Determination of metrics of emerging risk (DEMETER)
This third-party funded project is conducted in the framework of the BfR research programme on functional analytics and early risk detection.
EFSA grant number: GP/EFSA/AFSCO/2016/01
Project homepage: -
The early identification of emerging risks in the food (and feed) chain is of paramount importance if the European consumer is to be protected through timely and effective preventive measures. lncreased global trade is making food chains more complex, both in terms of geographical spread and the rapid distribution of goods. The increasing complexity of the chain makes it more difficult to oversee and assess all drivers of change for food safety risks in a particular chain. As such, yesterday's emerging issue in one area may be tomorrow's crisis in a different place. Dealing with this complexity requires a high degree of scientific and technical expertise.
The use of new data mining and data science solutions (digital technologies) can help to overcome current constraints to enable identification of emerging food safety issues at an early stage so that timely measures can be taken to prevent these becoming a food safety risk. The advantages of digital/data-driven solutions are numerous. The process of emerging risks detection in the European Union must therefore utilise digital technologies and the application of "big data" analysis to identify emerging food safety risks across an increasingly complex and geographically dispersed food web.
The objectives and research proposed in this project proposal are specifically designed to support current (and future) EFSA procedures for emerging risk identification by providing a set of integrated, open-source solutions that will allow EFSA and EU Member State authorities to share data, knowledge and methods in a rapid and effective manner. This main objective will be achieved by activities carried out in five integrated work packages (WP).
BfR parts of the project:
The BfR is involved in four of five WP:
WP1 Data retrieval and validation pipelines: This work package will identify, disclose and develop automated data retrieval methods for the identification of emerging issues on the basis of a highly customisable open-source data analysis framework (KNIME). These resources allow the generation of web-based services as developed in WP3 and WP4.
WP2 Methodological resources: This work package will identify relevant data on emerging risks in relation to end-user behaviour from expert elicitation, citizen science and the behavioural science literature. These data streams will provide inputs into the emerging risk identification to show the possibilities of including social science data in emerging risk identification efforts.
WP3 Platform requirements: In this WP, barriers to, and facilitators of, EREN member state utilisation of the current system will be identified. Foresight methodologies will be applied to identify what will be needed in terms of the desired Emerging Risk Knowledge Exchange Platform (ERKEP) in the future. A Graphical User Interface (GUI) that meets the needs of end-users will be developed for ERKEP and refined through beta testing. Finally, a training package will be developed to build capacity across EREN member states using the new platform.
WP4 Platform implementation: The objective of WP4 is to facilitate software-technical implementation of the desired collaborative platform (ERKEP) supporting current EFSA procedures for emerging risks identification. Specifically this platform will allow EU Member State authorities and EFSA to share knowledge, data and methods for the identification of emerging food-related risks in a rapid and effective manner.
- Wageningen University, The Netherlands (coordination)
- University of Newcastle upon Tyne, UK
- National Food Chain Safety Office, Hungary