During its work, the Data Science Task Force encountered numerous definitions of data science—some put emphasis on “data” and its transformation into knowledge; others draw on the intersection of disciplines; and still others consider the “data pipeline.”
With such ambiguity, the task force suggests a definition to guide the implementation of the recommendations. This definition emphasizes discovery, exploration, and knowledge creation, i.e., the uses of data and data methods:
Data Science draws upon multiple disciplines to develop or apply computational and analytic methods to responsibly explore data and discover actionable insights and accelerate translation into implementation with real-world evidence.
Data Science for Undergraduates: Opportunities and Options
National Academies of Sciences, Engineering, and Medicine, Washington, DC: The National Academies Press, 2018.
Data Science Strategic Plan
NIH, 2018.
Full set of NSCAI reports from July 2019 through March 2021: National Security Commission on Artificial Intelligence (AI)
Schmidt, Eric, Bob Work, Safra Catz, Steve Chien, Chris Darby, Kenneth Ford, Jose-Marie Griffiths, et al. National Security Commission on Artificial Intelligence.
The Data Science Life Cycle: A Disciplined Approach to Advancing Data Science as a Science.
Victoria Stodden. Communications of the ACM, July 2020, Vol. 63 No. 7, pages 58-66.
The Federal Big Data Research and Development Strategic Plan
Big Data Senior Steering Group. Subcommittee on Networking and Information Technology Research and Development (NITRD), National Science and Technology Council, 2016.
Ten Simple Rules for Starting (and Sustaining) an Academic Data Science Initiative
Parker, Micaela S., Arlyn Burgess, and Philip Bourne. 2020. OSF Preprints. June 2.