Food Systems Seismology

Food Systems Seismology will exploit heterogenous data generated and collected by and through WUR partner organizations, such as 4TU, FAO etc to release early warnings of disruptions within food systems globally. The project will contribute to the development of a global data-ecosystem that makes it possible to detect system-wide risks as or before they occur.

Summary Shocks and disruptions in food systems can have far-reaching consequences with respect to global food security. General theory on systems resilience predicts that major changes in systems are preceded by early warning signals (e.g. critical slowing down, spatial patterns, autocorrelation). For complex socio-techno-ecological systems with multiple relevant outputs these early warning signals are however not trivially identified. Furthermore, domain knowledge can identify specific (combinations of) parameters that make a system, or components more vulnerable to disturbances.

Food systems seismology combines data science techniques with a deep understanding of the structure and functioning of food systems to identify potential early warning signals of system change and produce actionable knowledge with regard to managing the vulnerabilities in the system, preparing for shocks and preventing loss of food security.

Within food systems Wageningen UR is in contact with most stakeholders through partnerships and (contract) research. At the same time Wageningen does not hold, collect or maintain major (international & standardized) databases with real-time data of the status within food systems. With this project Wageningen UR will work towards setting up a data-exchange infrastructure to enable the combined and anonymous analysis of operational data from diverse sets of partners.

The project focusses on three aspects:

a. Data engineering: the technical side of sharing data: which possibilities can or need to be created.

b. Data science: the combination of domain knowledge and data analysis techniques: which signals are to be extracted from the data, and what do they tell us.

c. Data economy: the added value of dataexchange: how to organise the sharing of data and how to ensure that the generated insights arrive there where they can make the difference.

For each these aspects the project will outline the current situation, identify realistic medium term ambitions and plan the realization of these ambitions, both scientifically and operational.