An important contributor to the success of any complex database development is the comprehensive and accurate capture and recording of the users’ information requirements. Indeed, both the technical and economic success of the system under development is likely to rest largely on the quality of the data structure design and the information requirement analysis on which it is based. The data models, which represent the results of the analysis and design activities necessary to achieve this quality outcome, are therefore critical components of the database development process. Nevertheless, research suggests that this modeling is not always done well and in some cases is not done at all (e.g., Hitchman, 1995). However, implicit in the creation of a database is the design of a data model, and thus the only optional feature is the level of formality that has been followed in its development (Simsion, 1994). Since the publication of Chen’s (1976) original description of an Entity-relationship (E-R) model, a significant amount of academic research into data modeling has concentrated on providing ever richer, more complex and more formal models with which to better represent reality (Hirschheim, Klein & Lyytinen, 1995). In addition, researchers and practitioners have also recognized the importance of data models as a means of communication. However, little attention has been given to examining the appropriateness of various modeling techniques to the very different requirements of the analysis and design activities that they support, although matching tools to activities would seem to be an essential prerequisite for success. The INTECoM framework, described in this chapter, was developed to emphasize and better serve the differing nature of these activities, and also to improve access for all users to both the process and the outcome of data modeling. The framework was initially instantiated with two widely used data modeling techniques, the NIAM-CSDP (Natural Language Information Analysis-Conceptual Schema Design Procedure) and the Entity-Relationship (E-R) approach. This instantiation was chosen primarily because the two techniques represent significantly different ways of working (Bronts, Brouwer, Martens & Proper, 1995) towards the construction of a relational database. This is not to suggest that other instantiations are not possible or desirable, particularly where the target DBMS is of a different paradigm.
Complete Chapter List
John A. Hoxmeier
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M. Mehdi Owrang O.
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Laura C. Rivero, Jorge H. Doorn, Viviana E. Ferraggine
Cheryl L. Dunn, Severin V. Grabiski
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