Today, in the world of information technology, conceptual model representation of database schemas is challenging for users both in the Software Development Life Cycle (SDLC) and the Human-Computer Interaction (HCI) domain. The primary way to resolve this issue, in both domains, is to use a model that is concise, interpretable and clear to understand, yet encompasses all of the required information to be able to clearly define the database. A temporal database is understood as a database capable of supporting reasoning of time-based data for e.g.: a temporal database can answer questions such as: - for what period was Mrs Jones single before she got married? On the other hand, an atemporal database stores data that is valid today and has no history. In the thesis, I looked at different theoretical temporal visual conceptual models proposed by temporal researchers and aimed, by means of a user-survey consisting of business users, to ascertain towards which models users a preference has. I further asked the users for firstly; whether they prefer textual or graphical representations for the entities, attributes and constraints represented by the visual models, or secondly; whether there is a preference for a specific graphical icon for the temporal entities and lastly; to ascertain if the users show a preference towards a specific theoretical temporal conceptual model. The methodology employed to reach my goal in this thesis, is one of experiments on business users with knowledge enhancements after each experiment. Users were to perform a task, and then based on analysis of the task results, they are taught additional temporal aspects so as improve their knowledge before the next experiment commences. The ultimate aim was to extract a visual conceptual model preference from business users with enhanced knowledge of temporal aspects. This is the first work done in this field and thus will aid researchers in future work, as they will have a temporal conceptual model that promotes effective communication, understandability and interpretability.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/20875 |
Date | January 2016 |
Creators | Shunmugam, Tamindran |
Contributors | Keet, Catharina, Kuttel, Michelle Mary |
Publisher | University of Cape Town, Faculty of Science, Department of Computer Science |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Master Thesis, Masters, MSc |
Format | application/pdf |
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