems: How to shape the data economy for food – Cor Verdouw (WUR)
The demand for healthy, sustainable, and affordable food in today’s complex and volatile business environment. Agri-food production is rapidly changing into data-driven, smart systems, enabled by emerging digital technologies.
This presentation explores the impact of digital innovation on the agri-food system and highlights some recent European projects that are addressing the transition toward data-driven agri-food systems.
AgData Interoperability – Towards a European Data Space – Eva Maes (ILVO)
The European Data Strategy aims to create a single data market, allowing optimal data use within Europe. A key component of this strategy is the development of Common European Data Spaces in strategic fields.
To avoid having every chain partner connected to every possible DISP, seamless collaboration between those platforms is indispensable. This study investigated the technical needs to realise interoperability between two DISPs, being the French AgDataHub en Belgian DjustConnect.
Data4Food2030 case Amsterdam: AI-based benchmarking for food loss & waste (FLW) quantification in Amsterdam Metropolitan Area - Xuezhen Guo (WUR)
In the "AMAFLOW" use case of the Data4Food2030 project, the goal is to quantify the geographical distribution of food loss and waste within the Amsterdam Metropolitan Area.
Due to inherent uncertainties and potential inaccuracies within the primary data sources needed, it is critical to establish an objective method to verify and validate the results.
Practical Applications of Generative AI in Behaviour Science – Jos van den Puttelaar (WUR)
This workshop explores the potential of generative AI in consumer behaviour sciences, focusing on its role in designing dynamic, personalized interventions for sustainable food consumption.
It will examine how large language models (LLMs) can address the scalability challenges of hyper-personalization, potentially making complex behaviour change targets more accessible across society.
Privacy Calculus and AI Transparency in Personalized Food Choices – Liam Dwyer (WUR)
This fifteen-minute session explores the critical intersection of AI-driven personalization in food choices and consumer privacy concerns, framed within the context of the EU AI Act. As AI increasingly shapes our dietary decisions, understanding the "privacy calculus" – how consumers weigh perceived benefits against potential privacy risks – becomes crucial for both researchers and practitioners.
If you are attending the 38th EFFoST International Conference, you can join this session on Tuesday 12 November from 10:45 to 12:15 CET.