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Title: An Ontology Design Pattern for Surface Water Features

Surface water is a primary concept of human experience but concepts are captured in cultures and languages in many different ways. Still, many commonalities can be found due to the physical basis of many of the properties and categories. An abstract ontology of surface water features based only on those physical properties of landscape features has the best potential for serving as a foundational domain ontology. It can then be used to systematically incor-porate concepts that are specific to a culture, language, or scientific domain. The Surface Water ontology design pattern was developed both for domain knowledge distillation and to serve as a conceptual building-block for more complex surface water ontologies. A fundamental distinction is made in this on-tology between landscape features that act as containers (e.g., stream channels, basins) and the bodies of water (e.g., rivers, lakes) that occupy those containers. Concave (container) landforms semantics are specified in a Dry module and the semantics of contained bodies of water in a Wet module. The pattern is imple-mented in OWL, but Description Logic axioms and a detailed explanation is provided. The OWL ontology will be an important contribution to Semantic Web vocabulary for annotating surface water feature datasets. A discussionmore » about why there is a need to complement the pattern with other ontologies, es-pecially the previously developed Surface Network pattern is also provided. Fi-nally, the practical value of the pattern in semantic querying of surface water datasets is illustrated through a few queries and annotated geospatial datasets.« less
 [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [6] ;  [4] ;  [7] ;  [8]
  1. Ohio University
  2. University at Buffalo (SUNY)
  3. Raytheon BBN Technologies
  4. U.S. Geological Survey, Rolla, MO
  5. University of California, Santa Barbara
  6. National University of Singapore
  7. Tumbling Walls, LLC
  8. ORNL
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Conference: The Eighth International Conference on Geographic Information Science, Vienna, Austria, 20140924, 20140926
Research Org:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
ME USDOE - Office of Management, Budget, and Evaluation; ORNL work for others
Country of Publication:
United States
GIS; ontology; hydrology