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Schema Matching and Mapping (Data-Centric Systems and Applications)

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This book provides an overview about the state-of-the-art solutions and the most recent advances in schema matching and mapping, both recognized as key areas of metadata management. Tasks involving metadata are indeed pervasive in databases and information systems and include schema evolution, schema and ontology integration and matching, XML message mapping, as well as data migration and data exchange.While research on these complex problems has been performed since several decades, we have witnessed significant progress especially in the last decade. In particular, research addressed the metadata problems in a more abstract and generic way rather than focusing on specific applications and data models. A cornerstone of this new line of research is the notion of schema mappings, i.e., expressive mappings interrelating schemas (or other metadata models such as ontologies). Furthermore, powerful operators to manipulate schemas and mappings (e.g., matching and merging of schemas or composition of mappings) have been investigated for solving various kinds of metadata-related tasks. Raising the level of abstraction for metadata management was a vision first articulated by Phil Bernstein et al. in A vision for management of complex models, ACM Sigmod Record 2000. Since then, many steps have been performed towards the various goals of matching and mapping different kinds of design artifacts (i.e., a relational schema, a web site, or a data mart), thus motivating a flurry of recent research, which we survey in this book. The book consists of ten comprehensive chapters grouped within three parts: large-scale and knowledge-driven schema matching, qualitydriven schema mapping and evolution and evaluation and tuning of matching tasks.

Schema Matching and Mapping provides an overview of the ways in which the schema and ontology matching and mapping tools have addressed information systems requirements. Topics include effective methods for matching data, mapping transformation verification, mapping-driven schema evolution and merging.

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