Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information Sciences

Ontology evolution is type of ontology changes that focuses on updating ontologies to changes in a certain domain and to changes of the conceptualization about that domain. The problem of ontology evolution is that it depends on ontology engineers to detect the need of evolution, to discover missing knowledge, and to implement all necessary changes to accommodate new knowledge properly in their ontologies. In addition, they have to ensure that their ontologies are still in its consistency state after evolution. Several research e{uFB00}orts provide various semi-automatic solutions to support ontology engineers. However, this support is not enough to keep ontologies up-to-date. The proposed approach provides a model for automating the process of ontology evolution. This model enables ontologies to acquire its missing domain knowledge without violating its underlying conceptualization and with maintaining its consistency. The proposed model consists of five main processes: Evolution detection, Evolution source, Evolution control, (4) evolution consistency, and (5) evolution implementation. These five processes are triggered when an ontology receives a query from the user or an application, such that this query contains a term does not exist in the ontology. This term initiates the evolution detection process which looks for that term in all possible domain ontologies. When the evolution detection process finds the missing term in one or more domain ontologies, the next processes of the model work consecutively and automatically

Issued also as CD