Paper Info
Title
Using Complex Correspondences for Integrating Relational Data Sources
Abstract
Data Integration (DI) is the problem of combining a set of heterogeneous, autonomous data sources and providing the user with a unified view of these data. Integrating data raises several challenges, since the designer usually encounters incompatible data models characterized by differences in structure and semantics. One of the hardest challenges is to define correspondences between schema elements (e.g., attributes) to determine how they relate to each other. Since most business data is currently stored in relational databases, here present a declarative and formal approach to specify 1-to-1, 1-m, and m-to-n correspondences between relational schema components. Differently from usual approaches, our (CAs) have semantics and can deal with outer-joins and data-metadata relationships. Finally, we demonstrate how to use the CAs to generate mapping expressions in the form of SQL queries, and we present some preliminary tests to verify the performance of the generated queries.
Year
DOI
Venue
2014
10.1007/978-3-319-22348-3_4
Lecture Notes in Business Information Processing
Keywords
Field
DocType
Schema matching,Correspondence assertions,Data integration,Relational model
Data integration,SQL,Data modeling,Data mining,Expression (mathematics),Relational database,Computer science,Schema matching,Relational model,Semantics
Conference
Volume
ISSN
Citations 
227
1865-1348
0
PageRank 
References 
Authors
0.34
14
3
Name
Order
Citations
PageRank
Valéria Magalhães Pequeno174.96
Helena Galhardas253.19
Vânia Maria Ponte Vidal39437.28