The National Science Foundation (NSF) announced today some $31 million in awards for 17 innovative projects geared toward the promotion of data science and a robust data infrastructure. The National Science Foundation (NSF) seeks to improve the nation’s capacity in data science by investing in the development of infrastructure, making it easer to use data, and increasing the number of skilled data scientists.
The $31 million funding award was directed to the Data Infrastructure Building Blocks (DIBBs) program, which is now in its second year. According to the NSF, “the DIBBs program encourages development of robust and shared data-centric cyberinfrastructure capabilities to accelerate interdisciplinary and collaborative research in areas of inquiry stimulated by data.” The 2014 DIBBs awards include 17 innovative projects, spanning 22 states. Research topics are varied and include computer science, information technology, and nearly every other discipline supported by the NSF.
“Developed through extensive community input and vetting, NSF has an ambitious vision and strategy for advancing scientific discovery through data,” said Irene Qualters, division director for Advanced Cyberinfrastructure at NSF. “This vision requires a collaborative national data infrastructure that is aligned to research priorities and that is efficient, highly interoperable and anticipates emerging data policies.”
The NSF is taking a building block approach to data science. Beyond the hardware, software and networking components, there is the human element, the research community. The current awards are considered an extension of last year’s program.
DIBBs includes two classes of awards: Pilot Demonstration Awards, and Early Implementation Awards. This year, two projects were selected for early implementation awards of $5 million over five years.
One of these awards went to Geoffrey Fox, a professor of computer science and informatics at Indiana University, who is developing middleware and analytics libraries to support the scaling of data science on high-performance computers. Test applications come from the fields of geospatial information systems (GIS), biomedicine, epidemiology and remote sensing.
The other early implementation projects is being led by Ken Koedinger, professor of human computer interaction and psychology at Carnegie Mellon University, who is working to develop infrastructure for use in education. The team is working on a distributed data infrastructure called LearnSphere that will make educational data (generated from interactive tutoring systems, educational games and massively open online courses, or MOOCs) accessible to course developers and instructors.
For more information on the awards and a complete list of recipients go to http://www.nsf.gov/news/news_summ.jsp?cntn_id=132880&org=NSF&from=news.