Education

It is essential that food safety and veterinary public health scientists acquire computational science skills during their training that will enable them to create, manipulate and analyse large datasets.
The creation and development of databases and the use of analytical methodologies are not only a matter of computer science and data science, but also require the ability to evaluate and analyse input data and results from a professional point of view. This implies a level of knowledge of the relevant food chain science domain that allows the interpretation and determination of the validity of individual data.
Therefore, the above interdisciplinary values will be given a prominent role in the development of the Hungarian and English language graduate courses. Currently, there is no such integrated food safety data science training in Hungary nor in the wider region, so launch of postgraduate courses in English are in progress.

In recent years, our Institute staff have regularly taught at other universities and in the European Commission's Better Training for Safer Food (BTSF) training scheme, in courses related to risk assessment, risk communication, HACCP, strategic planning of the food chain, marketing. With the creation of DFI, these courses will continue to be taught, but we plan to extend our teaching portfolio at the University of Veterinary Medicine Budapest as well.

Courses managed by DFI

Assessing the safety of the food chain, analysing risks and, where appropriate, managing them, requires increasingly complex, computationally intensive analyses and methods. The overall objective of the course is to familiarise students with the range of computational methods applicable to food chain safety, their fundamentals, applications and limitations.

Veterinary public health contributes to the overall physical, mental and social well-being of people through the application of veterinary science. The overall aim of the course is to provide an overview of the public health aspect of veterinary medicine and to introduce the common principles of food hygiene, epidemiology and veterinary public health management.

One of the important tasks of a veterinarian is to contribute to the production of healthy, wholesome food through healthy, well-bred farm animals. But what makes a food healthy? Is there such a thing as healthy food? There are many beliefs and misconceptions about healthy eating. The aim of this course is to provide students with an understanding and deeper knowledge of how the food industry works, the basics of food safety, gastronomy and nutrition. In addition to a scientific introduction to the issues of the field, the course will also cover the latest gastronomic and nutritional trends and future research and development directions.

The overall aim of the course is to familiarise students with the role of veterinarians in ensuring food chain safety. During the lectures, guest speakers from the National Food Chain Safety Office (Nébih) and the Ministry of Agriculture will present the current issues and challenges in their respective fields and the main responsibilities of veterinarians in each field.

The course is available only in Hungarian.

The course will give students an insight into the challenges of agro-ecological systems as a resource for the food chain. In line with EU sustainability principles, today's global issues from climate change and adaptive agriculture to future food security and safety will be addressed. Innovation opportunities for adaptation in agriculture and food production practices will also be presented.

Theses supervised by DFI

Recent years have shown the importance of being able to predict and track outbreaks of infectious diseases with the aim of preventing major incidents that can cause vast disruptions to society. Predicting disease emergence can be aided by the study of the drivers and trends of infectious disease emergence. This thesis describes a proof of concept for the use of automated news screening as a tool to use in as part of an early warning system to identify the emergence of infectious disease, using the Lake Victoria Basin as the subject for this exploration. The method described in thesis uses the open-source text mining and data analysis tools of KNIME and R’s tidyGraph, iGraph and visNetwork packages to breakdown and examine digital news articles to create an easily visualizable summary of news articles relevant to news on a topic of choice, in this thesis, disease outbreaks.

Click here to download the KNIME workflow used in the thesis.

Newsletter subscription