DOE funds research on “Objective-based Data Reduction for Scientific Workflows” to tame massive data sets to advance scientific discovery

The following news release was issued by the U.S. Department of Energy. It announces funding for nine projects that will address management and processing of massive data sets produced by scientific observatories, experimental facilities, and supercomputers that span the DOE national laboratory complex.

As part of this program, Brookhaven Lab was awarded $2.4 million in funding over three years. Dr. Byung-Jun Yoon of Brookhaven National Lab‘s Computational Science Initiative will lead the project with Texas A&M University and University of Illinois Urbana-Champaign as partners. Dr. Yoon and his team’s work will involve using novel theoretical strategies to develop practical algorithms anchored in scientific objectives – i.e., focused specifically on the goals of interest. These algorithms would bypass scientifically irrelevant information, which could considerably reduce overall data generated by complex experimental or computational systems and streamline any required processing.

Further information and the full announcement can be found at the link below: