A comparative analysis of methodologies for database schema integration
ACM Computing Surveys (CSUR)
Distributed Artificial Intelligence
Distributed Artificial Intelligence
A Theory of Attributed Equivalence in Databases with Application to Schema Integration
IEEE Transactions on Software Engineering
Communications of the ACM - Special issue on computer graphics: state of the arts
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ACM Transactions on Database Systems (TODS) - Special issue: papers from the international conference on very large data bases: September 22–24, 1975, Framingham, MA
System-Guided View Integration for Object-Oriented Databases
IEEE Transactions on Knowledge and Data Engineering
Multi-User View Integration System (MUVIS): An Expert System for View Integration
Proceedings of the Sixth International Conference on Data Engineering
A methodology for interschema relationship identification in heterogeneous databases
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
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ACM Transactions on Information Systems (TOIS)
Requirements interaction management
ACM Computing Surveys (CSUR)
A publish and subscribe collaboration architecture for web-based information
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
An ontology-based framework for semi-automatic schema integration
Journal of Computer Science and Technology
A co-operative methodology for automatic solutions to problems in indefinite integral calculus
AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
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We describe a four-level blackboard architecture that supports schema integration and provide a detailed description of the communication among human and computational agents that this system allows.Today's corporate information system environments are heterogeneous, consisting of multiple and independently managed databases. Many applications that assist decision making call for access to data from multiple heterogeneous databases. To facilitate this, there needs to be an integrated representation of the underlying databases that allows users to query multiple databases simultaneously. The process of deriving this integrated representation is called schema integration.Schema integration is time consuming and complex, as it requires a thorough understanding of the underlying database semantics. Since no data model can capture the entire real world semantics of each database's objects, this process requires human agent assistance. Although certain aspects of schema integration can be automated, interaction with designers and users is still necessary. In this article, we describe how blackboard architectures can facilitate the communication among human and computational agents for schema integration.