Databases Reference
In-Depth Information
Chapter 7
Schema Mapping Evolution Through
Composition and Inversion
Ronald Fagin, Phokion G. Kolaitis, Lucian Popa, and Wang-Chiew Tan
Abstract
Mappings between different representations of data are the essential
building blocks for many information integration tasks. A schema mapping is a
high-level specification of the relationship between two schemas, and represents a
useful abstraction that specifies how the data from a source format can be trans-
formed into a target format. The development of schema mappings is laborious and
time consuming, even in the presence of tools that facilitate this development. At
the same time, schema evolution inevitably causes the invalidation of the existing
schema mappings (since their schemas change). Providing tools and methods that
can facilitate the adaptation and reuse of the existing schema mappings in the con-
text of the new schemas is an important research problem.
In this chapter, we show how two fundamental operators on schema mappings,
namely composition and inversion, can be used to address the mapping adaptation
problem in the context of schema evolution. We illustrate the applicability of the
two operators in various concrete schema evolution scenarios, and we survey the
most important developments on the semantics, algorithms, and implementation of
composition and inversion. We also discuss the main research questions that still
remain to be addressed.
1
Introduction
Schemas and schema mappings are two fundamental metadata components that are
at the core of heterogeneous data management. Schemas describe the structure of
the various databases, while schema mappings describe the relationships between
B
R. Fagin (
) and L. Popa
IBM Almaden Research Center, San Jose, CA, USA
e-mail:
fagin@almaden.ibm.com, lucian@almaden.ibm.com
P.G. Kolaitis and W.-C. Tan
IBM Almaden Research Center, San Jose, CA, USA
and
UC Santa Cruz, Santa Cruz, CA 95064, USA
e-mail:
kolaitis@cs.ucsc.edu
,
wctan@cs.ucsc.edu
