Overview
NSF's Harnessing the Data Revolution program has produced foundational science in AI and data-intensive research. GeoRoundtable's work connects these discoveries to open standards and commercial engineering.
The NSF Harnessing the Data Revolution (HDR) initiative is an integrated fabric of interrelated institutes that aims to accelerate discovery and innovation across multiple areas of data-intensive science and engineering. An objective of the HDR Ecosystem Conference was to advance a vision of how the HDR ecosystem is an integral part of a broader, coherent ecosystem of AI and data-intensive research.
GeoRoundtable participated in the 3rd annual NSF HDR Ecosystem Conference (September 9–12, 2024, University of Illinois Urbana-Champaign) as a representative of the NSF I-GUIDE Council of Geospatial Leaders — bringing a perspective focused on how HDR research results can be carried forward into open consensus standards and commercial product development, particularly for AI.
The central argument: HDR research in AI and data science provides new scientific foundations for the IEEE Spatial Web standard — specifically for the definition of Spatial Web Hyperspace — while the Spatial Web provides the engineering architecture to operationalize HDR discoveries at scale.
GeoRoundtable's Perspective
Percivall's approach to community engagement centers on the use of open consensus standards as the mechanism for transferring HDR research results into the broader engineering ecosystem — making scientific insights available to commercial product developers who would not otherwise engage with academic research.
This is of particular importance for AI commercial product development, which could benefit substantially from more rigorous scientific grounding. The HDR ecosystem has produced foundational work in areas — machine learning theory, data-intensive computing, spatial reasoning — that remain underutilized in commercial AI engineering practice.
NSF-funded projects have historically been the basis of open geospatial standards development. I-GUIDE's involvement in OGC Testbed 19 and 20 represents a continuation of this pipeline: research results becoming part of new OGC standards.
The Technical Bridge
Space and Time as organizing principles connect HDR geospatial research to the IEEE Spatial Web standard — with Hyperspace as the generalization that brings AI and data science into the same framework.
NSF HDR Research
AI & Data Science Foundations
Bridge
Spatial Web Hyperspace Definition
IEEE 2874-2025
Spatial Web Standard
Engineering Practice
Commercial AI Products
The Spatial Web generalizes the notion of space to hyperspace — arising from AI and big data systems that handle terabytes and petabytes of information using tensors, which are very high-dimensional mathematical spaces. HDR research in high-dimensional data science provides direct scientific grounding for this architectural choice in IEEE 2874-2025.
I-GUIDE is focused on harnessing the geospatial data revolution with Space and Time as the organizing principles — the same principles at the core of the Spatial Web standard. This shared foundation makes I-GUIDE research directly applicable to Spatial Web specification and architecture.
I-GUIDE's participation in OGC Testbed 19 and 20 — working on CyberGIS interoperability — demonstrates the pipeline from NSF research to open standards. These testbed results are candidates for new OGC standards, continuing a decades-long tradition of NSF-funded science becoming the foundation of interoperability standards.
Commercial AI product development often outpaces its scientific foundations. GeoRoundtable's community engagement strategy positions open standards as the conduit through which HDR research results — in machine learning, spatial reasoning, data governance — become accessible to the broader engineering community building AI products and systems.
"The Spatial Web is an ecosystem of intelligent agents coordinating activities toward shared goals — using space as the organizing principle for scalable, collective intelligence."
— George Percivall
The 3rd annual NSF HDR Ecosystem Conference brought together the full fabric of HDR institutes — spanning AI, data science, geospatial research, astronomy, biology, and more — to advance a common vision for data-intensive science. GeoRoundtable's participation as part of the I-GUIDE Council of Geospatial Leaders represented the geospatial standards and engineering communities within this ecosystem.
The next NSF HDR Ecosystem Conference is planned for August 2026 in Chicago, hosted by I-GUIDE, with the theme "AI and Science: From Geospatial to Convergence" — a theme that directly reflects the bridge between HDR research and AI engineering that GeoRoundtable has been working to build.
The Spatial Web's definition of hyperspace — grounded in the high-dimensional mathematics of modern AI and data science — represents a concrete technical example of how fundamental HDR research flows into engineering standards that shape commercial AI development.
NSF HDR Institutes
The NSF HDR program funds an integrated set of institutes spanning data-intensive science — with geospatial, AI, and physics at the forefront.
Geospatial · GeoRoundtable Role
Focused on harnessing the geospatial data revolution with Space and Time as organizing principles. George Percivall participates as a member of the Council of Geospatial Leaders, bridging I-GUIDE research to IEEE and OGC standards development. Hosted by the University of Illinois Urbana-Champaign.
Physics & Astronomy
Institute for Accelerating AI Algorithms for Data-Driven Discovery — developing real-time AI for physics experiments including CERN and multi-messenger astronomy. Demonstrates how HDR research pushes the frontiers of AI in ways directly relevant to the Spatial Web's high-dimensional hyperspace architecture.
Broader Ecosystem
The HDR ecosystem spans institutes in climate, biology, AI systems, and cyberinfrastructure — all contributing to the integrated fabric of data-intensive research. Community engagement across institutes enables cross-domain discoveries to flow into shared engineering standards.
Related
Interested in how NSF HDR research connects to open standards, Spatial Web architecture, or geospatial AI? Get in touch.
✉️ percivall@ieee.org