THE SEMANTIC GEOSPATIAL PROBLEM SOLVING ENVIRONMENT: AN ENABLING TECHNOLOGY FOR GEOGRAPHICAL PROBLEM SOLVING UNDER OPEN, HETEROGENEOUS ENVIRONMENTS
Open Access
- Author:
- Luo, Junyan
- Graduate Program:
- Geography
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- December 15, 2006
- Committee Members:
- Mark N Gahegan, Committee Chair/Co-Chair
Frederico T Fonseca, Committee Member
Brenton Yarnal, Committee Member
Ian J Turton, Committee Member - Keywords:
- Geographical Problem Solving
Semantics
Automated Planning
Knowledge Representation
Problem Solving Environment
Semantic Geospatial PSE - Abstract:
- This thesis presents a conceptual and computational framework for the Semantic Geospatial Problem Solving Environment, an enabling technology for geographical problem solving under today’s open, heterogeneous environment. The framework adopts an open software architecture to integrate different geospatial information technologies, employs the dataflow-based visual programming interface to facilitate front-end user task construction, and most importantly, utilizes structurally represented semantic knowledge to assist and automate the construction of geographical applications. The major contribution of this thesis is the development of a semantic model of geographical problem solving, which synthesizes aspects of knowledge representation and reasoning to capture and model the meanings of geospatial information technologies and geographical applications. Three levels of semantics are addressed according to C. S. Peirce’s theory of pragmatism, including the first level semantics about individual resources, the second level semantics about relations, and the third level semantics related to geographical applications. Correspondingly, the idea of proxy representation is introduced to signify the meanings of individual resources under different interpretation contexts, and the first order model theory is adopted to build the logical structures that connect individual resources together. Then automated problem solving tools are developed based on cognitive models of problem solving and automated planning techniques, which support three useful modes of reasoning in geographical application construction, including incremental problem solving, prototype refinement, and task decomposition. After that, the proposed semantic model is implemented based on the World Wide Web Consortium’s Web Ontology Language to facilitate the sharing of semantics on the Semantic Web. Finally, a reference implementation is described to illustrate the concepts and ideas discussed in the thesis.