By Chris Johnson
Recently, the term big data has become ubiquitous. People who can wrangle big data are called data scientists. According to a number of sources, there is a growing need for people trained as data scientists. But what is data science? Is data science its own field or is it an interdisciplinary mix of computer science, mathematics and statistics, and domain knowledge, or perhaps is it really what statisticians have been doing all along? Since data science at scale involves large-scale computation, what is the relation between data science and computational science in research and education?
At the recent SIAM Computational Science and Engineering Conference (CSE 2015), we held what turned out to be a very lively panel to discuss the current and future status of data science, its relationship to computational science, opportunities for data and computational scientists, and educating future data scientists. View a brief video recapping the panel:
Some surprising things we learned from the panelists were that data science:
- Is NOT statistics
- Should be taught by computer scientists
- Is not new, but just the other side of the coin of computational science and engineering.
In the pursuing discussion with the audience, we learned that for every statement made by a panelist, there was at least one response to the contrary and many additional ideas about data science. I hope you will view the panel slides, listen to the lively discussion, and offer your own thoughts and insights.
Chris Johnson is director of the Scientific Computing and Imaging Institute, co-director of the Center for Integrative Biomedical Computing, and a Distinguished Professor of Computer Science at the University of Utah. He was co-chair of the 2015 SIAM Conference on Computational Science and Engineering and Chair of the Data Science panel.