Geospatial Web Services make geospatial information available as part of the World Wide Web. Much of the geographic information on the Web are documents that require significant processing to be used as geospatial products like maps and features. Geospatial Web Services exposes services of a GIS platform to the Web. To achieve this the standards that underlie the WWW - http, html, etc. - were extended with geospatial technologies. The Web Map Service - standardized by the Open Geospatial Consortium in 1999 - marked a milestone in the development and deployment of geospatial web services. WMS along with additional standards now provide access to millions of geospatial data and services on the Web. As of 2024, over 3.5 million spatial datasets were available on the internet served by over 400,000 operational services using OGC standards.
It is difficult to share and reuse geospatial data and retrieve geospatial information because of geospatial data heterogeneity problems. Lack of semantic interoperability is one of the major problems facing GIS (Geographic Information Science/System) systems and applications today. To solve geospatial data heterogeneity problems and support geospatial information retrieval and semantic interoperability over the Web, the use of an ontology is proposed because it is a formal explicit description of concepts or meanings of words in a well-defined and unambiguous manner. Geospatial ontologies represent geospatial concepts and properties for use over the Web. OWL (Ontology Web Language) is an emerging language for defining and instantiating ontologies. OWL builds on RDF (Resource Description Framework) but adds more vocabulary for describing properties and classes. The downside of representing structured geospatial data in OWL and RDF languages is that it can result in inefficient data access. SPARQL (Simple Protocol and RDF Query Language) is recommended for general RDF query while the GeoSPARQL (Geographic Simple Protocol and RDF Query Language) protocol is proposed as an extension of SPARQL for querying geospatial data. However, the runtime cost of GeoSPARQL queries can be high due to the fine-grained nature of RDF data models. There are several challenges to using ontologies for geospatial semantic interoperability but these can be overcome through collaboration.