Schema Evolution publication categorizer

Interoperability of heterogeneous data sources has been extensively
studied in data integration applications. However, the increasing number of
tools that produce data with very different formats, such as bug tracking,
version control, etc., produces many different kinds of semantic heterogeneities.
These semantic heterogeneities can be expressed as mappings between the tools
metadata which describe the data manipulated by the tools. However, the
semantics of complex mappings (n:1, 1:m and n:m relationships) is hard to
support. These mappings are usually directly coded in executable

Mapping between heterogeneous
data is a central problem in many dataintensive
applications. In particular, using
one mapping language causes serious
limitations and makes mapping management
difficult. In this paper, we propose a solution
that can better control the trade-off between
genericity, expressiveness and efficiency of
mappings. Our solution considers mappings
as models and exploits specific mapping
engines. We define model weaving as a
generic way to establish element
correspondences. Weaving models may then
be used by a model transformation language