This research focuses on the development and implementation of an interface to the Geospatial Analytical Research Knowledgebase (GeoARK), a spatially enabled big data informatics approach assembled around applications in health research and analytics. Example applications in telehealth reach, COVID-19 risk in rural situations, pathways for zoonotic disease spread, and contextual leukemia research will be provided. The creation and design of GeoARK occurred within the University of Missouri’s Institute for Data Science and Informatics. Being spatially engendered, its core is data that is pre-processed, cleaned, integrated and represented in its spatial context as millions of point locations. To this core, additional ancillary / complementary data are added. This data includes demographic, environmental, infrastructure, cultural, physical, as well as geo-analytically derived layers (i.e. accessibility). We have assembled these data within a database design supporting user based complex query, contextual extraction, spatial analysis, and visualization to examine potential relationships among the integrated data layers and patterns of potential interest for further research. The spatial design allows for quantification at location to be focused and visualized to promote greater understanding and increase communication of impacts, opportunities, and risks.