High-dimensional statistics; Interdisciplinary research; Data science; Computational science; Machine learning; Scientific computing; Data Analytics; Data-driven modelling; Modelling
Abstract :
[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.
Ley, Christophe; Ghent University > Department of Applied Mathematics, Computer Science and Statistics
BORDAS, Stéphane ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
Language :
English
Title :
What makes Data Science different? A discussion involving Statistics2.0 and Computational Sciences
Publication date :
21 March 2017
Number of pages :
8
Focus Area :
Computational Sciences
European Projects :
FP7 - 279578 - REALTCUT - Towards real time multiscale simulation of cutting in non-linear materials with applications to surgical simulation and computer guided surgery
Name of the research project :
RealTcut
Funders :
European Research Council Starting Independent Research Grant (ERC Stg grant RealTcut, agreement No. 279578) CE - Commission Européenne