FSI

The proposed programme aims to build an international community of practice that will co-develop and share common standards, methods, and tools for the use of data to monitor and predict food security ouctomes across different contexts and scales.

The programme is centred around the concept of Food Security Intelligence (FSI), which we define as a system for the collaborative generation and sharing of comprehensive, actionable knowledge, encompassing the food system and its dependencies and which aims to help a specific community of stakeholders to make better decisions when dealing with food and nutrition security challenges at a chosen scale and to offer clear value to all participants involved.

The research in this programme will be centred around four specific case studies, which represent different existing intelligence ecosystems, uniting diverse groups of stakeholders around specific food security challenges. A team of complementary experts, together with five PhDs, a postdoc and an EngD, will work around the different case studies to contribute less burdensome, time-consuming and privacy sensitive methods of data collection, advanced analytical and machine learning methods for the analysis, integration and interpretation of data, and procedures and best practices to ensure equitable, safe and just collection, access and utilization of data. In addition, the programme will provide targeted capacity building on methods and procedures to members of the FSI community, strengthening regional capacities in data science and intelligence for food security in at least four low- and middle-income countries in Africa.

Together with local partners in Senegal, we will investigate causal machine learning methods in the context of sustainable farming for smallholder communities.