November 12, 2013
Grant will support interdisciplinary, data-intensive research at UW
Researchers across the University of Washington campus soon will be able to collaborate in an unprecedented way with a new team of data scientists to advance research through big-data analysis and discovery.
The UW, along with the University of California, Berkeley, and New York University, are partners in a new five-year, $37.8 million grant from the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation that aims to accelerate the growth of data-intensive discovery across many fields.
“All across our campus, the process of discovery will increasingly rely on researchers’ ability to extract knowledge from vast amounts of data,” said UW project lead Ed Lazowska, a professor of computer science and engineering and director of the eScience Institute.
“To remain at the forefront, the UW must be a leader in advancing the methodologies of data science and putting them to work in the broadest imaginable range of fields.”
The new initiative was announced Tuesday (Nov. 12) as a featured talk at a White House Office of Science and Technology Policy event highlighting public-private partnerships that support big data research.
The UW’s award with UC Berkeley and NYU builds upon existing investments in the eScience Institute – created in 2008 to focus on data-intensive discovery across campus – and the Center for Statistics and the Social Sciences, now almost 15 years old. More than a dozen faculty members are working to implement the initiative at the UW.
At the UW, the grant will mainly fund salaries for new research positions, including five data scientists who specialize in software and will work with researchers across campus, four postdoctoral data science fellows pursuing interdisciplinary research and four partially funded research scientists stationed in other departments and centers. A dedicated “data science studio” on campus will have meeting areas and drop-in workspaces to encourage collaboration across the UW’s colleges and schools.
These new resources will allow faculty members to submit short-term project proposals that require data science expertise, which could include analyzing a large dataset, accessing cloud resources or scaling up a statistical method, said Bill Howe, co-lead of the new effort and a UW affiliate assistant professor of computer science and engineering. A social scientist could, for example, learn how to mine data from social media channels to help with a research project. Or, a geographer might want to know how weather data affect a landscape in real-time.
Faculty participants in the program would send a graduate student or research staff member to physically relocate for a period to work directly with the data scientists. The idea behind this embedded approach is to learn techniques, collaborate and then bring that knowledge back to individual labs and departments.
“We see enormous potential in the cross-pollination that happens by having participants co-locate in the data science studio,” Howe said. “These projects will help expose common problems and enable collaboration as we continue to scale up our investment in data science expertise.”
The UW also has received a $2.8 million Integrative Graduate Education and Research Traineeship grant from the National Science Foundation. Together, the two grants will fund several dozen graduate students from a variety of departments to learn how to tackle big data in their research fields. The need to analyze vast amounts of data now touches nearly every department and discipline, and both grants will boost the university’s ability to prepare students.
Faculty members see this initiative as advancing the capacity for data-intensive scientific research and boosting Seattle’s leadership in data science, while attracting more top talent back to universities at a time when big data is more pervasive than ever before.
“These data scientists are coveted in industry as well as in academia,” Howe said. “One of the missions we have in this effort is to provide competitive career paths and roles that allow these experts the freedom to apply their skills to the most important problems in science.”