Schema Evolution publication categorizer

In dynamic environments like theWeb, data sources
may change not only their data but also their schemas, their
semantics, and their query capabilities.When a mapping is left
inconsistent by a schema change, it has to be detected and updated.
We present a novel framework and a tool (ToMAS)
for automatically adapting (rewriting) mappings as schemas
evolve. Our approach considers not only local changes to a
schema but also changes that may affect and transform many
components of a schema. Our algorithm detects mappings affected
by structural or constraint changes and generates all
the rewritings that are consistent with the semantics of the
changed schemas. Our approach explicitly models mapping
choices made by a user and maintains these choices, whenever
possible, as the schemas and mappings evolve. When
there is more than one candidate rewriting, the algorithm may
rank them based on how close they are to the semantics of the
existing mappings.