AF16082 Cool Data, big data for optimised cold storage of food (BO-46-002-015, BO-32.02-006-012)

In this project we want to prove that Big Data technologies (in particular machine learning combined with linked data standards and knowledge modelling) will allow storage and transport providers to operate significantly more effective and efficient than they do now. Ultimately, the partners in this project aim to establish an open platform in which the developed data, models and algorithms can be continuously shared and updated: the Cool Data Hub.

This project will lead to improved and homogeneous product quality and a more sustainable process in the fresh product supply chain. The project will create new business opportunities throughout the chain and in IT. Scientifically, our challenge is to integrate self-learning methods such as Bayesian Belief Networks with Linked Data, i.e., semantically enriched data. If this can be done, a continuous self-learning cycle involving data, models and applications can be realized. Moreover, the generated data will allow agrifood scientists to create new hypotheses for further experimental research.