Most emerging applications, especially in science domains, maintain databases that are rich in metadata and annotation information, e.g., auxiliary exchanged comments, related articles and images, provenance information, corrections and versioning information, and even scientists’ thoughts and observations. To manage these annotated databases, numerous techniques have been proposed to extend the DBMSs and efficiently integrate the annotations into the data processing cycle, e.g., storage, indexing, extended query languages and semantics, and query optimization. In this paper, we address a new facet of annotation management, which is the discovery and exploitation of the hidden corrections that may exist in annotated databases. Such correlations can be either between the data and the annotations (data-to-annotation), or between the annotations themselves (annotation-to-annotation). We make the case that the discovery of these annotation-related correlations can be exploited in vario...