Geographic semantic data is growing increasingly prominent as the application and development of semantic technology advancing in the geospatial field. In order to effectively deal with geographic semantic data, fast, efficient and intelligent geographic semantic query is very necessary.The draft of GeoSPARQL specification is promoted by geographic ontology technical, SPARQL spatial expansion technical, inference rules technical, etc. technical. GeoSPARQL specification was a geographic semantic query specification released by OGC in September2012, it is intended to provide a widely-used geo-semantic query solution, so as to query heterogeneous, incompatible geographic semantic data consistently.GeoSPARQL defines the following contents:an RDF/OWL vocabulary for representing spatial information consistent with the Simple Features model;a set of SPARQL extension functions for spatial computations; a set of RTF rules for query transformation.In order to effectively process and apply geographic semantic data as well as achieve fast and efficient data retrieval, with support of ontological technology, semantic technology, etc., this paper uses the GeoSPARQL specification to study and solve several key issues about geographic semantic query, namely the SPARQL spatial expansion, efficient data organization, and intelligent content query.Major contributions of this paper are as follows:1. Build and implement spatial operator defined by the GeoSPARQL specification in SPARQL syntax layer. Adhering to the latest OGC geographic semantic query specification---GeoSPARQL, this paper has built and achieved the GeoSPARQL spatial operators in SPARQL syntax, implementing the semantic spatial relational query.2. Propose and implement the geographic semantic spatial index which meets the geographic ontology stated in GeoSPARQL regulation. According to RDF data organization and traditional spatial indexes, this paper puts forward a semantic data model-GeoQuard model, proposing and constructing a geographic semantic spatial index structure. 3. Put forward and implement a streaming data transformation method based on STX for transforming GML file to OWL file. Tackling the data transformation problem in reasoning query for the geographic semantic property, this paper proposes and implements a streaming data transformation method based on STX, fulfilling a fast and effective transformation.4. Construct and implement a parsing layer of GeoSPARQL specification, hence supporting the parsing of the ontology and ontological derivatives data along with the visualization of these data by observing the GeoSPARQL specification.Through these studies, this paper can enrich the research of semantic technology in the geospatial field, and promote the study and application of geographic semantic query to some extent. |