Schema Evolution publication categorizer

Schema mappings are high-level specifications that describe the relationship
between two database schemas. Two operators on schema
mappings, namely the composition operator and the inverse operator,
are regarded as especially important. Progress on the study of
the inverse operator was not made until very recently, as even finding
the exact semantics of this operator turned out to be a fairly delicate
task. Furthermore, this notion is rather restrictive, since it is rare that
a schema mapping possesses an inverse.
In this paper, we introduce and study the notion of a quasi-inverse

We study the problem of answering queries through a target schema, given a set of mappings between one or more source schemas and this target schema, and given that the data is at the sources. The schemas can be any combination of relational or XML schemas, and can be independently designed. In addition to the source-to-target mappings, we consider as part of the mapping scenario a set of target constraints specifying additional properties on the target schema.

Many problems in information integration rely on specifications, called schema mappings, that model the relationships between schemas. Schema mappings for both relational and nested data are well-known. In this work, we present a new formalism for schema mapping that extends these existing formalisms in two significant ways. First, our nested mappings allow for nesting and correlation of mappings. This results in a natural programming paradigm that often yields more accurate specifications.

Schema mappings are high-level specifications that describe the relationship between database schemas. Schema mappings are prominent in several different areas of database management, including database design, information integration, data exchange, metadata management, and peer-to-peer data management systems. Our main aim in this paper is to present an overview of recent advances in data exchange and metadata management, where the schema mappings are between relational schemas. In addition, we highlight some research issues and directions for future work.

In this paper we motivate and describe materialized views, their applications, and the problems and techniques for their maintenance. We present a taxonomy of view maintenance problems based upon the class of views considered, upon the resources used to maintain the view, upon the types of modications to the base data that are considered during maintenance, and whether the technique works for all instances of databases and modications. We describe some of the view maintenance techniques proposed in the literature in terms of our taxonomy.

Clio, the IBM Research system for expressing declarative schema mappings, has progressed in the past few years from a research prototype into a technology that is behind some of IBM's mapping technology. Clio provides a declarative way of specifying schema mappings between either XML or relational schemas. Mappings are compiled into an abstract query graph representation that captures the transformation semantics of the mappings. The query graph can then be serialized into different query languages, depending on the kind of schemas and systems involved in the mapping.

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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

Schemas evolve over time to accommodate the changes in
the information they represent. Such evolution causes invalidation
of various artifacts depending on the schemas,
such as schema mappings. In a heterogenous environment,
where cooperation among data sources depends essentially
upon them, schema mappings must be adapted to reflect
schema evolution. In this study, we explore the mapping
composition approach for addressing this mapping adaptation
problem. We study the semantics of mapping composition
in the context of mapping adaptation and compare