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Building the U.S. Big Data Machine

By R&D Editors | November 19, 2015

The Big Data Regional Innovation Hubs cover all 50 states and include commitments from more than 250 organizations — from universities and cities to foundations and Fortune 500 corporations — with the ability to expand further over time. Courtesy of NSFThe U.S. National Science Foundation (NSF) has long been integral to the development of the infrastructure, tools, and training required for gleaning insights from large data sets. With a recent $5 million (€4.68 million) investment, they are creating four big data hubs so scientists can investigate research topics with an everyday impact in their region.

The four hubs are located at Columbia University (Northeast); Georgia Institute of Technology and the University of North Carolina (South); the University of Illinois at Urbana-Champaign (Midwest); and the University of California, San Diego, the University of California, Berkeley, and the University of Washington (West). Alaskan and Hawaiian researchers will work through the West hub, and U.S. territories are welcome to participate in any regional hub.

“By establishing partnerships among likeminded stakeholders,” says Jim Kurose, NSF’s assistant director for Computer and Information Science and Engineering, “BD Regional Innovation Hubs represent a unique approach to improving the impact of data science.”

Each of the hubs chose research foci mirroring regional strengths and challenges. For instance, the Midwest hub is situated near one of the largest freshwater reservoirs in the world. The Midwest is also home to Mayo Clinic, world-renowned leader in healthcare, and Eli Lilly, one of the world’s largest pharmaceutical companies. And, as the third most populous city in the US, Chicago employs many smart city management concepts.

For these reasons, the Midwest hub will focus on:

  1. Society (e.g., smart cities and communities; network science; business analytics)
  2. Natural and built world (e.g., water, food, and energy; digital agriculture; transportation; and advanced manufacturing)
  3. Healthcare and biomedical research

“Big data will help us determine how much water to use for raising food, how much for drinking, and how much to leave untouched,” said Edward Seidel, principal investigator of the Midwest hub and director of the National Center for Supercomputing Applications. “It will help us decide how to allocate resources based on current soil, crop, and climate decisions — ultimately, how to make the smartest decisions possible for the benefit of the people who live here.”

The other hubs will have similar foci:

  • Northeast hub: Big data in health, energy, finance, cities/regions, discovery science, and data science in education (connecting research will include data sharing, privacy and security, ethics and policy, and education)
  • Southern hub: Healthcare, coastal hazards, industrial big data, materials and manufacturing, and habitat planning
  • Western hub: Big data technologies, managing natural resources and hazards, precision medicine, metro data science, and data-enabled scientific discovery and learning

The Big Data Hubs program is an offshoot of the National Big Data Research and Development Initiative President Obama launched in early 2012. Under that initiative, six federal departments pledged over $200M (€187 million) to fund the forward-thinking research thrust, launching new fields of otherwise inaccessible inquiry.

Given reduced coordination costs, the NSF expects partnerships with Fortune 500 companies and smaller research and education institutions to form more easily. Greasing the wheel in this way ensures “teams of data science researchers will come together with domain experts, with cities and municipalities, and with anchor institutions to accelerate progress in a wide range of science and education domains with the potential for great societal benefit,” says Kurose.

  • Read more: Establishing a Brain Trust for Data Science

This article was originally published on ScienceNode.org. Read the original article.

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