A team working to eliminate data-ingestion bottlenecks in order to enable faster storage systems at Rutgers University and the Stony Brook University is one of 16 recipients of midscale research awards made by Core Techniques and Technologies for Advancing Big Data Science & Engineering (BIGDATA), a collaboration between the National Science Foundation (NSF) and the National Institutes of Health.
“Scientific advances are increasingly limited by our ability to analyze and interpret extremely large data sets,” says Vasant Honavar, director of the Information Integration and Informatics Program at the NSF. Sources of data range from email and Internet transactions to sensor networks. “We now can gather lots of diverse types of data, but scientific advances won’t take place until we can manage such data effectively and can extract useful knowledge from data.”
BIGDATA solicited proposals that were focused on data collection as well as management, analytics and infrastructure for collaborative science environments. It’s one of many NSF efforts tuned into the Big Data challenge. Another is the Science of Learning Centers program, which funds programs to leverage Big Data for the improvement of instruction through online tutoring.
The NSF also has plans to establish a program aimed at educating and supporting a new generation of researchers who can address fundamental Big Data challenges concerning core technologies and cyberinfrastructure across disciplines. This will be a new track in the NSF’s Integrative Graduate Education and Research Traineeship program.
The Big Data Senior Steering Group of the Networking and Information Technology Research and Development program, a large interagency coordinating group (of which the NSF is a part), also is working to identify programs across the federal government and bring together experts to define a potential national initiative in this area.