Schema Evolution publication categorizer

The translation of information between heterogeneous rep-
resentations is a long standing issue. With the large spreading of cooper-
ative applications fostered by the advent of the Internet the problem has
gained more and more attention but there are still few and partial solu-
tions. In general, given an information source, different translations can
be defined for the same target model. In this work, we first identify gen-
eral properties that “good” translations should fulfill. We then propose
novel techniques for the automatic generation of model translations. A
translation is obtained by combining a set of basic transformations and
the above properties are verified locally (at the transformation level)
and globally (at the translation level) without resorting to an exhaustive
search. These techniques have been implemented in a tool for the man-
agement of heterogeneous data models and some experimental results
support the effectiveness and the efficiency of the approach