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The National Academies of Sciences, Engineering and Medicine
Board on Mathematical Sciences and Analytics
Board on Mathematical Sciences and Analytics
About BMSA
Committee On Applied & Theoretical Statistics
Math Frontiers Webinar Series
Data Education Roundtable
Member Bios
BMSA & CATS Impacts



About the Roundtable

The Roundtable on Data Science Postsecondary Education brings together representatives from academic data science programs, funding agencies, professional societies, foundations, and industry to discuss the community’s needs, best practices, and ways to move forward. The roundtable will help affected communities develop a coherent and shared view of the emerging field of data science and of how best to prepare large numbers of professionals to help realize the potential of this field. 


The roundtable convenes four meetings per year. Each meeting focuses on a topic related to data science education or practice, and consists of presentations from experts followed by open discussions of the roundtable. All meetings are open to the public and advertised to the broader data science community. Meetings will be webcast live with the capability for remote participation, and all videos and slides from each meeting will be posted online. Meeting highlights will be produced following each meeting to summarize the presentations and discussions that occurred.


The roundtable is sponsored by the Gordon and Betty Moore Foundation, the National Institutes of Health, the National Academy of Sciences W. K. Kellogg Foundation Fund, the Association for Computing Machinery, the American Statistical Association, and the Mathematical Association of America.


Member Biographies 


Past Meetings

September 27, 2019   Final Meeting of the Data Science Education Roundtable: Synthesis and Dissemination Plans

June 12, 2019             Data Science Education at Two-Year Colleges

March 29, 2019           Improving Coordination between Academia and Industry

December 10, 2018    Motivating Data Science Education through Social Good 

September 17, 2018   Challenges and Opportunities to Better Engage Women and Minorities in Data Science Education

June 13, 2018             Programs and Approaches for Data Science Education at the PhD Level

March 23, 2018           Improving Reproducibility by Teaching Data Science as a Scientific Process 

December 8, 2017      Integrating Ethical and Privacy Concerns into Data Science Education

October 20, 2017        Alternative Mechanisms for Data Science Education

May 1, 2017                Data Science Education in the Workplace

March 20, 2017           Examining the Intersection of Domain Expertise and Data Science

December 14, 2016    The Foundations of Data Science from Statistics, Computer Science, Mathematics, and Engineering