Journal article
An analysis of structural validity in entity-relationship modeling
Data & knowledge engineering, v 47(2), pp 167-205
2003
Abstract
We explore the criteria that contribute to the structural validity of modeling structures within the entity-relationship (ER) diagram. Our approach examines cardinality constraints in conjunction with the degree of the relationship to address constraint consistency, state compliance, and role uniqueness issues to derive a complete and comprehensive set of decision rules. Unlike typical other analyses that use only maximum cardinality constraints, we have used both maximum and minimum cardinality constraints in defining the properties and their structural validity criteria yielding a complete analysis of the structural validity of recursive, binary, and ternary relationship types. Our study evaluates these relationships as part of the overall diagram and our rules address these relationships as they coexist in a path structure within the model. The contribution of this paper is to provide a comprehensive set of decision rules to determine the structural validity of any ERD containing recursive, binary, and ternary relationships. These decision rules can be readily applied to real world data models regardless of their complexity. The rules can easily be incorporated into the database modeling and designing process, or extended into case tool implementations.
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Details
- Title
- An analysis of structural validity in entity-relationship modeling
- Creators
- James Dullea - Boeing Phantom WorksIl-Yeol Song - Drexel Univ College of Information Science and Technology, Philadelphia, PAIoanna Lamprou - Drexel Univ College of Information Science and Technology, Philadelphia, PA
- Publication Details
- Data & knowledge engineering, v 47(2), pp 167-205
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000185808100002
- Scopus ID
- 2-s2.0-0141792842
- Other Identifier
- 991019183955204721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Industry collaboration
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems