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Ten Research Challenge Areas in Data Science

Published onSep 30, 2020
Ten Research Challenge Areas in Data Science
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  • This Release (#1) was created on Jul 30, 2020 ()
  • The latest Release (#3) was created on Apr 10, 2022 ().

Abstract

To drive progress in the field of data science, we propose 10 challenge areas for the research community to pursue.  Since data science is broad, with methods drawing from computer science, statistics, and other disciplines, and with applications appearing in all sectors, these challenge areas speak to the breadth of issues spanning science, technology, and society. We preface our enumeration with meta-questions about whether data science is a discipline.  We then describe each of the ten challenge areas.  The goal of this article is to start a discussion on what could constitute a basis for a research agenda in data science, while recognizing that the field of data science is still evolving.

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