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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Technique and Cue Selection for Graphical Presentation of Generic Hyperdimensional Data

Howard, Lee Mont 22 June 2012 (has links) (PDF)
The process of visualizing n-D data presents the user with four problems: finding a hyperdimensional graphics package capable of rendering n-D data, finding a suitable presentation technique supported by the package that allows insight to be gained, using the provided user interface to interact with the presentation technique to explore the information in the data, and finding a way to share the information gained with others. Many graphics packages have been written to solve the first problem. However, existing packages do not sufficiently solve the other three problems. A hyperdimensional graphics package that sufficiently solves all these problems simplifies the user experience and allows the user to explore, interact with, and share the data. I have implemented a package that solves all four problems. The package is able to render n-D data through appropriate encapsulation of presentation techniques and their associated visual cues. Through the use of an extensible plugin system, presentation techniques can be easily added and accommodated. Desirable features are supported by the user interface to allow the user to interact easily with the data. Sharing of visualizations and annotations are included to allow users to share information with one another. By providing a hyperdimensional graphics package that easily accommodates presentation techniques and includes desirable features, including those that are rarely or never supported, the user benefits from tools that allow improved interaction with multivariate data to extract information and share it with others.

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