A Smart Service-Oriented CyberGIS Framework for Solving Data-Intensive Geospatial Problems

This chapter introduces a CyberGIS solution that aims at resolving the big data challenges in the discovery, search, visualization and interoperability of geospatial data. We describe a service-oriented architecture to make heterogeneous geospatial resources easily sharable and interoperable. OGC standards for sharing vector data, raster data, sensor observation data etc. are adopted in such an infrastructure because of their widespread popularity in the GIScience community. Three supporting techniques include: (1) a novel method that combines real-time Web crawling and meta-cataloging in support of quick identification and discovery of distributed geospatial services; (2) an ontology-enabled semantic search framework to enhance the relevancy search and ranking; (3) multi-dimensional visualization of diverse interrelated dataset for discovering underlying patterns and decision-making. Finally, we introduce two applications: Landsat Image Service Archive (LISA) and the ESIP (Earth Science Information Partnership) Semantic Web Testbed to demonstrate the applicability of proposed techniques in various Earth Science domains.