Ontological structures play a major role in the semantic Web; they became the target of an extensive research over the last decade. An important advance was the attempt to employ fuzzy sets and fuzzy logic techniques in representing ontologies for intrinsically vague domains of interest where most of human knowledge cannot be expressed in crisp logical formulas. Although the fuzzy approach alleviates the crispness problem, it does not deal satisfactory with the ambiguity caused by deficient discernibility of objects. We consider building rough approximations of fuzzy concepts and relations to measure the roughness of generated ontologies. The key objective of this work is to roughly approximate fuzzy concepts, entailments and sub-sumptions of a given ontology to have a better understanding of both ontology's quality and boundaries of usage. This will be useful for estimating appropriateness of existing ontologies for reasoning in incomplete domains.