URI_Research_Magazine_Momentum_Spring_2018_Melissa-McCarthy

Meng Wei, assistant professor, Graduate School of Oceanography; Maya Vadiveloo, assistant professor, nutrition and food sciences; Joan Peckham, professor, computer science and statistics, coordinator, Big Data Collaborative; Lubos Thoma, associate professor, mathematics; Harrison Dekker, associate professor, University Kingston Library.

In another data-driven project, Oceanography Professor Yang Shen capitalizes on the Big Data Collaborative to synthesize the large data sets he obtains from underwater sensors that detect earthquakes and differentiates them from nuclear explosions. “One of the biggest assets of the collaborative is the resources it aggregates,” according to Peckham. “It’s interdisciplinary in that we bring people from different programs to work together to solve problems.” In the fall of 2016, the provost and academic deans helped increase this diversity with the placement of nine new data research-oriented faculty at URI. These new faculty members help feed the demand from students and industry for data science skills. The interdisciplinary curriculums Peckham helped design include data science BA and BS majors and a minor, intended to teach students the “skills they need in order to wrangle data.” She says graduate data science programs and a Data Science Institute may be on the horizon at the University as well. “There are a lot of people with large data sets, and of course, it’s a challenge today,” Peckham explains.

“Part of the reason we’re developing the study of data science is that we’ve learned how to collect huge volumes of data and we haven’t really developed viable techniques for analyzing the data and understanding what the data is saying.” People commonly assume that so-called big data refers to large data sets, but, according to Peckham, that is not always the case. Rather, the term refers to any data set for which there does not yet exist viable techniques for managing, analyzing and understanding the data – from small and complex to incomplete sets of data. This aspect of modern big data sets will drive research and scholarship in data science going forward. Though less than a year old, the program already has brought a multitude of exciting new research and partnerships to the University community.

Page 26 | The University of Rhode Island { momentum: Research & Innovation }