I-GUIDE VCO: Why Discrete Global Grid Systems (DGGS) Matter Now: From Grids to AI-Ready Geospatial Systems

Why Discrete Global Grid Systems (DGGS) Matter Now: From Grids to AI-Ready Geospatial Systems

February 25, 2026 11:00 am (Central Time)

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Abstract

Discrete Global Grid Systems (DGGS) have shifted from theoretical models to operational infrastructure, thanks to recent OGC standards. The ISO 19170-1 standard (2021) and the OGC API – DGGS (2025) provide a shared foundation for interoperability, allowing DGGS to support consistent, scalable, and standards-based spatial services. These developments are critical for advancing AI-ready, digital-first spatial representation. The AI-DGGS Pilot, focused on flood risk in Manitoba’s Red River Basin, demonstrated how DGGS infrastructure aligned with OGC standards can integrate diverse datasets and support explainable, AI-driven disaster response. A live demo will showcase DGGS service interactions.

Speakers

Sina Taghavikish

Sina Taghavikish

Open Geospatial Consortium

Dr. Sina Taghavikish is a Project Manager for international research and development projects at the Open Geospatial Consortium (OGC). He holds a PhD in Geomatics Engineering from the University of Calgary. His work focuses on geospatial interoperability and the application of standards-based geospatial technologies in Earth observation. In this role, he supports the coordination and execution of multi-partner initiatives involving government, research, and industry. He has contributed to the design, implementation, and evaluation of operational geospatial workflows and is experienced in Earth observation, geomatics engineering, precision engineering and deformation monitoring, laser scanning, mobile mapping, remote sensing, optical and synthetic aperture radar satellite imagery, GIS, and GNSS.

Nathan McEachen

Nathan McEachen

TerraFrame

Nathan McEachen is the founder, CEO, and CTO of TerraFrame, which specializes in supporting ministries of health and national spatial data infrastructures by building geospatial knowledge infrastructures with open-source GIS, remote sensing, and interoperability solutions. He obtained his bachelor’s degree in computer science from California Polytechnic State University in San Luis Obispo and his master’s degree in computer science from Colorado State University in the United States. He is academically published in the fields of software testing, model-driven engineering, disease intervention, and spatial information sciences. Nathan is involved with the Open Geospatial Consortium and HL7 to help align standards development, enabling more automated data integration across sectors to bring geospatial awareness to large language models.

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