Evolving from semantic network notions, ontologies have become a cornerstone in supporting interoperability and facilitating knowledge management and configuration. With the availability of useable tools, the number of ontologies increased rapidly, leading to more and more complex knowledge bases containing redundant, useless, or not very well structured information with regard to their usage. This has a negative impact on the efficiency of the semantic-based systems, especially at the reasoner and the storage level. Within this project we propose an ontology refactoring technique that aims to improve the efficiency of semantics-based systems by adapting the system’s internal description of ontologies. The changes proposed by the refactoring process will operate only on the system’s internal representation of an ontology and will not be reflected into original ontology structure. We propose the fundamental research for finding an optimal system’s internal description of an ontology with regard to its usage, by analyzing, specifying and implementing a prototype for ontology refactoring in an evolutionary framework.