Big data Europe and agri-environmental research

Project

Big data Europe and agri-environmental research

The project links up with the major European Big Data communities through the Big Data Europe project, a major European Big Data networking and platform development initiative. Its aim is twofold. First to position the agro-environmental science domain and especially some of the specific Wageningen UR challenges in the heart of European Big Data research. Second, to benefit from state-of-the-art concepts, technologies and expertise that are offered for use through Big Data Europe and thus bring forward the potential to apply Big Data in our research.

The project will bring into Big Data Europe a targeted scientific agro-environmental use case that builds on already performed work in FP-7 projects SemaGrow and Trees4Future and that focusses on tackling cross-discipline integration (Variety) to create added Value in the agro-environmental applied science domain. The result will be a working use case, showcasing how to deal with cross-discipline data integration through the advanced use of semantics and data analysis techniques to cope with the heterogeneity of Big Data in the agro-environmental domain and value adding for science.

Assessing different Big data analytical solutions on their usefullness as pattern recognition to agricultural and environmental data sets available on the Big Data Europe infrastructure

The project links up with the major European Big Data communities through the Big Data Europe project, a major European Big Data networking and platform development initiative. Its aim is twofold. First to position the agro-environmental science domain and especially some of the specific Wageningen UR challenges in the heart of European Big Data research. Second, to benefit from state-of-the-art concepts, technologies and expertise that are offered for use through Big Data Europe and thus bring forward the potential to apply Big Data in our research.

The project will bring into Big Data Europe a targeted scientific agro-environmental use case that builds on already performed work in FP-7 projects SemaGrow and Trees4Future and that focusses on tackling cross-discipline integration (Variety) to create added Value in the agro-environmental applied science domain.

The result will be a working use case, showcasing how to deal with cross-discipline data integration through the advanced use of semantics and data analysis techniques to cope with the heterogeneity of Big Data in the agro-environmental domain and value adding for science.

Publications