Quality control is an essential task within ontology development projects especially when the knowledge formalization is partially automatized. In this talk, I will present a reasoning-based, interactive approach to support the revision of formalized knowledge and reduce the required manual effort. In the presented approach, the evaluation decisions taken by a human expert are propagated in order to automatically evaluate axioms and thereby reduce the number of axioms that have to be manually evaluated. Additionally, we propose different ranking techniques that determine the order in which the expert processes the axioms. By choosing an appropriate ranking technique one can further reduce the number of manual decisions required for the revision. Our evaluation, based on data from the NanOn project, shows that the developed techniques reduce both the number of manual decisions and the computation time by a significant amount.