AbstractIn the context of the Semantic Web, ontologies refer to the consensual and formal description of shared concepts in a domain. Ontologies are said to be a way to aid communication between humans and machines and also between machines for agent communication. The importance of ontologies for providing a shared understanding of common domains, and as a means for data exchange at the syntactic and semantic level has increased considerably in the last years. Therefore, ontology management becomes a significant task to make distributed and heterogeneous knowledge bases available to the end users. Ontology alignment is the process where ontology from different domains can be matched and processed further together, hence sharing a common understanding of the structure of information among different people.
This research starts from a comprehensive review of the current development of ontology, the concepts of ontology alignments and relevant approaches. The first motivation of this work is trying to summarise the common features of ontology alignment and identify underdevelopment areas of ontology alignment.
It then works on how complex businesses can be designed and managed by semantic modelling which can help define the data and the relationships between these entities, which provides the ability to abstract different kinds of data and provides an understanding of how the data elements relate.
The main contributions of this work is to develop a framework of handling an important category of ontology alignment based on the logical composition of classes, especially under a case that one class from a certain domain becomes a logic prerequisites (assumption) of another class from a different domain (commitment) which only happens if the class from the first domain becomes valid. Under this logic, previously un-alignable classes or miss-aligned classes can be aligned in a significantly improved manner. A well-known rely/guarantee method has been adopted to clearly express such relationships between newly-alignable classes. The proposed methodology has be implemented and evaluated on a realistic case study.
|Date of Award||Nov 2012|
|Supervisor||Shikun Zhou (Supervisor), Mark Xu (Supervisor) & Dylan Jones (Supervisor)|