Information explosion leads to continuous growth of data distributed over different data sources. However, the increasing number of data sources increases the risk of inconsistency. In such a federative setting, description logics can be applied to define a central schema that serves as a conceptual view comprising and extending the semantics of each data source. Consequently, each data source is treated as a single knowledge base that is integrated in a federated knowledge base. Following this idea, we propose an approach for automated debugging of federated knowledge bases that targets the identification and repair of inconsistency. We report on experiments with a large distributed dataset from the domain of library science.