Can data be used as a basis for warnings about unhealthy food, together with or instead of on-pack information? And how can an app help cocoa farmers in Peru increase their yields while helping the government fight deforestation? Researchers are answering such questions with the aid of robots, sensors, machine learning, artificial intelligence and shared data infrastructures.
The Knowledge Base programmes can be imagined as interlinked pillars leading up to the societal challenges we face. These pillars rest on the foundation formed by the Data Driven & High Tech Knowledge Base programme.
Jene van der Heide heads this KB programme. “We want to encourage a different research mindset: the data-driven mindset. After all, you don't know what patterns are hidden in the data. It is important to know how that works and whether you can validate the results or combine them with results from mechanistic models. This issue is also being addressed by the Wageningen Modelling Group.”
In this chapter two projects are highlighted to illustrate the important work of the KB-programme Data-driven en High tech.
Jene van der Heide Programme leader KB-38 Data-driven and High Tech
Data make digital diet truly personalised
Jene van der Heide: “We develop apps to encourage healthy food choices. The aim of such apps is clear, but the challenge is how to handle the (big) data and how to present it in a consumer friendly way that’s tailored to personal requirements.”
Figuring out language
Jene van der Heide: “We want to create a data-driven mindset among researchers. So we have also developed a data-driven tool to help researchers set up collaborations in multidisciplinary projects.”