Emerging risk identification by applying data analytical tools

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Abstract

The working programme ‘Emerging risk identification by applying data analytical tools’ was delivered by the Digital Food Chain Education, Research, Development, and Innovation Institute (Digital Food Institute, DFI) on the field of emerging risks at the University of Veterinary Medicine Budapest, Hungary. The Institute is the University's research and education unit that provides data analysis and research along the whole food chain and takes networking in this area to a new level. The Fellow joined the hub of experts and researchers in the field of food chain safety data analysis, responsible for protecting public health concerning food in Hungary. The programme consisted of several different activities to provide an overview of the different tools that can be employed in the emerging risk identification process and prepare various stakeholders for new food chain safety issues. The programme was split into four modules to run over the one-year fellowship covering different areas of data analysis and emerging risk identification. The aim was to be fully integrated with the organisation's work experience, increase knowledge of scientific aspects relevant in the field of data analysis and visualisation tools in the emerging risk identification area, and implement the results into various EU stakeholders' environments assessments.

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APA

Palmas, E., Engelhardt, T., Farkas, Z., Csorba, S., Országh, E., & Józwiak, Á. B. (2022). Emerging risk identification by applying data analytical tools. EFSA Journal, 20(S2). https://doi.org/10.2903/j.efsa.2022.e200913

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