Crossing the Innovation Valley of Death: Democratizing Data and Artificial Intelligence for Research Administration

This project aims to significantly enhance post-award research administration by developing open-source tools that integrate artificial intelligence (AI) and data science. Research administration is crucial for supporting scientific progress, but many institutions face challenges with inefficient processes that hinder their ability to effectively manage grants and contracts.

Recent advances in generative AI provide a unique opportunity to augment research administrators' capabilities. By creating accessible, innovative tools, this project will help level the playing field for emerging research institutions, minority-serving institutions, and primarily undergraduate institutions. Improved research administration will accelerate scientific discovery across disciplines by reducing the administrative burden on researchers, allowing them to focus more on their work.

The project will also contribute to workforce development by training research administrators in data science and AI skills, preparing them for the increasingly technological future of the field. By making these tools open source, the project promotes collaboration and innovation in the broader research management ecosystem.

The project has three main objectives: 1) Develop open-source data models and workflows that adhere to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles to improve data accessibility and interoperability in research administration. 2) Create trustworthy AI-powered tools to automate manual processes, reduce errors, and augment the capabilities of research administrators. These will include natural language processing and machine learning models for tasks like data extraction, compliance verification, and decision support.

All tools will undergo rigorous testing for accuracy, reliability, and reproducibility. 3) Implement and assess the impact of these tools at partner institutions, starting with the University of Idaho and Southern Utah University, then expanding to additional collaborators. The project will use an iterative, user-centered development approach, incorporating feedback from partners to ensure the tools meet real-world needs.

Importantly, the project features an independent external evaluator to ensure the research administration community can learn from both successes and challenges, a critical approach given the rapid advancements in AI capabilities. By integrating data science and AI in a thoughtful, tested manner, this project aims to create a transformative framework for efficient, data-driven research administration that can be adopted widely across diverse institutions.

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.