TRACK-ing Stars and Unicorns: The trajectory of funded and unfunded people and ideas

Scientific progress and innovation depend on a complex interplay between researchers, funding, teams, time, and ideas. Funding agencies, including UKRI, must balance investing in people—the cornerstone of a sustainable research workforce—with investing in ideas that could lead to future innovations. Previous research has identified markers for high-performing individuals (Lee, 2024, Scientometrics), but predicting market success early in the innovation pipeline remains far more difficult, increasing the risk of heavily funding ideas that may never materialise (Thelwall et al., 2023, QSS). Overemphasis on early investment in ideas risks underinvesting in the workforce necessary to develop future innovations. This project frames the paradox as a choice between supporting “stars” (research careers) versus “unicorns” (high-risk, novel ideas). What is needed is a funding mechanism that supports both people and the environments in which transformative ideas can thrive.
This project leverages Natural Language Processing (NLP) and Knowledge Graphs to extract concepts from titles and abstracts, linking them with bibliometric data to monitor research success among individuals who were either successful or unsuccessful in securing UKRI funding. It will result in the development of the TRACK-database (Trajectories ofResearch Applications and Career Knowledge), the world’s first longitudinal funding database linking pseudonymised individuals to their applications, research concepts, and outputs over time. This represents a step change in research policy evaluation, introducing a scalable, AI-powered framework capable of enabling large-scale, longitudinal analysis. The TRACK-database will allow investigation of how research careers and ideas evolve, and how outcomes are causally linked to different types of early-career funding (<5 years from first publication).
Further analyses will explore whether particular disciplines benefit more from certain funding models and assess the UK’s position within the global research landscape by comparing trends internationally. These insights will deepen understanding of the long-term impact of funding strategies on both individuals and innovation ecosystems.
Engagement with UKRI, as a primary beneficiary, will ensure that the insights generated are applied to inform policy and practice. Findings from the TRACK-database will support the development of a funding environment that both sustains a high-quality research workforce and fosters the generation of novel ideas. By providing an evidence-based foundation for future funding strategies, the project will help create a more resilient, productive, and internationally competitive UK research ecosystem.