Over the last decade, the National Science Foundation (NSF) has successfully developed its “10 Big Ideas” into a collection of research and enabling programs. One of these, Harnessing the Data Revolution (HDR), led to a collection of five different Institutes that each focuses on data, its science, and its applications that are enabled by cyberinfrastructure. Their specific disciplinary areas span from biological images at the Imageomics Institute, physics at A3D3, polar-region inquiries at iHARP, and scientific and engineering design processes themselves at ID4. As one of these Institutes, I-GUIDE facilitates the use of geospatial data in convergence science with a particular focus on solving problems of extreme events and disaster resilience.
Within the HDR ecosystem, the unambiguous focus on data is nested within “convergence research” activities, an approach for complex problems that inherently leverage multi- and transdisciplinary teams. In practice, this means that each of the five HDR Institutes consists of many scholars who are subject-matter experts in various fields, and the research agendas they have pursued have woven together their respective threads into synergistic solutions. As one example from I-GUIDE, hydrologists who understand stream flow patterns have coordinated with atmospheric scientists who model extreme rainfall so that geographic information scientists who generate flood inundation maps can connect with sociologists who gather input from – and share their findings with – potentially affected populations.
For convergence research at this scale to be successful, each Institute relies on cyberinfrastructure to enable their distributed team activities. For I-GUIDE, its Platform has become a solution for convergence science that builds upon previous NSF investments in cyberGIS and cyberinfrastructure. Through its integration of advanced cyberinfrastructure and AI, the I-GUIDE Platform provides seamless access to data, models, and computational resources, drastically advancing convergence research and education across areas such as aging dam infrastructure, disaster resilience, and food and water security.
The rapid advances of artificial intelligence (AI) and machine learning (ML) have also had significant impacts on all five Institutes. Three of the Institutes collaborated on a ML Challenge for novel approaches to detecting data anomalies. A second Challenge is underway to generate data models that function well outside of their limited training realms. I-GUIDE’s Spatial AI Challenge is currently recruiting another round of participants as well. In addition to outreach and broadening participation, these Challenges allow the Institutes to test their respective cyberinfrastructure systems and data science capabilities with external audiences.
To discover and explore potential convergence research opportunities across these five Institutes, NSF funds an annual HDR Ecosystem Conference to maximize cross-Institute knowledge sharing. At the 2025 HDR Ecosystem Conference, hosted by Imageomics at the Ohio State University, AI was a ubiquitous topic across several panels. Personnel from all Institutes appreciated workshops where we explored together how to use generative AI in research workflows. AI will again figure prominently at the final HDR Ecosystem Conference which will take place in August 2026 in Chicago, hosted by I-GUIDE. Its theme, AI and Science: From Geospatial to Convergence, will accommodate the full extent of data-intensive activities underway across the five Institutes and highlight the convergence they have achieved.
Though NSF is not renewing its HDR program after its initial five-year run, the research produced and lessons learned have already advanced knowledge frontiers regarding how AI and data science innovation can enable convergence science discovery as the preponderance of data still requires both multidisciplinary teams of people and the ongoing support of cyberinfrastructure.