NSF-funded study maps how research centers shape collaboration, impact in higher education

Data science doesn’t fit the traditional academic mold. While most universities contain departments of mathematics, physics, computer science, and biology, data science draws from all of them — and more. It is a field born from interdisciplinary need, often housed in institutes rather than departments, precisely because it resists being boxed into a single discipline.

This tension between disciplinary structure and interdisciplinary ambition is at the heart of a newly funded research project led by Alex Gates, assistant professor at the University of Virginia School of Data Science. Funded by the National Science Foundation (NSF) and conducted in collaboration with Alina Lungeanu (Northeastern University) and Dakota Murray (SUNY Albany), the project investigates how university research centers and institutes — like the ones that house data science — shape academic collaboration and influence the trajectory of scientific research.

Universities are still largely organized around departments, which cultivate depth in specific fields. But the most pressing scientific challenges — whether modeling climate systems, responding to pandemics, or advancing artificial intelligence — require breadth. They demand collaboration across disciplines, and increasingly, that collaboration happens within research centers and institutes designed to break down silos and foster translational science.

Yet, despite their growing importance, the influence of these centers remains underexplored. Gates’ project aims to change that by assembling a massive longitudinal dataset that links researchers, publications, funding, and institutional affiliations across all major research universities in the U.S. This is a formidable data challenge, requiring sophisticated methods to disambiguate affiliations, integrate underutilized data sources, and trace the evolution of collaborative networks over time.

Once built, the dataset will support complex analyses to understand how institutes shape researcher behavior, collaboration patterns, and scientific impact. Gates will use natural experiments to isolate the causal effects of centers — even after they dissolve — offering rare insight into their long-term influence on academic ecosystems.

“We’re trying to understand how the architecture of the university itself affects the science it produces,” Gates explains. “Institutes are designed to foster interdisciplinary work, but we need empirical evidence to understand when and how they succeed.”

This work promises to illuminate the hidden scaffolding of academic collaboration and provide actionable insights into how universities can better organize themselves to meet the scientific challenges of the future.