The following sentences from the original I-GUIDE proposal describe an ambitious vision for using enabling cyberinfrastructure (CI) to approach geospatial convergence science:

“I-GUIDE seeks to develop integrative cyberinfrastructure and scientific synthesis, supporting reproducible integration of geospatial data, analytics, and domain-specific models, as critical scaffolding necessary to gain geospatial understanding across diverse computational, domain-specific, spatial, and temporal scales. I-GUIDE will transform geospatial data-intensive sciences by integrating cyberGIS, reproducible data-intensive analytics and modeling, FAIR data principles, and innovative education and workforce development programs.”

Beginning with the premise that existing CI components would meet many of I-GUIDE’s convergence science needs, we have built the I-GUIDE CI Platform as a set of composable components that can be assembled in flexible ways to support the needs of I-GUIDE’s convergence science catalyst teams. While the Platform is aimed at supporting open, reproducible, convergence science – at scale – using distributed geospatial datasets and analyses that may be too large to conveniently run, store, or move using conventional technologies, using the Platform is not yet as easy or as well understood as it could be. This is both a technical challenge (i.e., working toward CI components and integration that increase scientists’ capabilities without requiring huge leaps in their technical skillsets) and a social challenge (i.e., convincing I-GUIDE’s participating scientists to use the available tools and change their normal research practices to promote FAIR principles and reproducible computational modeling and analytics).

In this presentation, we will describe the principles guiding development of the I-GUIDE platform, specific components of the Platform and their supported functionality, challenges we seek to overcome through innovation, and the I-GUIDE CI Team’s vision for the I-GUIDE Platform as “…a novel, integrative geospatial discovery environment for empowering diverse communities to produce data-intensive solutions to society’s resilience and sustainability challenges.”