ABSTRACT
Geospatial data contain information about a physical object that can be represented by numerical values in a geographic coordinate system. Geospatial data represents the location, size, and shape of an object on earth such as a school, house, sea, park or county. Remote sensing, global positioning system, geographic information system, and volunteered geographic information (VGI) are major modern geospatial technologies to collect and handle geospatial data. VGI data sets may have the following characteristics: large in volume, subject to dynamic changes and updates, collected through crowdsourcing architectures using different devices and technologies, and contain a mixture of structured and unstructured information. Ontologies provide the semantic congruity, consistency, and clarity to support big geospatial data analysis and knowledge extraction. Ontologies may make it possible to exploit big geospatial data in the context of their relationships with other existing data. Ontology matching is another important challenge for sharing big geospatial data over the geospatial semantic web.
