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In this talk, we will share our experience visualizing spatio-temporal data (e.g., chemical dispersion, atmospheric data, wind patterns, and water flow) using CesiumJS. While CesiumJS excels at rendering massive, heterogeneous 3D objects, visualizing spatio-temporal data remains challenging due to its dynamic nature. To address these challenges, we explored workaround solutions to efficiently handle and visualize large-scale spatio-temporal data, aiming for intuitive representation and realistic simulation. As a result, we successfully developed techniques for chemical dispersion visualization, water flow simulation, and atmospheric data rendering over time. In this session, we will showcase real-world projects that leverage these solutions, demonstrating how CesiumJS can be adapted to support complex, time-dependent geospatial datasets. Acknowledgement: This work was supported by Korea Environment Industry & Technology Institute (KEITI) through 'Advanced Technology Development Project for Predicting and Preventing Chemical Accidents' program. Sanghee Shin CEO/President Gaia3D Jinho Kim GIS Software Developer Gaia3D, Inc Yongsub Kwak Senior Researcher, Digital Twin Division Gaia3D