A semantic approach to discovering schema mapping expressions

Yuan An, Alex Borgida, Renée J. Miller, John Mylopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

51 Scopus citations


In many applications it is important to find a meaningful relationship between the schemas of a source and target database. This relationship is expressed in terms of declarative logical expressions called schema mappings. The more successful previous solutions have relied on inputs such as simple element correspondences between schemas in addition to local schema constraints such as keys and referential integrity. In this paper, we investigate the use of an alternate source of information about schemas, namely the presumed presence of semantics for each table, expressed in terms of a conceptual model (CM) associated with it. Our approach first compiles each CM into a graph and represents each table's semantics as a subtree in it. We then develop algorithms for discovering subgraphs that are plausible connections between those concepts/nodes in the CM graph that have attributes participating in element correspondences. A conceptual mapping candidate is now a pair of source and target subgraphs which are semantically similar. At the end, these are converted to expressions at the database level. We offer experimental results demonstrating that, for test cases of non-trivial mapping expressions involving schemas from a number of domains, the "semantic" approach outperforms the traditional technique in terms of recall and especially precision.

Original languageEnglish (US)
Title of host publication23rd International Conference on Data Engineering, ICDE 2007
Number of pages10
StatePublished - 2007
Event23rd International Conference on Data Engineering, ICDE 2007 - Istanbul, Turkey
Duration: Apr 15 2007Apr 20 2007

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627


Other23rd International Conference on Data Engineering, ICDE 2007

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Information Systems


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