An Applied Ontology for Semantics Associated with Surface Water Features

Surface water land cover plays a major role in a range of geographic studies, including climate cycles, landform generation, and human natural resource use settlement. Extensive surface water data resources exist from geographic information systems (GIS), remote sensing, and real-time hydrologic monitoring technologies. An applied ontology for surface water was designed to create an information framework to relate data in disparate formats. The objective for this project was to test whether concepts derived from a GIS hydrographic data model based on cartographic relational table attribute data can be formalized for semantic technology and to examine what differences are evident using the ontology for database semantic specification. The surface water ontology (SWO) was initially derived from the National Hydrography Dataset (NHD) GIS data model. The hypothesis was that ontology semantics can be consistent with a long-term empirically collected database. An automated conversion of classes and properties was then manually refined with the support of an upper ontology. The results were tested for reliable class associations, inferred information, and queries using SPARQL Protocol and RDF Query Language (SPARQL). The ontology reflects studies of the physical environment, the objectives of the supporting institution, the reuse of GIS, and the adaptation of semantic technology. The results contribute to the development of an ontology model that leverages large data volumes with information user access.