An ontology based approach to the integration of entity-relationship schemas

In schema integration, schematic discrepancies occur when data in one database correspond to metadata in another. We explicitly declare the context that is the meta information relating to the source, classification, property etc. of entities, relationships or attribute values in entity-relationship (ER) schemas. We present algorithms to resolve schematic discrepancies by transforming metadata into the attribute values of entity types, keeping the information and constraints of original schemas. Although focusing on the resolution of schematic discrepancies, our technique works seamlessly with the existing techniques resolving other semantic heterogeneities in schema integration.

[1]  Tok Wang Ling,et al.  Issues in an Entity-Relationship Based Federated Database System , 1996, International Symposium on Cooperative Database Systems for Advanced Applications.

[2]  Amar Gupta,et al.  Formulating Global Integrity Constraints During Derivation of Global Schema , 1995, Data Knowl. Eng..

[3]  Serge Abiteboul,et al.  Foundations of Databases , 1994 .

[4]  Laks V. S. Lakshmanan,et al.  SchemaSQL: An extension to SQL for multidatabase interoperability , 2001, ACM Trans. Database Syst..

[5]  Vipul Kashyap,et al.  Semantic and schematic similarities between database objects: a context-based approach , 1996, The VLDB Journal.

[6]  Arnon Rosenthal,et al.  Using semantic values to facilitate interoperability among heterogeneous information systems , 1994, TODS.

[7]  Peter M. G. Apers,et al.  The Role of Integrity Constraints in Database Interoperation , 1996, VLDB.

[8]  Rakesh Agrawal,et al.  Storage and Querying of E-Commerce Data , 2001, VLDB.

[9]  Maurizio Lenzerini,et al.  A Methodology for Data Schema Integration in the Entity Relationship Model , 1984, IEEE Transactions on Software Engineering.

[10]  Venkataraman Ramesh,et al.  Management of Heterogeneous and Autonomous Database Systems , 1999 .

[11]  Laks V. S. Lakshmanan,et al.  On Efficiently Implementing SchemaSQL on an SQL Database System , 1999, VLDB.

[12]  Tok Wang Ling,et al.  Extending and inferring functional dependencies in schema transformation , 2004, CIKM '04.

[13]  Stéphane Bressan,et al.  Context Interchange: New Features and Formalisms for the Intelligent Integration of Information Context Interchange: New Features and Formalisms for the Intelligent Integration of Information , 1997 .

[14]  Tok Wang Ling,et al.  A Methodology for Structural Conflict Resolution in the Integration of Entity-Relationship Schemas , 2003, Knowledge and Information Systems.

[15]  Ravi Krishnamurthy,et al.  Language features for interoperability of databases with schematic discrepancies , 1991, SIGMOD '91.

[16]  Renée J. Miller Using schematically heterogeneous structures , 1998, SIGMOD '98.

[17]  Georg Gottlob Computing covers for embedded functional dependencies , 1987, PODS '87.

[18]  Stefano Spaccapietra,et al.  Model independent assertions for integration of heterogeneous schemas , 1992, The VLDB Journal.

[19]  Nelson Mendonça Mattos Integrating Information for On Demand Computing , 2003, VLDB.

[20]  Craig A. Knoblock,et al.  Semantic Query Optimization for Query Plans of Heterogeneous Multidatabase Systems , 2000, IEEE Trans. Knowl. Data Eng..

[21]  Tok Wang Ling,et al.  Resolving Constraint Conflicts in the Integration of Entity-Relationship Schemas , 1997, ER.