Geospatial data, also known as spatial data or geographic information, is data or information representing physical objects with an explicit geographic component on the surface or near-surface of the Earth. The increased volume and diversity of geospatial data have caused serious usability challenges to researchers in various scientific domains, which calls for a cyberGIS solution. To address these issues, this paper presents a cyberGIS community data service framework to facilitate big geospatial data access, processing, and sharing based on a hybrid supercomputer architecture. Through the collaboration between the CyberGIS Center at the University of Illinois at Urbana-Champaign (UIUC) and the U.S. Geological Survey (USGS), a community data service for accessing, customizing, and sharing digital elevation model (DEM) and its derived datasets from the 10m national elevation dataset, namely TopoLens, is developed to demonstrate the pipelined integration of big geospatial data sources, computation needed for customizing the original dataset for end user needs, and a highly usable online user environment. TopoLens provides online access to precomputed and on-demand computed high-resolution elevation data by leveraging the ROGER supercomputer. The need for building such services for GIScientists and the usability of this prototype service have been acknowledged in community evaluation.