Data validation and cleaning are integral processes of the data quality management cycle. Domain specific knowledge is needed to detect and correct semantic errors. Ontologies can be used to represent valid and invalid attribute value combinations to detect and correct invalid data. We introduce reorganization operations for maintaining such an ontology in the data quality management cycle.