Explain the main concepts and elements of SPARQL
The increasing accessibility of geospatial data in the form of knowledge graphs, developed in alignment with the Semantic Web vision and employing Linked Data principles, is becoming a prominent feature of the Web. The multitude of available geospatial knowledge graphs demonstrates their indispensable role within the Web of Data Cloud. Such graphs serve as central nexuses, interconnecting events, people, and objects, offering an ever-growing semantic representation of the geospatial information wealth. The resulting resources and capabilities are being leveraged to utilize, consume, and capitalize on geospatial information through the strategic deployment of knowledge graphs. The geospatial graphs are stored and managed by triple stores, which are also known as RDF stores or knowledge bases. As examples, SPARQL and GeoSPARQL are semantic query languages that are used to retrieve and process knowledge graphs. Some developments and experiences in the GIScience community have demonstrated the feasibility of expressing queries across diverse knowledge graphs to retrieve and process geospatial data from disparate and distributed sources. These efforts have facilitated the consumption of geospatial knowledge graphs through lightweight web applications or GIS applications.