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Emerging risk identification by applying data analytical tools

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, Hu...

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Autores principales: Palmas, Elisa, Engelhardt, Tekla, Farkas, Zsuzsa, Csorba, Szilveszter, Országh, Erika, Józwiak, Ákos Bernard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749435/
https://www.ncbi.nlm.nih.gov/pubmed/36531278
http://dx.doi.org/10.2903/j.efsa.2022.e200913
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author Palmas, Elisa
Engelhardt, Tekla
Farkas, Zsuzsa
Csorba, Szilveszter
Országh, Erika
Józwiak, Ákos Bernard
author_facet Palmas, Elisa
Engelhardt, Tekla
Farkas, Zsuzsa
Csorba, Szilveszter
Országh, Erika
Józwiak, Ákos Bernard
author_sort Palmas, Elisa
collection PubMed
description 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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spelling pubmed-97494352022-12-15 Emerging risk identification by applying data analytical tools Palmas, Elisa Engelhardt, Tekla Farkas, Zsuzsa Csorba, Szilveszter Országh, Erika Józwiak, Ákos Bernard EFSA J Eu‐fora Series 5 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. John Wiley and Sons Inc. 2022-12-14 /pmc/articles/PMC9749435/ /pubmed/36531278 http://dx.doi.org/10.2903/j.efsa.2022.e200913 Text en © 2022 Wiley‐VCH Verlag GmbH & Co. KgaA on behalf of the European Food Safety Authority. https://creativecommons.org/licenses/by-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nd/4.0/ (https://creativecommons.org/licenses/by-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited and no modifications or adaptations are made.
spellingShingle Eu‐fora Series 5
Palmas, Elisa
Engelhardt, Tekla
Farkas, Zsuzsa
Csorba, Szilveszter
Országh, Erika
Józwiak, Ákos Bernard
Emerging risk identification by applying data analytical tools
title Emerging risk identification by applying data analytical tools
title_full Emerging risk identification by applying data analytical tools
title_fullStr Emerging risk identification by applying data analytical tools
title_full_unstemmed Emerging risk identification by applying data analytical tools
title_short Emerging risk identification by applying data analytical tools
title_sort emerging risk identification by applying data analytical tools
topic Eu‐fora Series 5
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749435/
https://www.ncbi.nlm.nih.gov/pubmed/36531278
http://dx.doi.org/10.2903/j.efsa.2022.e200913
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