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

Doctor of Philosophy, Case Western Reserve University, 2019, EECS - Computer and Information Sciences

Biomedical ontologies and standardized terminologies play an important role in healthcare information management, extraction, and data integration. The quality of ontologies impacts its usability. One of the quality issues is not conforming lattice property, a generally applicable ontology design principle. Non-lattice structures are often indicative of anomalies in ontological systems and, as such, represent possible areas of focus for subsequent quality assurance work. Quality assurance of ontologies is an indispensable part of the terminology development cycle. This dissertation presents a non-lattice based ontology quality assurance workflow, along with involved approaches, algorithms, and applications. The general steps of non-lattice based ontology quality assurance include: (1) extracting non-lattice fragments; (2) detecting potential defects and proposing remediation suggestions; (3) reviewing and validating these suggested remediations. For (1), a general MapReduce pipeline, called MaPLE (MapReduce Pipeline for Lattice-based Evaluation), is developed for extracting non-lattice fragments in large partially ordered sets. Using MaPLE in a 30-node Hadoop local cloud, we systematically extracted non-lattice fragments in 8 SNOMED CT versions from 2009 to 2014, with an average total computing time of less than 3 hours per version. Compared with previous work, which took about 3 months, MaPLE makes it feasible not only to perform exhaustive structural analysis of large ontological hierarchies but also to systematically track structural changes between versions. Our change analysis showed that the average change rates on the non-lattice pairs are up to 38.6 times higher than the change rates of the background structure (concept nodes). For (2), two methods, NEO and Spark-MCA, are proposed. NEO is a systematic structural approach for embedding of FMA fragments into the Body Structure hierarchy to understand the structural disparity of the subsumption relat (open full item for complete abstract)

Committee: Guo-Qiang Zhang (Advisor); Kenneth Loparo (Committee Chair); Xu Rong (Committee Member); Li Pan (Committee Member) Subjects: Biomedical Research; Computer Science; Health; Information Science

Doctor of Philosophy, The Ohio State University, 2009, Geography

This study pursues questions about the top-down and the bottom-up directions of geographical thinking. A question about the top-down direction: 1) how geographical concepts could influence spatial data, is asked in the first half of the study, and another question for the bottom-up direction: 2) how existing data could inform geographical concepts, is asked in another half of the study. To answer the first question, Part 1 deals with the uncertainty of an exurban concept as a primary example, since there are many different definitions of exurbanization and the spatial boundaries based on them are not identical. Several definitions of exurbanization are investigated to determine how they represent exurban areas, and formal representations of the fuzzy-set approach are developed to analyze and visualize the uncertainty of the exurban definitions. The study develops a software interface that would allow interactive exploration, analysis, negotiation, and visualization of uncertain geographical concepts. Selected exurban definitions and empirical spatial data demonstrate concept comparison and concept creation activities using the interface. A case study of five different definitions of exurbanization in Ohio, U.S. shows different degrees of agreement on the exurban boundary, and also illustrates an impact of different approaches to negotiate the multiple definitions. In addition, Part 1 provides results from user evaluations of the developed software interface to better support the exchange of knowledge and communication between exurban stakeholders in Ohio. Findings from the evaluation indicate that the software interface could be useful for urban ontology research and land use, with support of the different ontologies of various actors for a common concept. To answer the second question, Part 2 attempts to derive some time-geography concepts from a set of spatio-temporal choreographic information developed by a multi-disciplinary project, “The Synchronous Objects pro (open full item for complete abstract)

Committee: Ola Ahlqvist (Advisor); Noel Cressie (Committee Member); Darla Munroe (Committee Member); Alan Price (Committee Member) Subjects: Dance; Design; Geography; Statistics

Master of Computer Science, Miami University, 2009, Computer Science and Systems Analysis

Research in ontology visualization provides software tools for ontology users to understand the structure of and to navigate through the complexity of a large ontology. OntoSELF was previously developed to provide a sophisticated user the ability to combine various weighting and filtering options to create a 3D ontology visualization. The inexperienced user, however, may have difficulty using OntoSELF since it requires mastery of technical details to produce the desired visualization. To allow novice users to easily perform topology understanding tasks on ontologies, the topology query (TQ) system OntoSELF+TQ has been developed. Users of OntoSELF+TQ can specify characteristics and constraints on components of the ontology to produce a visualization that helps them better understand the topology of the ontology. The querying capabilities of OntoSELF+TQ are demonstrated and evaluated through a small user study and system performance evaluations that exercise a wide variety of queries for numerous tasks common to understand ontologies.

Committee: Valerie Cross PhD (Advisor); James Kiper PhD (Committee Member); Eric Bachmann PhD (Committee Member) Subjects: