Building Research Data Infrastructure for Emerging Research Institutions Using an Open-Source Model Design

Emerging research institutions (ERIs) are vital incubators of scientific discovery but often lack the resources and infrastructure to support a robust institutional research enterprise. ERIs thus face challenges with essential research management activities like tracking research performance, outputs, and funding. ResDataNexus will provide an open-source framework to build interactive data platforms that monitor research and development (R&D) activities and expenditures while forecasting future opportunities. By automating data collection and analysis, ResDatanexus will support informed, data-driven decision-making, strengthen collaborations, and boost institutional competitiveness. The project also engages students in hands-on data analytics, helping build future research talent and encouraging strategic partnerships that drive innovation and national research progress. The ResDataNexus project will explore ways of developing a cost-effective, low-maintenance, open-source data infrastructure for ERIs to systematically track research outputs, R&D expenditures, and grant activities. The project will unfold in three phases: framework development; prototype testing and validation on partner campuses (University of San Diego, Elon University, Pepperdine University); and iterative refinement with broad dissemination. ResDataNexus will integrate diverse data sources, build interactive dashboards for real-time monitoring, and apply machine learning to create a forecasting model and research activity composite index. By correlating financial inputs with publication metrics and funding outcomes, the model will predict institutional research return on investment. Scalable and customizable, ResDataNexus will empower ERIs with data-driven planning, strengthening research capacity and competitiveness. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.