Schema Evolution publication categorizer

To achieve interoperability, modern information systems
and e-commerce applications use mappings to translate
data from one representation to another. In dynamic environments
like the Web, data sources may change not
only their data but also their schemas, their semantics, and
their query capabilities. Such changes must be reflected
in the mappings. Mappings left inconsistent by a schema
change have to be detected and updated. As large, complicated
schemas become more prevalent, and as data is
reused in more applications, manually maintaining mappings
(even simple mappings like view definitions) is becoming
impractical. We present a novel framework and
a tool (ToMAS) for automatically adapting 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. We consider
a comprehensive class of mappings for relational and
XML schemas with choice types and (nested) constraints.
Our algorithm detects mappings affected by a structural
or constraint change and generates all the rewritings that
are consistent with the semantics of the mapped schemas.
Our approach explicitly models mapping choices made by
a user and maintains these choices, whenever possible, as
the schemas and mappings evolve. We describe an implementation
of a mapping management and adaptation tool
based on these ideas and compare it with a mapping generation
tool.