I-GUIDE VCO: Open-Source Spatiotemporal Geovisual Analytics with CyberGIS-Vis: A COVID-19 Case Study

Open-Source Spatiotemporal Geovisual Analytics with CyberGIS-Vis: A COVID-19 Case Study

June 25, 2025 12:00 pm (Central Time)

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Abstract

The COVID-19 pandemic underscored the critical need for effective disease mapping tools, which have long been integral to public health efforts in tracking infectious diseases. In response to the World Health Organization’s (WHO) declaration of COVID-19 as a pandemic in March 2020, numerous technological solutions were rapidly developed to map cases, assess risk factors, and monitor human mobility, attracting significant attention from researchers and policymakers. Despite the widespread adoption of these tools, there was a notable lack of reusable and reproducible, open-source mapping software, which is essential for quick and effective responses to future pandemics. The pandemic also highlighted the growing importance of visualizing spatiotemporal dynamics in disease datasets. However, there remains a scarcity of open-source JavaScript-based tools that support Coordinated and Multiple Views (CMV) within geovisual analytics, a critical feature for enabling comprehensive and dynamic data analysis. Traditional GIS software packages that support CMV, such as GeoViz Toolkit and CommonGIS, are predominantly Java-based and designed for offline environments, creating a gap in their integration with modern, web-based visualization environments that rely on libraries like D3, Plotly.js, and Leaflet. To address these gaps, we developed an open-source JavaScript-based software tool within the CyberGIS-Vis project, designed to support CMV for interactive geospatial visualization. This talk will introduce two visualization modules within CyberGIS-Vis, demonstrating their application in visualizing spatiotemporal data through a COVID-19 case study. The CyberGIS-Vis tool integrates advanced cyberGIS and online visualization capabilities with analytical methods, empowering knowledge discovery from geospatial data. Features include dynamic choropleth mapping linked with charts, comparative visualization of spatiotemporal patterns, and integration with CyberGIS-Jupyter for reproducible visual analytics, offering multi-language support for Python and JavaScript.

Speakers

Su Yeon Han

Su Yeon Han

Geography and Environmental Studies at Texas State University

Su Yeon Han is an Assistant Professor in the Department of Geography and Environmental Studies at Texas State University. She earned her Ph.D. in Geography through the joint doctoral program between San Diego State University and the University of California, Santa Barbara. She holds an M.S. in Geography and Geographic Information Science from the University of Illinois at Urbana–Champaign and a B.A. in Geography with a minor in Computer Science from the University of North Carolina at Chapel Hill. Dr. Han’s research interests span spatial data science, disaster management, human mobility, social media analytics, health GIS, web-based GIS, GIS-based decision support systems, CyberGIS, cartography, geovisualization, geovisual analytics, and neighborhood dynamics. Her recent work centers on analyzing shelter accessibility and human mobility during wildfires. She is also the core developer and maintainer of CyberGIS-Vis, an open-source software tool designed for interactive geospatial visualization and scalable visual analytics. 

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