Ontologies are valuable tools for knowledge representation and important building blocks of the Semantic Web. They are not static and can change over time. Changing an ontology can be necessary for various reasons: the domain that is represented by an ontology can change or an ontology is reused and must be adapted to the new context. In addition, modeling errors could have been introduced into the ontology which must be found and removed. The non-triviality of the change process has led to the emerge of ontology change as an own field of research. The removal of knowledge from ontologies is an important aspect of this change process, because even the addition of new knowledge to an ontology potentially requires the removal of older, conflicting knowledge. Such a removal must be performed in a thought-out way. A naïve change of concepts within the ontology can easily remove other, unrelated knowledge or alter the semantics of concepts in an unintended way [2]. For these reasons, this thesis introduces a formal operator for the fine-grained retraction of knowledge from EL concepts which is partially based on the postulates for belief set contraction and belief base contraction [3, 4, 5] and the work of Suchanek et al. [6]. For this, a short introduction to ontologies and OWL 2 is given and the problem of ontology change is explained. It is then argued why a formal operator can support this process and why the Description Logic EL provides a good starting point for the development of such an operator. After this, a general introduction to Description Logic is given. This includes its history, an overview of its applications and common reasoning tasks in this logic. Following this, the logic EL is defined. In a next step, related work is examined and it is shown why the recovery postulate and the relevance postulate cannot be naïvely employed in the development of an operator that removes knowledge from EL concepts. Following this, the requirements to the operator are formulated and properties are given which are mainly based on the postulates for belief set and belief base contraction. Additional properties are developed which make up for the non-applicability of the recovery and relevance postulates. After this, a formal definition of the operator is given and it is shown that the operator is applicable to the task of a fine-grained removal of knowledge from EL concepts. In a next step, it is proven that the operator fulfills all the previously defined properties. It is then demonstrated how the operator can be combined with laconic justifications [7] to assist a human ontology editor by automatically removing unwanted consequences from an ontology. Building on this, a plugin for the ontology editor Protégé is introduced that is based on algorithms that were derived from the formal definition of the operator. The content of this work is then summarized and a final conclusion is drawn. The thesis closes with an outlook into possible future work.