Big data becomes available at different levels of detail and domains. The interdisciplinary integration provides guidelines for researching complex issues, for example in the field of food safety and sustainability.
Big data plays a role here at three distinct levels. Firstly, at the micro level, big data helps to understand and predict the behaviour of micro-organisms in the foodchain. Additionally, at the meso level, big data provides a view on local environmental factors, such as fluctuations in air temperatures. At the macro level, big data predicts the behaviour of the consumer and the manufacturer and global issues. This reveals how consumers and producers use products: what are the consequences for the optimal shelf life of products?
By combining these data about the behaviour of micro-organisms, weather forecasts, expected consumer behaviour and different levels of details, research is better able to predict which product has the most health risks, or where in the chain extra measures are required.