The National Science Foundation (NSF), with support from the National Institutes of Health (NIH), today announced 8 awards totaling nearly $15 million in new Big Data fundamental research projects. These awards aim to develop new tools and methods to extract and use knowledge from collections of large data sets to accelerate progress in science and engineering research and innovation.
A UW CSE project led by Magda Balazinska, Bill Howe, and Dan Suciu was among the 8 awardees. In brief:
“The ability to analyze massive-scale datasets has become an important tool both in industry and in the sciences and many systems have recently emerged to support it. However, effective methods for deep data analytics are currently high-touch processes: they require a highly specialized expert who thoroughly understands the application domain and pertinent disparate data sources and who needs to perform repeatedly a series of data exploration, manipulation and transformation steps to prepare the data for querying, machine learning or data mining algorithms. This project explores the foundations of big data management with the ultimate goal of significantly improving the productivity in big data analytics by accelerating the bottleneck step of data exploration. The project integrates two thrusts: a theoretical study, which leads to new fundamental results regarding the complexity of various new (ad hoc) data transformations in modern massive-scale systems, and a systems study, which leads to a multi-platform software middleware for expressing and optimizing ad hoc data analytics techniques.”