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Empirical identification of domain and cross-domain failure analysis ontology

Posted on:2007-07-28Degree:Ph.DType:Dissertation
University:Arizona State UniversityCandidate:Edgington, Theresa MFull Text:PDF
GTID:1448390005961322Subject:Business Administration
Abstract/Summary:
As research relating to knowledge management, business process intelligence, and failure analysis continues to grow, the need to identify relevant ontology becomes a crucial element for these research endeavors. Ontology relates to the characterization of explicit and sometimes subtle aspects of meaning. It can frame an underlying model of understanding that encompasses a contextually bounded endeavor, such as a business process. Much ontology research has been bound exclusively to a domain, such as software development, enterprise process, or medical disease. Little research in Information Systems has attempted to identify ontology to find common constructs uniting disparate domains that perform common business processes. This research investigates issues of commonality existing in business processes relating to information technology services, enterprise software development, semiconductor manufacturing, and public health by ontological identification of empirical data. The research questions pursued are stated as follows: (1) How can empirical metadata and its associated data be used to identify ontological constructs in a failure analysis business process context, and (2) How can individual domain ontologies be integrated to create a cross domain failure analysis ontology? The findings suggest that the business process constructs influencing explicit data elements in the ontology can be quantifiably identified (Process Tracking, Customer Input, Resolution, and Anomaly) and that they are common across disparate domains. Further findings suggest that domain ontologies exhibit unique behavior which broadens and enriches the definition of context with regard to knowledge. Overall, domain ontology identification can be a substantial preliminary aid to domain experts and knowledge engineers for many activities involving process or knowledge discovery, intelligent analysis, and process optimization through organizational learning or automation. Cross-domain ontological analysis can be valuable input to business process improvement activities.
Keywords/Search Tags:Failure analysis, Business process, Domain, Ontology, Empirical, Identification
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