What factors lead to a productive sales team? What kinds of management behaviors lead to higher turnover?

Academic researchers have long asked these hypothetical questions over the years, with each author providing distinct analyses and sets of data.   

“There’s a lot of data out there,” said Rick Watson, a Regents Professor and the J. Rex Fuqua Distinguished Chair for Internet Strategy.  

But there’s no way for researchers to look at all data collected on a given topic at one time or use modern data analysis to find answers.

Watson has partnered with Xia Zhao, an assistant professor in management information systems and Terry student Yuanyuan (April) Song, who is completing a Ph.D. to help make social science research data more accessible and useful. Their team has been awarded an $80,000 grant to find a way to use those methods on the mountains of data in social science research papers.

The Alfred P. Sloan Foundation is funding Watson and Zhao’ development of a data mining method and a knowledge coding protocol to support knowledge analytics. The methods will help researchers make new connections that may have been hiding in plain sight.

“For example, one researcher may have found that A causes B. Another researcher found that B causes C,” Watson said. “But no one has been able to link together that A causes B causes C.”

That’s the type of connection Watson, Zhao and Song hope to facilitate by mining causal models and other data sets from the papers.

While the tools being developed by their Theory Research Exchange (called T-Rex for short) project are initially aimed at streamlining information systems research, they will be available to social science researchers to help break down the silos that stifle discoveries.

“Today, we have millions of scientists, most of whom are not giants but contributors of small pieces to the giant jigsaw of scientific discovery across diverse fields,” Watson wrote in his grant application. “Scientific progress requires building upon many exponentially expanding foundations. This massive combinatorial problem of synthesizing ideas across manifold publications needs supporting technology to accelerate progress.”

Similar efforts to make data searchable and accessible transpire in biology and genetics, but this is among the first to create high-quality, accessible data and associated data analytics tools in the social science disciplines, Watson said.

The Sloan Foundation will fund the project through December 2023. More information on the project’s progress is available at t-rex-graph.org.