Date of Award

Fall 12-11-2020

Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science (MS)


Computer Science


Torsten Hahmann

Second Committee Member

Roy Turner

Third Committee Member

Sepideh Ghanavati


With the amount of data collected everyday ever expanding, techniques which allow com- puters to semantically understand data are growing in importance. Ontologies are a tool to describe the relationships connecting data so that computers can correctly interpret and combine data from many sources. An ontology about water needs to describe what the term "river" may refer to: An arbitrary river or one usable for navigation; a single tributary or an entire river network; the riverbed or the water itself? Well-designed ontologies can be shared, reused, and extended across multiple applications and facilitate betters integration of different data collections.

Common Logic (CL) and the Web Ontology Language (OWL) are two logic based languages of popular interest. However, ontologies developed in either of these languages are not easily consumed by users of the other language. By utilizing the first order properties of Common Logic, an automated approximation routine between CL and OWL is provided. OWL, being less expressive than CL, is capable of being totally represented by logically equivalent CL axioms. Leveraging the logical equivalence, we provide a method of axiom normalization and extraction in order to construct robust OWL ontologies from existing CL sources. This increases CL ontology intelligibility, and allows the automatic construction of OWL versions of existing reference ontologies. Further, the benefits of such a translation are demonstrated by applying previously exclusive OWL tooling and analysis techniques to evaluate the translated ontologies.