Surface Network Ontology Design Patterns for Linked Topographic Data

The vision of Linked Topographic Data is critical for the Semantic Web, since topographic data are fundamental to a wide range of geoscientific analyses and mapping of geographic phenomena. Terrain datasets are probably the most important for Linked Topographic Data. Terrain is computationally represented using a continuous field data model (2-D surfaces), but the Semantic Web needs discrete objects for assigning URIs. This prevents terrain surface datasets from being shared on the Semantic Web—which is ironical given the availability of incredibly high resolution terrain data. Surface networks, which are a topologically connected set of shape-critical points, lines, and areal districts, can be used to share information about surfaces on the Semantic Web. In this paper, we reinterpret surface network theory for Linked Topographic Data, and present two OWL ontology design patterns. Surface Network is a template pattern intended for any type of surface network. It formalizes only the topological connections between surface network elements, since formalized of the metric properties requires commitment to a domain-specific spatial ontology. Geospatial SNODP extends SNODP for metric geographic space through alignment with the GeoSPARQL geospatial ontology. It can be used to annotate any geospatial surface network, but is expected to primarily serve as a core terrain ontology for Linked Topographic Data. CyberInfrastructure and Geospatial Information Laboratory (CIGI) & National Center for Supercomputing Applications (NCSA), University of Illinois at Urbana-Champaign, Urbana, IL, USA.