Resolving Schematic Discrepancy in the Integration of Entity-Relationship Schemas

In schema integration, chematic discrepancies occur when data in one database correspond to metadata in another. We define this kind of semantic heterogeneity in general using the paradigm of 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 entities, keeping the information and constraints of original schemas. Although focusing on the resolution of schematic discrepancies, our technique works seamlessly with existing techniques resolving other semantic heterogeneities in schema integration.

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

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

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

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

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

[6]  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 .

[7]  Tok Wang Ling,et al.  Designing semistructured databases using ORA-SS model , 2001, Proceedings of the Second International Conference on Web Information Systems Engineering.

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

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

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

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

[12]  ChenPeter Pin-Shan.  The entity-relationship modeltoward a unified view of data , 1976 .

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

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

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

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

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

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

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

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

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

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