Schema Evolution publication categorizer

Attribute-level schema matching has proven to be an important first step in developing mappings for data exchange, integration,
restructuring and schema evolution. In this paper we investigate
contextual schema matching, in which selection conditions are associated
with matches by the schema matching process in order
to improve overall match quality. We define a general space of
matching techniques, and within this framework we identify a variety
of novel, concrete algorithms for contextual schema matching.
Furthermore, we show how common schema mapping techniques

. Much data is published on the Web in XML format satisfying schemas, and to make the Semantic Web a reality, such data needs to be interpreted with respect to ontologies. Interpretation is achieved through a semantic mapping between the XML schema and the ontology. We present work on the heuristic construction of complex such semantic mappings, when given an initial set of simple correspondences from XML schema attributes to datatype properties in the ontology. To accomplish this, we first offer a mapping formalism to capture the semantics of XML schemas.

There are many problems requiring a semantic account of a database
schema. At its best, such an account consists of mapping formulas between the
schema and a formal conceptual model or ontology (CM) of the domain. This
paper describes the underlying principles, algorithms, and a prototype of a tool
which infers such semantic mappings when given simple correspondences from
table columns in a relational schema to datatype properties of classes in an on-
tology. Although the algorithm presented is necessarily heuristic, we offer formal