A Metadata Approach to Resolving Semantic Conflicts

In this paper we describe a rule-based approach to semantic specification that can be used to establish semantic agreement between a source and receiver. Query processing techniques use these specifications along with conversion routines and query modification to guarantee correct data semantics. This work also examines the effect of changing data semantics. These changes may occur at the source of the data or they may be changes in the specifications of the dat,a semantics for the application, Methods are described for detecting these changes and for determining if the database can continue to supply meaningful data to the application. These methods for semanlic reconcilia2ion are necessary for determining logical connectivity between a data source (database) and a data receiver (application). Though described in terms of the source-receiver model, these techniques can also be used for semantic reconciliation and schema integration for multidatabase systems. Keywords[data dictionaries, heterogeneous databases, metadata, query modification, schema integration, semantic conflicts]

[1]  John L. McCarthy,et al.  Metadata Management for Large Statistical Databases , 1982, VLDB.

[2]  Margaret Henderson Law,et al.  Guide to information resource dictionary system applications , 1988 .

[3]  David W. Embley,et al.  An approach to schema integration and query formulation in federated database systems , 1987, 1987 IEEE Third International Conference on Data Engineering.

[4]  Edward Sciore,et al.  A method for automatic rule derivation to support semantic query optimization , 1992, TODS.

[5]  Jonathan J. King QUIST: A System for Semantic Query Optimization in Relational Databases , 1981, VLDB.

[6]  Stuart E. Madnick,et al.  Composite information systems : resolving semantic heterogeneities , 1991 .

[7]  James A. Larson,et al.  Federated databases: architectures and integration , 1990 .

[8]  Clement T. Yu,et al.  Determining relationships among attributes for interoperability of multi-database systems , 1991, [1991] Proceedings. First International Workshop on Interoperability in Multidatabase Systems.

[9]  Tom M. Mitchell,et al.  Learning improved integrity constraints and schemas from exceptions in databases and knowledge bases , 1986 .

[10]  Stanley B. Zdonik,et al.  Knowledge-Based Query Processing , 1980, VLDB.

[11]  Amit P. Sheth,et al.  Attribute Relationships: An Impediment in Automating Schema Integration , 1989 .

[12]  L. Napolitano Materials , 1984, Science.

[13]  Jack Minker,et al.  Semantic Query Optimization in Expert Systems and Database Systems , 1984, Expert Database Workshop.

[14]  Jintae Lee,et al.  Partially shared views: a scheme for communicating among groups that use different type hierarchies , 1990, TOIS.

[15]  Dennis McLeod,et al.  A federated architecture for information management , 1985, TOIS.

[16]  M H. Law,et al.  Guide to Information Resource Dictionary Applications: General Concepts and Strategic`Systems Planning , 1988 .

[17]  Dennis McLeod,et al.  A Learning-Based Approach to Meta-data Evolution in an Object-Oriented Database , 1988, OODBS.

[18]  R. MacGregor,et al.  Mermaid—A front-end to distributed heterogeneous databases , 1987, Proceedings of the IEEE.

[19]  Michael Siegel,et al.  Automatic Rule Derivation For Semantic Query Optimization , 1989, Expert Database Conf..

[20]  Stuart E. Madnick,et al.  Schema integration using metadata , 1989 .

[21]  Jl McCarthy Information Systems Design for Material Properties Data , 1989 .

[22]  Alan Goldfine,et al.  A Technical Overview of the Information Resource Dictionary System (Second Edition) , 1988 .

[23]  Terry A. Landers,et al.  An Overview of MULTIBASE , 1986, DDB.

[24]  Stuart E. Madnick,et al.  The Composite Information System Laboratory (CISL) Project at MIT , 1990, IEEE Data Eng. Bull..