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Defining Data Science by a Data-Driven Quantification of the Community

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Predictive Medicine and Data Analytics Lab, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland
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Institute of Biosciences and Medical Technology, FI-33101 Tampere, Finland
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Institute for Intelligent Production, Faculty for Management, University of Applied Sciences Upper Austria, Steyr Campus, A-4400 Steyr, Austria
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Department of Mechatronics and Biomedical Computer Science, UMIT, A-6060 Hall in Tyrol, Austria
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College of Computer and Control Engineering, Nankai University, Tianjin 300071, China
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Author to whom correspondence should be addressed.
Mach. Learn. Knowl. Extr. 2019, 1(1), 235-251; https://doi.org/10.3390/make1010015
Received: 4 December 2018 / Revised: 14 December 2018 / Accepted: 17 December 2018 / Published: 19 December 2018
(This article belongs to the Section Data)
Data science is a new academic field that has received much attention in recent years. One reason for this is that our increasingly digitalized society generates more and more data in all areas of our lives and science and we are desperately seeking for solutions to deal with this problem. In this paper, we investigate the academic roots of data science. We are using data of scientists and their citations from Google Scholar, who have an interest in data science, to perform a quantitative analysis of the data science community. Furthermore, for decomposing the data science community into its major defining factors corresponding to the most important research fields, we introduce a statistical regression model that is fully automatic and robust with respect to a subsampling of the data. This statistical model allows us to define the ‘importance’ of a field as its predictive abilities. Overall, our method provides an objective answer to the question ‘What is data science?’. View Full-Text
Keywords: scientometrics; data science; computational social science; dataology; statistics; digital society scientometrics; data science; computational social science; dataology; statistics; digital society
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Emmert-Streib, F.; Dehmer, M. Defining Data Science by a Data-Driven Quantification of the Community. Mach. Learn. Knowl. Extr. 2019, 1, 235-251.

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