Trends in Interactive Visualization: State-of-the-Art Survey

397 Pages·2009·9.128 MB·English

by  Elena Zudilova-Seinstra, Tony Adriaansen, Robert van Liere (auth.), Robert Liere, Tony Adriaansen, Elena Zudilova-Seinstra (eds.)

Advanced Information and Knowledge Processing
Series Editors
Professor Lakhmi C. Jain
[email protected]
Professor Xindong Wu
[email protected]
For other titles published in this series, go to
http://www.springer.com/series/4738
Elena Zudilova-Seinstra • Tony Adriaansen
Robert van Liere
Editors
Trends in Interactive
Visualization
State-of-the-Art Survey
Editors
Elena Zudilova-Seinstra, PhD Tony Adriaansen, BA
University of Amsterdam ICT Centre
The Netherlands Commonwealth Scientific and Discovery
Research Organisation (CSIRO)
Australia
Robert van Liere, PhD
Center for Mathematics and Computer Science (CWI)
The Netherlands
AI&KP ISSN 1610-3947
ISBN: 978-1-84800-268-5 e-ISBN: 978-1-84800-269-2
DOI: 10.1007/978-1-84800-269-2
British Library Cataloguing in Publication Data
Library of Congress Control Number: 2008935082
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Preface

Massive increases in data sizes and ongoing improvements in computational per-
formance have created an urgent need for new systems that enable users to explore
complex datasets and computations in an intuitive and flexible manner.
The field of Interactive Visualization studies how people interact with computers
to create visual representation of information and how this process can be made
more efficient. With this book, we have tried to compile a comprehensive overview
of this young research field.
The book is a state-of-the-art survey of studies on Interactive Visualization. It
examines research topics advancing the field, presents insightful findings and novel
ideas, and describes applications across multiple disciplines. The book is intended
for a broad audience and collects multidisciplinary articles that give readers insight
into Interactive Visualization from various perspectives.
For instance, visualization experts can consult this book to find advanced methods
for solving particular problems. Interaction designers will become familiar with the
latest interaction techniques and input devices to perform visual exploration tasks.
Scientists and engineers will realize new ways to examine complex datasets.
Usability experts will be exposed to new and effective evaluation methodologies.
Furthermore, the book is appropriate for both undergraduate and graduate
masters students and can be easily transformed into a handbook or a supplementary
textbook for teaching courses such as scientific and information visualization, human–
computer interaction, computer graphics, and interaction/interface design. To reflect
a potential teaching taxonomy, we have organized the book into five parts.
I Introduction
Part I presents fundamentals of Interactive Visualization, surveys research in the
field, examines existing challenges, and provides information about popular inter-
active frameworks for scientific and information visualizations.
v
vi Preface
II Challenges in Data Mapping
Part II deals with one of the most challenging tasks in Interactive Visualization,
mapping and teasing out information from large complex datasets and generating
visual representations. This section consists of four chapters.
Binh Pham, Alex Streit, and Ross Brown provide a comprehensive requirement
analysis of information uncertainty visualizations. They examine the sources of
uncertainty, review aspects of its complexity, introduce typical models of uncertainty,
and analyze major issues in visualization of uncertainty, from various user and task
perspectives.
Alfred Inselberg examines challenges in the multivariate data analysis. He explains
how relations among multiple variables can be mapped uniquely into α-space
subsets having geometrical properties and introduces Parallel Coordinates method-
ology for the unambiguous visualization and exploration of a multidimensional
geometry and multivariate relations.
Christiaan Gribble describes two alternative approaches to interactive particle
visualization: one targeting desktop systems equipped with programmable graphics
hardware and the other targeting moderately sized multicore systems using packet-
based ray tracing.
Finally, Christof Rezk Salama reviews state-of-the-art strategies for the assignment
of visual parameters in scientific visualization systems. He explains the process of
mapping abstract data values into visual based on transfer functions, clarifies the
terms of pre- and postclassification, and introduces the state-of-the-art user inter-
faces for the design of transfer functions.
III Design and Evaluation
People’s abilities and disabilities both tend to be underestimated in current visuali-
zation systems. Meanwhile, interactive visualisation systems should be easy to use
and should not require sophisticated computer skills by users, as many are not
computer experts. Part III addresses this research concern from two complementary
perspectives: user-oriented and technology oriented. It includes three chapters.
To open this section, Roy Kalawsky explains why human perceptual and cog-
nitive capabilities have to be taken into account when designing visualization
techniques and tools. An example is discussed where the difficult technical chal-
lenges of creating an interactive three-dimensional visualization system on a
PDA device have been overcome by applying knowledge of human perception
and cognition.
Next, Martin Hicks reviews existing theories and principles for design of effec-
tive interactive visualization user interfaces, including Gestalt laws, data graphics,
interaction design, and Human–Computer Interaction guidelines. To illustrate the
principal benefits of applying these design principles, he discusses several case
studies.
Preface vii
Then, Ingo Wassink et al. present a user-centred approach to the design of
interactive visualization systems. They explain the importance of context-of-use in
visualization design, evaluate different methodologies and techniques for user and
task analysis, and discuss practical challenges in design and evaluation of collabo-
rative visualization environments.
In the last chapter of this section, Ross Brown, Simon Joslin, and Penny Drennan
describe the development life cycle of a collaborative virtual environment and
introduce the automatic visualization framework to assist in evaluation and analysis
of the usage data. To illustrate the framework benefits to the development team, a
case study is presented and discussed in detail.
IV Novel User Interfaces
Effective user interfaces is one of the top research and development problems of
Interactive Visualization. Part IV of the book is devoted to natural user interaction
with the visualized data. This section contains three chapters.
Joseph LaViola Jr. et al. describe virtual environments for interactive visualiza-
tion and data analysis for such domains as archaeology, biology, computational
fluid dynamics, and geoscience. Results of experimental studies are presented that
discuss benefits of Immersive Virtual Reality-based visualizations for end users.
Francis Marchese provides a comprehensive overview of novel interaction and
visualization techniques applied to interactive exploration of molecular structures.
He describes haptic displays and material molecular models along with mobile,
multimodal, and collaborative visualization systems.
Finally, Jeffrey Heer et al. discuss systems that support collaborative visualiza-
tion on the Web. They describe collaboration mechanisms for viewing, sharing,
annotation, discussion, and publishing visualizations and review existing Web-based
collaborative visualization systems.
V Integrating Visualization and Modeling
Part V of the book combines four chapters describing innovative visualization and
data mining techniques, tools and systems capable of solving computational and
imaging problems in various domains.
Judith Terrill et al. discuss how traditional data analysis and data mining tools
can be enriched with multiple representations and interactions. They present a
visual exploration environment that allows domain scientists to interactively meas-
ure and analyze experimental data. To demonstrate the use of quantitative visualiza-
tions, the description of three case studies is provided.
Yang Cai et al. present a new shape-based spatiotemporal reasoning method
that combines computer vision, multiphysics simulation, and user interaction.
viii Preface
They describe case studies of tracking and predicting behavior of oceanographic
phenomena and discuss results obtained from testing their algorithms using 2,384
satellite images.
Jean-Bernard Martens discusses how statistical models can be used for interac-
tive analysis of experimental data. He introduces a special class of geometrical
models that can be used to capture various data analysis scenarios and describes
the interactive visualization program XGms that implements these models.
In the last chapter of this section, Kamran Sedig provides an overview of formal
frameworks and tools for interactive mathematical visualizations. He explains
what mathematical visualizations are and discusses general benefits of making
them interactive.
Acknowledgments
To conclude the preface, we acknowledge the many people who made this book
possible.
It has been a pleasure to work with the chapter authors, and we therefore thank
all contributors. Without their support and commitment, it would have been impos-
sible to bring this book to publication.
Also, we thank members of the International Review Board who participated in
the refereeing process. We are grateful to: Charl Botha (Delft University of
Technology, the Netherlands), Sabine Coquillart (National Institute of Research in
Computer Science, France), Ellen Yi-Luen Do (Georgia Tech University, USA),
Noureddine Elouazizi (University of Leiden, the Netherlands), Pilar Herrero
(Universidad Politecnica de Madrid, Spain), Suguru Ishizaki (Carnegie Mellon
University, USA), Roy Kalawsky (Loughborough University, UK), Gordon
Kindlmann (Harvard Medical School, USA), Judith Klein-Seetharaman (Carnegie
Mellon University, USA), Ulrich Lang (University of Stuttgart, Germany), David
McGee (Adapx, USA), Frits Post (Delft University of Technology, the Netherlands),
Bernhard Preim (University of Magdeburg, Germany), Jos Roerdink (University
of Groningen, the Netherlands), Corina Sas (Lancaster University, UK), Margaret-
Anne Storey (University of Victoria, Canada), Anna Vilanova Bartoli (Eindhoven
University of Technology, the Netherlands), Frederic Vexo (Ecole Polytechnique
Federale de Lausanne, Switzerland), Antony Unwin (Augsburg University,
Germany), and Daniel Weiskopf (Simon Fraser University, Canada).
Finally, our special thanks go to Beverley Ford, Catherine Brett, and Helen
Desmond from Springer, UK, for their assistance during the preparation of this
book.
ix
Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv
Part I Introduction
1 Overview of Interactive Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Elena Zudilova-Seinstra, Tony Adriaansen,
and Robert van Liere
Part II Challenges in Data Mapping
2 Visualization of Information Uncertainty:
Progress and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Binh Pham, Alex Streit, and Ross Brown
3 Parallel Coordinates: Interactive Visualization
for High Dimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Alfred Inselberg
4 Interactive Particle Visualization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Christiaan P. Gribble
5 Visual Parameters and Transfer Functions. . . . . . . . . . . . . . . . . . . . . . 99
Christof Rezk Salama
Part III Design and Evaluation
6 Gaining Greater Insight Through Interactive
Visualization: A Human Factors Perspective . . . . . . . . . . . . . . . . . . . . 119
Roy S. Kalawsky
xi