In a multidatabase system, schematic conflicts between two objects are usually of interest only when the objects have some semantic similarity. We use the concept of semantic proximity, which is essentially an abstraction/mapping between the domains of the two objects associated with the context of comparison. An explicit though partial context representation is proposed and the specificity relationship between contexts is defined. The contexts are organized as a meet semi-lattice and associated operations like the greatest lower bound are defined. The context of comparison and the type of abstractions used to relate the two objects form the basis of a semantic taxonomy. At the semantic level, the intensional description of database objects provided by the context is expressed using description logics. The terms used to construct the contexts are obtained from {\em domain-specific ontologies}. Schema correspondences are used to store mappings from the semantic level to the data level and are associated with the respective contexts. Inferences about database content at the federation level are modeled as changes in the context and the associated schema correspondences. We try to reconcile the dual (schematic and semantic) perspectives by enumerating possible semantic similarities between objects having schema and data conflicts, and modeling schema correspondences as the projection of semantic proximity with respect to (wrt) context.