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

In this paper, we illustrate a preliminary approach to the
translation of Web data between heterogeneous formats. This work fits
into a larger pro ject whose aim is the development of a tool for the man-
agement of data described according to a large variety of formats used on
the Web and the (semi)automatic translation of schemes and instances
from one model to another. Data translations operate over XML repre-
sentations of instances and rely on a uniform representation of models
that we call metamodel. The metamodel shows structural diversities and

Extensible Markup Language (XML) is fast becoming the new standard for data representation and exchange on the World Wide Web, e.g., in B2B e-commerce. Modern enterprises need to combine data from many sources in order to answer important business questions, creating a need for integration of web-based XML data.

In this chapter, three semantics-based schema conversion methods are presented:
1) CPI converts an XML schema to a relational schema while preserving semantic
constraints of the original XML schema, 2) NeT derives a nested structured
XML schema from a flat relational schema by repeatedly applying the nest operator
so that the resulting XML schema becomes hierarchical, and 3) CoT takes a relational
schema as input, where multiple tables are interconnected through inclusion dependencies
and generates an equivalent XML schema as output.

A methodology for extracting an extended Entity-Relationship (EER) model from a relational database is presented. Through a combination of data schema and data instance analysis, an EER model is derived which is semantically richer and more comprehensible for maintenance and design purposes than the original database. Classification schemes for relations and attributes necessary for the EER model extraction are derived and justified. These have been demonstrated to be implementable in a knowledge-based system; a working prototype system which does so is briefly discussed.

We describe MIDST, an implementation of the model management
operator ModelGen, which translates schemas from one model
to another, for example from OO to SQL or from SQL to XSD. It extends
past approaches by translating database instances, not just their
schemas. The operator can be used to generate database wrappers (e.g.
OO or XML to relational), default user interfaces (e.g. relational to
forms), or default database schemas from other representations. The approach
translates both schemas and data: given a source instance I of a

We demonstrate a prototype that translates schemas from a source metamodel (e.g., OO, relational, XML) to a target metamodel. The prototype is integrated with Microsoft Visual Studio 2005 to generate relational schemas from an object-oriented design. It has four novel features. First, it produces instance mappings to round-trip the data between the source schema and the generated target schema. It compiles the instance mappings into SQL views to reassemble the objects stored in relational tables.