Ontologies are powerful and expressive mechanism for knowledge representation to support artificial intelligence applications. In many practical domains it is natural to use vague, probabilistic or imprecise knowledge. In this research we will discuss approaches for combining crisp, probabilistic and vague theories for modelling and automated reasoning with knowledge in practical domains. We also propose a methodology for mixed modelling of crisp and fuzzy or probabilistic knowledge by ontologies.