Semantic Modeling of Requirements: Leveraging Ontologies in Systems Engineering

The interdisciplinary nature of "Systems Engineering" (SE), having "stakeholders" from diverse domains with orthogonal facets, and need to consider all stages of "lifecycle" of system during conception, can benefit tremendously by employing "Knowledge Engineering" (KE) to achieve semantic agreement among all "stakeholders" for all stages of "life cycle". Present practices in "SE", such as using "Vocabularies, Processes, Standards", and "Modeling Languages" are oriented towards manual reasoning of system concepts and relations to achieve semantic agreement. "Semantic Web (SW)" is being developed to provide "KE" and automated "reasoning" to the unstructured information, in huge amounts, present on the "World Wide Web", using "Knowledge Representation" (KR) methods. Borrowing these "KE" and "KR" methods from"SW" and improvising them to solve the problems in SE is the main theme of my research. Employing "KE" methods from "SW" in "SE" requires "ontologies" that are capable to represent semantic information in a system model. In my research, I introduced "Ontology for System Engineering, OSE", for this purpose. Using OSE, a "Knowledge Base" (KB) is constructed with extracted semantic information from system model. The information is "translated, aligned, reasoned" and "queried", during different stages of proposed framework, to gain semantic agreement. The conception of a system model with agreed semantics, using "UML" or "SysML", is based on requirements model conceived by "Requirements Engineering" (RE) process. As system design proceeds, the requirements model needs to be integrated into the system model through translation of concepts. Present research in "RE" involves methodologies such as use of an "ontology" or a "Requirements Modeling Language", which have been developed independently from the system modeling environment. As a consequence, manual integration of requirements and systems models introduces inconsistencies. To overcome this major limitation, I introduced an "Ontology for Requirements Engineering" (ORE). ORE is designed to be completely compatible with "UML" and "SysML", thus enabling a seamless integration. Complete mapping between "ORE" (and "OSE") and "UML" (or "SysML") is demonstrated. "Reasoning" is used to infer implicit information in the model and to detect hidden inconsistencies. Two comprehensive case studies have been presented to demonstrate the efficiency of the proposed "ontologies" and framework. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]