|Structural Focus + Context Navigation of Relational Data|
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.
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
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.
- 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.
- 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.
- 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.
These files are the recommended way to download the thesis for optimal viewing.
They contain collections of files compressed using the zip file format.
These are useful if you are interested in browsing or downloading individual files from the thesis.
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
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).