Members of the Visual Analytics team include (from left) Xinran Hu, Chris North, Leanna House, Scotland Leman, Lauren Bradel, Jessica Zeitz Self, and Ian Crandell.

Big Data: Everyone wants to use it; but few can. A team of researchers at Virginia Tech is trying to change that.

In an effort to make Big Data analytics usable and accessible to nonspecialist, professional, and student users, the team is fusing human-computer interaction research with complex statistical methods to create something that is both scalable and interactive.

“Gaining big insight from big data requires big analytics, which poses big usability problems,” said Chris North, a professor of computer science and associate director of the Institute for Critical Technology and Applied Science’s Discovery Analytics Center.

With a $1 million from the National Science Foundation, North and his team are working to make vast amounts of data usable by changing the way people see it.

Yong Cao, an assistant professor with the Department of Computer Science in the College of Engineering, along with Leanna House, an assistant professor, and Scotland Leman, an associate professor, both with the Department of Statistics of the College of Science, are working with North to bring large data clouds down to manageable working sets. Read more.