Requirements ontology and multi-representation strategy for database schema evolution

Authors:
Hassina Bounif;Stefano Spaccapietra;Rachel Pottinger
Affiliations:
Database Laboratory, EPFL, School of Computer and Communication Science, Lausanne, Switzerland;Database Laboratory, EPFL, School of Computer and Communication Science, Lausanne, Switzerland;Data Management and Mining Laboratory, University of British Columbia, Vancouver, Canada
Venue:
ODBIS'05/06 Proceedings of the First and Second VLDB conference on Ontologies-based databases and information systems
Year:
2005

Citing 8
Cited 0

Using persistence technology to control schema evolution

SAC '94 Proceedings of the 1994 ACM symposium on Applied computing
Ontologies for conceptual modeling: their creation, use, and management

Data & Knowledge Engineering
A Unified Framework for Supporting Dynamic Schema Evolution in Object Databases

ER '99 Proceedings of the 18th International Conference on Conceptual Modeling
An Ontology-Based Framework for Generating and Improving Database Design

NLDB '02 Proceedings of the 6th International Conference on Applications of Natural Language to Information Systems-Revised Papers
Basic description logics

The description logic handbook
Introduction to Data Mining, (First Edition)

Introduction to Data Mining, (First Edition)
Schema Repository for Database Schema Evolution

DEXA '06 Proceedings of the 17th International Conference on Database and Expert Systems Applications
Accommodating exceptions in databases, and refining the schema by learning from them

VLDB '85 Proceedings of the 11th international conference on Very Large Data Bases - Volume 11

Quantified Score

Hi-index	0.00

Visualization

Abstract

With the emergence of enterprise-wide information systems, ontologies have become by definition a valuable aid for efficient database schema modeling and integration, in addition to their use in other disciplines such as the semantic web and natural language processing. This paper presents another important utilization of ontologies in database schemas: schema evolution. Specifically, our research concentrates on a new three-layered approach for schema evolution. These three layers are 1) a schema repository, 2) a domain ontology called a requirements ontology, and 3) a multirepresentation strategy to enable powerful change management. This a priori approach for schema evolution, in contrast with existing a posteriori solutions, can be employed for any data model and for both 1) design from scratch and evolution and 2) redesign and evolution of the database. The paper focuses on the two main foundations of this approach, the requirements ontology and the multi-representation strategy which is based on a stamping mechanism.