Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2008. / Includes bibliographical references (leaves 68-72). Also available in electronic version.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2009. / Includes bibliographical references (p. 49-53).

Thesis (M.S.)--Rowan University, 2009. / Typescript. Includes bibliographical references.

Thesis (M.S.)--Oregon State University, 2007. / Printout. Includes bibliographical references (leaves 70-74). Also available on the World Wide Web.

Data storage is an important practice for organisations that want to track their progress. The evolution of data storage technologies from manual methods of storing data on paper or in spreadsheets, to the automated methods of using computers to automatically log data into databases or text files has brought an amount of data that is beyond the level of human interpretation and comprehension. One way of addressing this issue of interpreting large amounts of data is data visualisation, which aims to convert abstract data into images that are easy to interpret. However, people often have difficulty in selecting an appropriate visualisation tool and visualisation techniques that can effectively visualise their data. This research proposes the processes that can be followed to effectively visualise data. Data logged from a mobile learning system is visualised as a proof of concept to show how the proposed processes can be followed during data visualisation. These processes are summarised into a model that consists of three main components: the data, the visualisation techniques and the visualisation tool. There are two main contributions in this research: the model to visualise mobile learning usage data and the visualisation of the usage data logged from a mobile learning system. The mobile learning system usage data was visualised to demonstrate how students used the mobile learning system. Visualisation of the usage data helped to convert the data into images (charts and graphs) that were easy to interpret. The evaluation results indicated that the proposed process and resulting visualisation techniques and tool assisted users in effectively and efficiently interpreting large volumes of mobile learning system usage data.

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Neuromuscular diseases are difficult to diagnose, requiring specialized equipment and training. A decision support system facilitates this by visualizing the data produced by a classification system, allowing users to make a diagnosis. This thesis explores the development of a specific component of the decision support system; a comparison tool which allows the user to explore the visualization by making comparisons between assertions derived from the underlying classification system. After studying the impact of the comparison tool upon the performance of volunteer users, we provide recommendations on the utility of a particular decision exploration strategy and give guidance for the correct course for the future development of this system. This document illustrates some of the unique challenges associated with the evaluation of a decision support system which relies not only upon the computational power of the computer, but also upon a human’s innate ability to solve problems.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords:data visualization, email, visualization, history flow. Includes bibliographical references (leaves 60-61).

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaf 76).

Thesis (Ph.D.)--University of Waikato, 2006. / Includes bibliographical references (leaves 257-278)