Date of Award


Document Type

Master Thesis

Degree Name

Masters of Science (Research)



First Advisor

Dr. Jeanne Stynes

Second Advisor

Dr. Reinhold Kröger


This thesis presents an approach that deals with the ever-growing amount of data in knowledge bases, especially concerning knowledge interoperability and formal representation of domain knowledge. There arc multiple issues that must be addressed with current systems. A multitude of different formats, sources and tools exist in a domain, and it is desirable to develop their use further towards a standardised environment. Such an environment should support both the representation and processing of data from this domain, and the connection to other domains, where necessary. In order to manage large amounts of data, it should be possible to perform whatever actions that need to be performed on the data automatically. This requires that the domain model and actual data that is modelled by it are available in a formal, comprehensive and machine-readable format. The definition of rules must be possible as well. Management of an IT environment is examined as an example domain. Semantic Web technology delivers the base on which the solution to the aforementioned problems can be built. The solution approach presented in this thesis is based on an Web Ontology Language (OWL) ontology, which combines a domain model, instance data and rules. For the particular domain of IT management, the Common Information Model (CIM) is employed and converted into an OWL ontology. A runtime system that has capabilities for importing updated information about the managed system is developed. Current information is extracted using a CIM client module and added as instance data to the ontology. An external reasoner that is part of the runtime system is used to evaluate the information in the ontology, including the rules. Through the combination of domain data, rules that make use of structural and dynamically updated information can be built. Using the evaluation results, reactions can be triggered based on this combined information.

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