In the realm of geospatial data analysis, Chao Gong stands out as a significant figure, currently studying for a PhD at Maynooth University in Ireland. Gong has amassed over ten years of experience, previously working on national-level surveying and mapping initiatives in China. His background includes managing extensive geospatial databases while supporting various infrastructure, land use, and environmental projects. This foundational expertise is instrumental in informing his doctoral research, which emphasizes the necessity for efficient access to spatial data. Gong’s current research is focused on developing API-driven methods for geospatial analysis that facilitate near real-time and on-demand access to important data. This approach addresses the limitations faced in traditional GIS workflows, where analysts often rely on downloading extensive datasets prior to undertaking any form of analysis. By pioneering methods that allow users to conduct proximity analysis without pre-downloading full datasets, Gong is effectively improving the efficiency and reliability of geospatial analysis in professional contexts. One of the key challenges Gong encounters in his research is achieving a balance between enabling near real-time data access and ensuring the integrity and reliability of analytical outcomes. Gong argues that simply having access to large datasets does not necessarily lead to better decision-making outcomes, especially if the data is not relevant or appropriately managed. This perspective informs the focus of his research, which seeks to connect users more directly with the data that is truly pertinent to their analysis tasks. Looking forward, Gong expresses a desire to see more research that explores the integration of cloud-based GIS and desktop systems. Additionally, he seeks to combine GIS with artificial intelligence and machine learning to further promote automated analysis. He believes that continued innovation in these areas will yield significant improvements in how organizations interact with geospatial data, ultimately enhancing their decision-making capabilities while decreasing operational costs.