/dev/kev

PhD Thesis

Structural Focus + Context Navigation of Relational Data

Abstract
Traditional information visualisation is concerned with methods of drawing a complete picture of an entire dataset. By contrast, much of modern information visualisation deals with the problem of how to see datasets that are too large to be displayed in toto. This problem is known as large scale information visualisation. The most common approach is to display only part of the dataset, but allow the user to navigate easily to other parts of the dataset that are not shown. Focus + Context techniques address large scale information visualisation by presenting a small amount of "focus" data at a high level of detail, surrounded by the majority of the remaining data at a low level of detail, the "context". The majority of Focus + Context techniques to date have been based on geometric distortion, where the visualisation of the entire dataset is adjusted to show the focus region at normal magnification, whilst demagnifying the context region.

An alternative to geometric distortion is data-driven Focus + Context, where the concepts of "focus", "context", "zooming" and "navigation" are defined in terms of multi-detail datasets that store the data using multiple levels of detail. Data-driven methods require the development of new techniques for the presentation and animation of information. This thesis presents a new data-driven Focus + Context technique which we call Structural Zooming.

Structural Zooming is presented in a visualisation independant way that allows any illustration of any type of data to be adapted for use with Structural Zooming. Further, a method is given for performing Structural Zooming of relational data, namely trees and clustered graphs. This has the advantages of geometric zooming techniques (such as Graphical Fisheye Views and the Hyperbolic Browser), including high detail focus, low detail context, smoothly animated transitions during navigation and preservation of a high quality, aesthetically pleasing layout. In addition, it has advantages over geometric zooming, including an approximately constant level of visual complexity by presenting less data at lower detail in the context region, preservation of spatial properties and the ability to leverage existing information visualisation techniques.

We define empirical quality measures and present an experimental evaluation of Structural Zooming of relational data using these measures. This evaluation utilises a corpus of data files from three application domains, and navigation data derived both from real users and computational models of navigation, in order to validate the design choices made in the application of Structural Zooming to relational data.

Thesis Download
A large part of this thesis is concerned with animations, and as such, it makes use of "animated figures" to show illustrative animations that support the text. Since it is not possible to show motion on paper, these figures appear in the printed form of this thesis as a matrix of frames. Additionally, the electronic Portable Document Format (PDF) version embeds the animated figures using the animfig package. This allows interactive playback of the animations in PDF viewers that support Acrobat PDF Javascript, such as the freely available Adobe Acrobat Reader. These embedded animations are accessed by clicking on the static matrix of frames.

The electronic version of this thesis is available for download from the following links. The main thesis is contained in the file thesis.pdf. The animations are available in three formats, located in the anim subdirectory. More information on the animation files can be found in Appendix A of the thesis.

  1. PDF format. Each animation is in a separate PDF file, with additional buttons to control playback. These files must be found in the anim subdirectory (relative to thesis.pdf) for clicking of animated figures in thesis.pdf to work as expected.
  2. AVI video format. Each animation is in an AVI file, encoded using the XviD video codec, which can be played back with a suitable media program.
  3. Image frame format. Each animation is stored as a collection of individual PNG (Portable Network Graphics) format image files. This allows viewing of the individual frames in a standard image viewing program. In the event that neither the PDF nor AVI format animations can be displayed, these image files permit crude animation by having an image viewer display each of the frames in turn.

Compressed archives

These files are the recommended way to download the thesis for optimal viewing. They contain collections of files compressed using the zip file format.

Individual files

These are useful if you are interested in browsing or downloading individual files from the thesis.

Software Download
The Smooth Structural Zooming (SSZ) research software which was developed in the course of this thesis, is unfortunately not currently available for download.

I would like to release it in both executable and source forms (preferably under the GNU GPL license), however it has been built using the Tom Sawyer Visualisation (TSV) software package. This library is the commercial and proprietary property of Tom Sawyer Software, and as such is not freely available. Thus, releasing my software for general use, but without free access to the TSV library on which it depends, is not expected to be particularly useful.

It is my hope that at some point in the future, I will reimplement those parts of TSV that SSZ requires in a library which will be freely available and source-code compatible with TSV (although perhaps not as efficient).



Last updated: Monday, 05 June, 2006.
Copyright © 1994-2012, Kevin Pulo, kev at pulo dot com dot au
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