2026 BTSCON: Informing the Design of Interdisciplinary Research Centers

Big Team Science Conference talk: Informing the Design of Interdisciplinary Research Centers with Longitudinal Social Network Analysis Presenter: Peng Warweg Interdisciplinary research centers are increasingly used to foster cross-disciplinary collaboration, but whether they actually reshape faculty collaboration networks is rarely tested with longitudinal, relational data. This study uses ten years (2015–2024) of NSF grant co-investigator data from a large research university to examine four interdisciplinary research centers established in 2020, framed through communities of practice theory as deliberately designed collaborative communities. Analyzing 322 faculty and 433 dyadic co-investigator ties at the node and dyad levels, we test whether center membership predicts collaboration, especially across colleges, and what mechanisms explain any advantage. Center and non-Center faculty collaborated at similar overall rates after 2020, but Center members reached significantly further across colleges, a difference that held after controlling for seniority, productivity, and college affiliation. At the dyadic level, ties involving Center members were disproportionately cross-college, and Center members' share of collaborative ties (30–50%) far exceeded their share of the population (21–28%), a diffusion effect. Longitudinal comparisons among long-standing members showed this cross-college advantage predated center formation (a selection effect) and did not grow further after joining (a ceiling effect), while the pattern was weaker among brand-new members. Together, these findings suggest research centers function less as engines that manufacture interdisciplinarity and more as mechanisms that concentrate already boundary-spanning researchers and radiate their collaborative practice outward. We discuss implications for how universities recruit, structure, and evaluate interdisciplinary research centers, and demonstrate a replicable, low-cost approach to using public grant data for longitudinal network evaluation of designed research communities. recorded October 7, 2026 bigteamscienceconference.github.io