Data science

Animal health research provides us with a lot of data. For example, we can quickly determine the complete genetic code of viruses and bacteria. It only gets really interesting when this new data is combined with existing data. Bioinformatics helps us to combine, analyze and interpret these huge amounts of data. Thus, answers can be obtained to biological questions. This allows us to draw conclusions about origins and risks of diseases. This provides new knowledge and applications in animal health, food safety and epidemiology. With this, for example, we can for example quickly determine characteristics and the origin bird flu virus outbreaks, automatically detect lame cows and monitor behaviour of fishers. Read more about our innovative research below.

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  Next Level Animal Sciences: data and models

  The rapid developments in sensor and imaging technology make larger and more complex datasets from different sources available. The challenge is to convert this data into useful information on animals' behaviour, health, and well-being.

The use of Data science allows the development of Smart Farming approaches for plants and animals (Precision Agriculture). Individual, small, as well as large production units can be managed and monitored in time and space according to their needs required for optimal production and biosafety without jeopardizing health, welfare, and environment. Improved data communication and data integration between parties within and between various food supply chains, locally as well as on a global scale, may contribute to improved efficiencies, sustainability, safety and a better global food and nutrition security.

Data science can help consumers in making healthy and sustained food choices. With the Data science the gap between intention and behaviour of consumers can be narrowed down and may provide ready-to-use health intervention strategies (e-Health). Personalized feedback on dietary needs may be given if one takes into account data on personal preferences, dietary intake history, activity levels, physiological information, and eating behaviour. Relevant markets include: individual consumers; (care) hospitals; retail; producers, breeders, etc.

Data science is crucial to understand and control biomass feedstocks. Open data systems are needed to set up and support the complex logistics in a future Biobased and Circular economy, where physical product flows are divers and scattered by definition.

Global changes of political, financial or climatic nature, make food production chains vulnerable and are expected to have major impacts on global and local economies. Planet earth as well as metropolitan clusters face problems with respect to their food supply and waste removal, for example, how to produce enough food and keep the local and global system environmentally sustainable?

Other nearby perspectives are the use of embedded systems in our food production and living systems. For example in smart greenhouses, in kitchens and fridges.