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Albers, T. (author), Lazovik, E. (author), Yousefi, M.H.N. (author), Lazovik, A. (author)Distributed data processing systems have become the standard means for big data analytics. These systems are based on processing pipelines where operations on data are performed in a chain of consecutive steps. Normally, the operations performed by these pipelines are set at design time, and any changes to their functionality require the...article 2021
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Lazovik, E. (author), Medema, M. (author), Albers, T. (author), Langius, E.A.F. (author), Lazovik, A. (author)Distributed data processing systems are the standard means for large-scale data analysis in the Big Data field. These systems are based on processing pipelines where the processing is done via a composition of multiple elements or steps. In current distributed data processing systems, the code and parameters that create the pipeline are set at...conference paper 2017
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Verhoosel, J.P.C. (author), Spek, J.C. (author)In the Dutch SmartDairyFarming project, better decision support for the dairy farmer on daily questions around feeding, insemination, calving and milk production processes is made possible using a variety of big data sources containing static and dynamic sensor data of individual cows. This paper is concerned with the inherent semantic...conference paper 2016
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Verhoosel, J.P.C. (author), van Bekkum, M.A. (author), van Evert, F.K. (author)This paper addresses the use of ontologies for combining different sensor data sources to enable big data analysis in the dairy farming domain. We have made existing data sources accessible via linked data RDF mechanisms using OWL ontologies on Virtuoso and D2RQ triple stores. In addition, we have created a common ontology for the domain and...conference paper 2015