Schema Evolution publication categorizer

Matching elements of two data schemas or two data instances plays a key role in data warehousing, e-business, or even biochemical applications. In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios. The algorithm takes two graphs (schemas, catalogs, or other data structures) as input, and produces as output a mapping between corresponding nodes of the graphs. Depending on the matching goal, a subset of the mapping is chosen using filters. After our algorithm runs, we expect a human to check and if necessary adjust the results.

The future of the Semantic Web depends on whether or not we succeed to integrate reliably thousands of online applications, services, and databases. These systems are tied together using mediators, mappings, database views, and transformation scripts. Model-management aims at reducing the amount of programming needed for the development of such integrated applications. We present a first complete prototype of a generic model-management system, in which high-level operators are used to manipulate models and mappings between models.

Model management aims at reducing the amount of programming needed for the development of metadata-intensive applications. We present a first complete prototype of a generic modelmanagement system, in which high-level operators are used to manipulate models and mappings between models. We define the key conceptual structures: models, morphisms, and selectors, and describe their use and implementation. We specify the semantics of the known model-management operators applied to these structures, suggest new ones, and develop new algorithms for implementing the individual operators.