Print Email Facebook Twitter Interactive insight in big livestock data Title Interactive insight in big livestock data Author Snijders, R. de Jong, A.P.J. Albers, T. van Waaij, B.D. Vonder, M.R. Publication year 2019 Abstract The vast amount of livestock (sensor) data collected everyday, offers a huge potential to improve model prediction and therefore decision support for farmers. However, the prediction performance of these models depends highly on the availability and quality of the data. Careful dataset preparation is therefore important. Nowadays, selecting and understanding the data becomes increasingly more difficult as the data grows in size and complexity. In our study we provide data providers within the livestock farming industry with guidelines to describe their data sets more accurately and provide model developers useful techniques to compose a good quality subset of the data to form the base for their model development. This all comes together into our Interactive Visualization tool which allows model developers to explore the data and select, visually or with the use of familiar programming languages, subsets of good quality data for modelling. By using state-ofthe-art distributed computing frameworks, our prototype solution can scale as the size of the data grows to terabytes or even petabytes. We use operational (sensor) data from the Dutch smart dairy farming project to illustrate our solution. Subject Big dataDairy farmingIteractive insightDataset preparationData quality To reference this document use: http://resolver.tudelft.nl/uuid:e4f96a9a-8fff-43e2-9654-1c11df5e7ef4 TNO identifier 868844 Source Proceedings 9th European Conference on Precision Livestock Farming, Cork, Ireland, 26-29 August 2019 Document type conference paper Files To receive the publication files, please send an e-mail request to TNO Library.