Master of Computer Science, Miami University, 2008, Computer Science and Systems Analysis

OntoSELF was recently developed to provide 3D visualization of the underlying hierarchical structure of intensional ontologies. The extensions to OntoSELF focus on enhancing perception and facilitating high-level comprehension as well as low-level detail exploiting. The extensions include various visualization cues to enhance visualization perception, processing user-defined relationships in addition to the standard hierarchical IS-A relationship, user filtering on which relationships to include in the visualization, and social network analysis (SNA) metrics for additional filtering and structuring criteria, and for finding and better understanding important concepts of interest. To use standard social network analysis (SNA) techniques, a preprocessing algorithm is used to project an m-mode n-plex ontology structure to a 1-mode 1-plex sociomatrix. A high-level abstraction algorithm based on the notion of "communities of interest" is provided to simplify the social network view of the ontology to a higher level of abstraction.

Committee: Valerie V. Cross PhD (Advisor); Mufit Ozden PhD (Committee Member); James D. Kiper PhD (Committee Member) Subjects: Computer Science

Master of Computer Science, Miami University, 2007, Computer Science and Systems Analysis

Ontologies are frequently used to formalize the conceptualization of a domain. Numerous ontologies exist in a variety of domains. For example, The United Nations Standard Products and Services Code (UNSPSC) ontology and the North American Industrial Classification System ontology (NAICS) are becoming widely used in e-commerce applications and contain on the order of thousands of product categories. The Gene Ontology (GO) with over 22,000 terms is widely used in biomedical applications. Useful techniques for visualizing the overall structure are needed by both ontology users and creators to understand their structure at a high level and then be able to navigate through the levels of complexity within the ontology. Researchers in ontology visualization are beginning to recognize that ontologies demand their own specialized tools with visualization techniques that depend strongly on both the characteristics of the presented information and the supported task requiring the visualization. This thesis develops a flexible ontology 3D visualization system called OntoSELF (Ontology Scrutiny Exploiting Layouts and Filtering) that allows a user to better understand the nature and identity, i.e., self, of an ontology. It provides a variety of weighting functions from concept-lattice drawing techniques and modifies the layout based on a user-selected weighting function. OntoSELF provides very adjustable filtering capabilities based on structural metrics determined for each ontology concept. Through filtering and flexible layout, the user can then focus on particular areas of the ontology where concepts meet the criteria the user deems essential for better understanding the structure of the ontology, either to hide or abstract out complexity or to reveal intricate details of the ontology. A variety of ontologies varying in domain knowledge and sizes and a set of topology understanding tasks are used to investigate the performance of OntoSELF. To make the testing process more effi (open full item for complete abstract)

Committee: Valerie Cross (Advisor) Subjects: Computer Science