Schema Evolution publication categorizer

The data mapping problem is to discover effective mappings
between structured representations of data. These
mappings are the basic ‘glue’ for facilitating large-scale
ad-hoc information sharing between autonomous peers in a
dynamic environment. Automating their discovery is one of
the fundamental unsolved challenges for information integration
and sharing on the Web. We outline a general approach
to automating the discovery of mappings between
relational data sources which leverages new perspectives
on the data mapping problem and report on a prototype implementation.
Our approach utilizes heuristic search within
a space delineated by basic relational transformation operators.
A further novelty of our approach is that these operators
include data to metadata transformations (and vice
versa), allowing a generalization of previous solutions such
as token-based schema matching.