Multimedia Gallery - Broadcast of OSTP-led Federal Government Big Data Rollout, March 29, 2012, Washington, DC.

March 30, 2012

Broadcast of OSTP-led Federal Government Big Data Rollout, March 29, 2012, Washington, DC.

Broadcast of OSTP-led federal government big data rollout, held on March 29, 2012, in the AAAS Auditorium in Washington, DC, and featuring: John Holdren, assistant to the President and director, White House Office of Science and Technology Policy; Subra Suresh, director, National Science Foundation; Francis Collins, director, National Institutes of Health; Marcia McNutt, director, United States Geological Survey; Zach Lemnios; assistant secretary of defense for research & engineering, U.S. Department of Defense; Ken Gabriel, acting director, Defense Advanced Research Projects Agency; and William Brinkman, director, Department of Energy Office of Science. Each official announced initiative(s) that his or her federal government agency was embarking on to embrace the opportunities and address the challenges afforded by the Big Data Revolution.

The announcements were followed by a panel discussion with industry and academic thought leaders, moderated by Steve Lohr of the New York Times. Panelists were: Daphne Koller, Stanford University (machine learning and applications in biology and education); James Manyika, McKinsey & Company (co-author of major McKinsey report on Big Data); Lucila Ohno-Machado, UC San Diego (NIH's "Integrating Data for Analysis, Anonymization, and Sharing" initiative); and Alex Szalay, Johns Hopkins University (big data for astronomy).

About Big Data: Researchers in a growing number of fields are generating extremely large and complicated data sets, commonly referred to as "big data." A wealth of information may be found within these sets, with enormous potential to shed light on some of the toughest and most pressing challenges facing the nation. To capitalize on this unprecedented opportunity--to extract insights, discover new patterns and make new connections across disciplines--we need better tools to access, store, search, visualize and analyze these data.

Credit: National Science Foundation

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