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.

Indiana University-Purdue University Indianapolis (IUPUI) / For individuals in the tourism industry and other businesses, the department of tourism in the government, or the individuals who are planning a travel, the data of tourist population movement can be a valuable resource that can uncover insights that could bring more profit and more tourists, or make the trip more enjoyable. As visualization is an effective way of conveying information with multiple dimensions, we would like to visualize the geo-temporal floating population data of tourists and residents in Jeju island in the Republic of Korea in two-dimensional space. In this study, we introduce the two methods we have implemented for visualizing the geo-temporal data using color curves as the representation of time dimension. We use the dots as the markers of floating population, and each color of dots represents the 24 hours of a day. In the first method, we plot the colored dots directly on the map, thereby coloring the area the data represents. In the second method, we plot the same dots inside a semi-transparent circle divided into arcs that represent each month of a year. The user can compare the population of tourists and residents between the different times of a day, the different months and the weather conditions to analyze the floating population in the given area.

The increasing number of web services published over the Web highlights the need for an effective method for users to find appropriate web services. Existing web service discovery methods do not effectively aid a user in finding suitable web services. The current methods provide textual lists of web services that the user is required to explore and manually evaluate. Thus, these methods lead to time-consuming and ineffective web service discovery. The aim of this research was to investigate using information visualization (IV) techniques to effectively support web service discovery. The node-and-link network IV technique was selected as the most appropriate IV technique to visualize web service collections. A prototype, called SerViz, was developed as a tool for interactive visualization of web service collections incorporating the node-and-link IV technique and an alphabetical list-based technique. SerViz used the Programmable Web web service collection as the sample web service collection. A usability evaluation was conducted to compare these techniques. Ninety percent of participants preferred the network IV technique for visualizing web service collections. The network IV technique was also faster for browsing. Several usability problems were identified with the network IV technique. This motivated a need for implementing an alternative IV technique in SerViz. The node-and-link tree IV technique was selected as it was more structured than the network IV technique. A usability evaluation was conducted to compare the network and tree IV techniques. Participants slightly preferred the tree IV technique as the technique to visualize web service collections. The tree IV technique was faster for browsing the web service collection while the network IV technique was faster for searching and filtering. This research has determined that IV techniques can be used to effectively support web service discovery. Future work will involve using IV techniques to support collaborative web service discovery. Keywords: Web Service Discovery, Information Visualization, Web Service Collections, Information Visualization Techniques.

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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).