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Journal of Systems and Software
Volume 28, Issue 2, February 1995, Pages 97-116
 
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doi:10.1016/0164-1212(94)00048-R    How to Cite or Link Using DOI (Opens New Window)
Copyright © 1995 Published by Elsevier Science Inc.

Group data base design: Addressing the view modeling problem

Stephen Hayne and Sudha RamCorresponding Author Contact Information

Faculty of Business, MIS, University of Calgary, Calgary, Alberta, Canada Department of MIS, College of BPA, University of Arizona, Tucson, Arizona, USA

Available online 4 February 2000.

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Abstract

Today's organizations increasingly depend on the use of data base technology to manage their operations. Advances in technology have resulted in increasing the number and complexity of these data bases. Despite their growing complexity, all data bases have one thing in common: each must have gone through either a formal or an informal design process. Data bases must mirror reality accurately, and thus the design process must better capture that reality. The heart of the design process is the conceptual design, data model mapping, and physical design. Our research focuses on providing automated support for the first of these, e.g., conceptual design. Conceptual design is known to be a very difficult and time-consuming phase in the development of data base applications. This article describes the architecture, implementation, and use of a distributed graphical group data base design system. The group view modeling system (GVMS) is implemented in Microsoft Windows for networked personal computers. The main purpose of GVMS is to allow multiple designers (or users) to share conceptual design information in real time and resolve design conflicts through the electronic medium. The underlying data model, semantic data model, is extended to include distribution information as well as transactions and is represented as an extended entity relationship model. Diagram management techniques are implemented to aid in simplifying large complex designs. A small study demonstrated that groups of data base designers who define their view collectively outperform individuals.

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