What is a Geospatial Ontology? (2JO4)
In general an ontology specifies of a vocabulary of concepts predicates together with some indication of their meanings. There is a range of levels of precision with which meaning is specified, but an overall goal is that people often want to share a common understanding of the structure of information among people or software agents. Often there are twin targets to make the meaning clear to people while allowing a degree of "automated" processing. In this case an ontology is used to make explicit the semantics and knowledge contained within efforts such as software applications. (2JOA)
An ontological model is made up of classes/concepts (at least partial hierarchical) along with properties & attributes for these concepts (usually with descriptions to help humans)plus constraints on properties and attributes. The backbone on an Ontology is made up of Classes in a formal Hierarchy. (2JOB)
A class is a concept in the domain so we may have a class of organizations (e.g. USGS) or a class of regions (e.g. Mid-Atlantic States). A class also has a population. It is a collection of the elements with similar properties defined by the class concept. Thus there are instances of states in the Mid-Atlantic class. (2JOC)
(2JDG) (2JO8)
As part of such an effort an ontology can be used to enable reuse of domain knowledge and to make domain assumptions explicit or to separate domain knowledge in a declarative form from the operational knowledge which can be implemented in software. (2JDH) (2JO9)
Geospatial ontologies take as their domain a range of geospatial concepts such as geospatial objects, relations and features. Relations start with seemingly basic things such as topological ideas of "near", "connected" and "around" as well as other common spatial relationships in use, equals, disjoint, intersects, touches, crosses, within, contains, and overlaps. Spatial objects include abstract spatial notions such as "place" or "locations". Geospatial objects may be abstracted to geometrical concepts like a point or polygon area concepts in order to be understood at different levels of granularity. Thus an area like DC can be presented as a small oval on a national map or a complex area when zoomed up close. Features include "size" and "volume". These provide summative information about spatial things. Besides these simple ideas it also includes more macro, aggregated and complex concepts like "river", "estuary", "pond" and "lake". Know about each of these would include relations to other things (e.g. each has boundaries with non-water objects, a river may connect to a lake etc.) Ontologies attempt to distinguish all of these concepts in explicit and precise ways to avoid confusions. (2JO7)
Thus an ontology's vocabulary might want to distinguish something called Y that is near X and say: If X is near Y then X and Y are not connected, and also that if X is near Y then Y is also near X. These can be stated in an ontology as axioms rule out the possibility of interpreting “near” as “connected”. One would also need to distinguish near from far since neither is connected. (2JO6)