Geospatial Semantic Web - Softcover

Über die Autorin bzw. den Autor

Chuanrong Zhang is currently an associate professor at University of Connecticut and holds a joint appointment with Department of Geography and the Center for Environmental Sciences and Engineering (CESE). She received her PhD degree in GIS from University of Wisconsin, Milwaukee in 2004. She has several years of working experience in computer companies. Her current research interests include Internet GIS, spatial statistics, and applications of these techniques in natural resource and environmental management.

Tian Zhao obtained his Ph.D. degree in Computer Science from Purdue University in 2002. He is currently an associate professor at University of Wisconsin, Milwaukee. His research interests include programming languages, type systems, program analysis, parallel programming, Geospatial Semantic Web, and GIS.

Weidong Li is currently a professor in geospatial information engineering at Huazhong Agricultural University, and also a research professor at University of Connecticut. He received a Master’s degree in computer science from Marquette University and obtained a PhD degree in soil and water science in 1995 from China Agricultural University. His research interest is focused on geostatistics, Internet GIS, and geoinformatics for natural resource management.

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This book covers key issues related to Geospatial Semantic Web, including geospatial web services for spatial data interoperability; geospatial ontology for semantic interoperability; ontology creation, sharing, and integration; querying knowledge and information from heterogeneous data source; interfaces for Geospatial Semantic Web, VGI (Volunteered Geographic Information) and Geospatial Semantic Web; challenges of Geospatial Semantic Web; and development of Geospatial Semantic Web applications. This book also describes state-of-the-art technologies that attempt to solve these problems such as WFS, WMS, RDF, OWL, and GeoSPARQL, and demonstrates how to use the Geospatial Semantic Web technologies to solve practical real-world problems such as spatial data interoperability.