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Dissertation
Semi-automatic conceptual data modeling using entity and relationship instance repositories
Doctor of Philosophy (Ph.D.), Drexel University
May 2011
DOI:
https://doi.org/10.17918/etd-3537
Abstract
Conceptual modeling is the foundation of analysis and design methodologies for the development of information systems. It is challenging because it requires a clear understanding of an application domain and an ability to translate the requirement specifications into a data model. However, novice designers frequently lack experience and have incomplete knowledge about the application being designed. We propose new types of reusable artifacts called Entity Instance Repository (EIR) and Relationship Instance Repository (RIR), which contain ER (Entity-Relationship) modeling patterns from prior designs and serve as knowledge-based repositories for conceptual modeling. We also select six data modeling rules to check whether they are comprehensive enough in creating quality conceptual models. This research aims to develop effective knowledge-based systems (KBSs) with EIR and RIR. Our proposed artifacts are likely to be useful for conceptual designs in the following aspects: (1) they contain knowledge about a domain; (2) automatic generation of EIR and RIR overcomes a major problem ofinefficient manual approaches that depend on experienced modeling designers and domain experts; and (3) they are domain-specific and therefore easier to understand and reuse. Two KBSs were developed in this study: Heuristic-Based Technique (HBT) and Entity Instance Pattern WordNet (EIPW). The goals of this study are (1) to find effective approaches that can improve the novice designers' performance in developing conceptual models by integrating pattern-based technique and various modeling techniques, (2) to evaluate whether those selected six modeling rules are effective in HBT, and (3) to validate whether the proposed KBSs are effective in creating quality conceptual models. To assess the potential of the KBSs to benefit practice, empirical testing was conductedon tasks of different sizes. The empirical results indicate that novice designers' overall performance increased by 30.9~46.0 % when using EIPW, and increased by 33.5~34.9% when using HBT, compared with the cases of no tools.
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Details
- Title
- Semi-automatic conceptual data modeling using entity and relationship instance repositories
- Creators
- Ornsiri Thonggoom - DU
- Contributors
- Il-Yeol Song (Advisor) - Drexel University (1970-)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- College of Information Science and Technology (1995-2013); Drexel University
- Other Identifier
- 3537; 991014632390404721