Reference : What makes Data Science different? A discussion involving Statistics2.0 and Computati...
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Computational Sciences
What makes Data Science different? A discussion involving Statistics2.0 and Computational Sciences
Ley, Christophe [Ghent University > Department of Applied Mathematics, Computer Science and Statistics]
Bordas, Stéphane mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
[en] High-dimensional statistics ; Interdisciplinary research ; Data science ; Computational science ; Machine learning ; Scientific computing ; Data Analytics ; Data-driven modelling ; Modelling
[en] Data Science is today one of the main buzzwords be it in business, industrial or academic settings. Machine learning, experimental design, data-driven modelling are all, undoubtedly, rising disciplines if one goes by the soaring number of research papers and patents appearing each year. The prospect of becoming a ``Data Scientist'' appeals to many. A discussion panel organised as part of the European Data Science Conference (European Association for Data Science (EuADS)) asked the question: ``What makes Data Science different?'' In this paper we give our own, personal and multi-facetted view on this question, from an engineering and a statistics perspective. In particular, we compare Data Science to Statistics and discuss the connection between Data Science and Computational Science.
European Research Council Starting Independent Research Grant (ERC Stg grant RealTcut, agreement No. 279578)
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FP7 ; 279578 - REALTCUT - Towards real time multiscale simulation of cutting in non-linear materials with applications to surgical simulation and computer guided surgery

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