Schema Evolution publication categorizer

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 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.