Data to Knowledge to Action: Building New Partnerships
The emergence of "Big Data" provides us with some of the biggest
challenges and opportunities. The challenges include the capture, storage,
sharing, search, visualization, analysis, understanding, and processing of
massive amounts of data that are complex and heterogeneous and are being
gathered at rates that exceed our current capacity for handling such data. The
opportunities stem from the potential for extracting useful knowledge from Big
Data for more informed decisions, helping accelerate discovery and innovation,
and supporting their transition into practice to benefit society.
To address the challenges and opportunities of Big
Data, the U.S. government has launched, in March 2012, the National Big Data
Research and Development Initiative (http://www.whitehouse.gov/blog/2012/03/29/big-data-big-deal),
which included over $200 million in research and development support from six
Federal departments and agencies. But making the most of Big Data requires a
joint effort from all the stakeholders: federal government, local governments, industry,
universities, and non-profits. To help achieve this goal, the White House has
sponsored the event “Data to Knowledge to Action: Building New Partnerships” on
November 12, 2013 at the Ronald Reagan Building and International Trade Center
in Washington, DC. The event was co-sponsored by the White House Office of
Science and Technology Policy and the Networking and Information Technology
R&D (NITRD) program, which represents the information technology portfolios
of 18 Federal agencies. It was also supported by an NSF grant to George Mason
University (http://www.nsf.gov/awardsearch/showAward?AWD_ID=1358747).
The "Data to Knowledge to Action" event
was attended by the key Big Data stakeholders: representatives of the many
federal agencies that support Big Data projects, leading academics engaged in
Big Data research, leading Big Data innovators from industry, as well as
participants from the state and local governments, non-profits, foundations and
other organizations engaged in Big Data research, applications, workforce
development, and technology transfer activities. The participants presented high-impact
collaborations and identified additional areas for possible collaboration
between the public and private sectors, including projects and initiatives
that: advance technologies that support Big Data and data analytics; educate
and expand the Big Data workforce; develop, demonstrate and evaluate
applications of Big Data that improve key outcomes in economic growth, job
creation, education, health, energy, sustainability, public safety, advanced
manufacturing, science and engineering, and global development; demonstrate the
role that prizes and challenges can play in deriving new insights from Big
Data; and foster regional innovation.
This event has led to: a better recognition and
appreciation of the current high-impact collaborations; increased
collaborations among the multiple Big Data stakeholders to facilitate
transformative advances in the core Big Data technologies of capturing,
storing, sharing, searching, visualizing, analyzing, understanding, and
processing of huge, diverse, complex, and distributed data sets; and fostering
of innovation in science, engineering, and education necessary for advancing
national goals and priorities in economic growth, education, health, clean
energy, and security.
Press Releases and Fact Sheets
Event Materials
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Plenary and Breakout Session Agenda
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Technical Showcase Agenda
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Speaker Biographies
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Presentation: Building New Partnerships
Tom Kalil, Deputy Director for OSTP
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Presentation: Harnessing The Potential of Data Scientists and Big Data for Scientific Discovery
Ed Lazowska, University of Washington
Saul Perlmutter, UC Berkeley
Yann Le Cun, New York University
Josh Greenberg, Alfred P. Sloan Foundation
Chris Mentzel, Gordon and Betty Moore Foundation
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Presentation: Innovation, Research & Development, and Education and Workforce Development
Breakout Sessions Report Back
Christy Wilson, Splunk
Michael Rappa, North Carolina State University
Stanley Ahalt, University of North Carolina at Chapel Hill
Poster Session
- IBM's Health and Wellness Analytics Solution
Timothy Paydos, IBM
- High Density Computing: Break Through the Boundaries and Limitations of Big Data Processing
Eng Lim Goh, Stacey McCallum, Dick Crisman, SGI
Gerry Kolosvary, Joe Conway, Fedcentric Technologies
- Large Scale Data Analytics and Visualization Research at the Center for Dynamic Data Analytics (CDDA)
Dimitris Metaxas, Rutgers University
Rong Zhao, Stony Brook University
Steven Greenspan, CA Technologies
James Mielke, Tina Eliassi-Rad, Jaideep Vaidya, CDDA
- Analytic Tradecraft’s Role in Big Data
Christian Shuler, David Reynolds, BAE Systems
- PBS KIDS: Learning Analytics Research & Development
Sara DeWitt, PBS KIDS Digital
Jeremy Roberts, The Incredible Pear, LLC
- Scientific Computing with Amazon Web Services
Jamie Kinney, Shannon Kellogg, Amazon Web Services
- Pivotal Network Intelligence: Applying Data Science for Network Security Monitoring
Derek Lin, Hulya Farinas, Pivotal
- Actionable Intelligence: Continuous Discovery of Evidence, Hypotheses, and Arguments from Masses of Data
Gheorghe Tecuci, David Schum, Mihai Boicu, Dorin Marcu, George Mason University
- Introducing HAVEn: A strategic overview of HP’s Big Data Platform
Brenda Kirkpatrick, Carl Bradley, Diana Zavala, Hewlett-Packard Development Company, LP
- Art of the Possible in Reducing “Time and Cost to Awareness”, Insider Threat Cyber Security Situational Awareness (CSSA)
Brenda Kirkpatrick, Carl Bradley, Diana Zavala, Hewlett-Packard Development Company, LP
- Big Data Is a Movement, Demanding More Analytics On All Data
Alex Lunsford et al., Teradata
- The Platform for Big Data
Webster Mudge, Andrew Swentzel, Michael Lazar, Cloudera
- Where Politics End and Governance Begins
John W. Davis, Notice and Comment
- MKI Makes 4000,000x Difference in Healthcare Industry with SAP HANA
Mike Ryan, Michele Pugliese, Jennifer Stafford, SAP
- Map-D
Todd Mostak, Tom Graham, MIT
- Making Big Linguistic Data Work
Martin Benjamin, Kamusi
- Docket Wrench Tutorial
Andrew Pendleton, Sunlight Foundation
- Pan-cellular, whole-organism 3D imaging and visualization at cellular resolution by synchrotron microCT for phenomics
Cheng Lab, Jake Gittlen, Keith Cheng, Xuying Xin, Penn State
- Big Data as an Engineering Discipline
Jennifer Truman Bernhard, Steven Lumetta, Roy Campbell, University of Illinois
- Financial Cyberinfrastructure and DSfin: Data Science for Finance
Louiqa Raschid, University of Maryland
Media
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Video Webcast: Event welcome, partnership announcements, and briefings
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Video Webcast: Panel discussion
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Video: Elizabeth Bruce of MIT describes the MIT's Big Data Initiative, which explores computational
platforms, algorithms, machine learning, security and privacy issues and
applications
- Video: Michael Bender, Stony
Brook University, describes his work on indexing of big data--organizing
data so that you can find things
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Video: Merce Crosas of the
Institute for Quantitive Social Science, from Harvard University describes
her work on open source data
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Video: Bill Howe of the
University of Washington describes his work on big data and opportunities
for collaboration among academia and industry
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Video: Srinivas Aluru of
Iowa State University works at the intersection of the life sciences and
big data
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Video: Martin-Farach-Colton
of Rutgers University concentrates on big data storage
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Video: Dimitris Mataxas of
Rutgers University works primarily with biomedical data and clinical
trials
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Video: Stan Ahalt of the
Renaissance Computer Institute at the University of North Carolina, Chapel
Hill defines big data
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Video: Tom Caruso of the
University of North Carolina discusses a public-private consortium in
self-generated health
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Video: Tom Mitchell of
Carnegie Mellon University concentrates his research efforts on machine
learning
- Video: Arcot Rajasekar of
the University of North Carolina, Chapel Hill, and his team are working to
increase data accessibility
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Video: Eli Upfal of Brown
University is working to build mathematical and statistical tools that
with advanced computational methods can derive meaning from big data
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Video: Kirk Borne of George
Mason University works in big data education, as well as applied areas
Associated Events
Select Press Highlights
- November 12, 2013 -- White House promotes new partnerships as it seeks to make better use
of ‘big data’
"The Obama administration
plans Tuesday to announce a new set of partnerships that enlist private
companies, nonprofits, academics and others in an effort to harness big data to
solve national problems. The new alliances come more than a year and a half
after the administration established $200 million in big data initiatives aimed
at sorting through the massive reams of information collected by the government
to glean new insights." (Source: Washington Post) Read the article
- November 12, 2013 -- Program Seeks to Nurture 'Data Science Culture' at Universities
"[The problem of data
silos], among others, is the focus of a new five-year project, involving three
universities and supported by $37.8 million in funding from the Moore
Foundation and the Sloan Foundation. The three universities in the partnership
are New York University, the University of Washington and the University of
California, Berkeley. The program is being announced today in Washington at an
event organized by the White House Office of Science and Technology Policy, to
highlight initiatives being taken by government, industry and academia to
advance data-driven scientific discovery and technological progress." (Source:
New York Times) Read the article
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