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Application of data science in risk assessment and early warning


Published on: Mon, 27 Aug 2018 00:00:00 +0200

The currently applied approaches, procedures and tools used for the identification of emerging risks vary greatly among Member States of the EU. EFSA established a structured approach for emerging risk identification that mainly consists of systematically searching, collecting, collating and analysing information and data. In addition, EFSA concluded that new methodologies and tools are needed to facilitate efficient and transparent sharing of data, knowledge and methods in the field of emerging risk identification between Member States. As the result of an open call issued by EFSA, the ‘Determination and metrics of emerging risks’ (DEMETER) project was established in spring 2017 to support current and future procedures for identification of emerging risks. As the Bundesinstitut für Risikobewertung (BfR) hosting site is involved in the DEMETER project, as well as in several other software development activities in the area of quantitative microbiological risk assessment, the fellow had the opportunity to play an active role in the project work and development of the running DEMETER project. The training and close integration in the project team enabled the fellow to make significant contributions, e.g. with the creation of new open source data processing workflows and by contributing to the Emerging Risk Knowledge Exchange Platform (ERKEP) Framework Concept Note. Besides DEMETER, the fellow participated in other activities of the Unit for Food Technologies, Supply Chains and Food Defence, including testing and applying several BfR open source software tools which had been developed in previous projects and that are used in microbiological risk assessment (e.g. Predictive Microbial Modelling Lab (PMM‐Lab)) or as automatic data retrieval systems (e.g. SiLeBAT NewsRadar) – see
© European Food Safety Authority, 2015

Application of data science in risk assessment and early warning

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