Kerren, A., Ebert, A. and Meyer J. (Eds.): Human-centered Visualization Environments, volume 4417 of LNCS Tutorial, Springer, 2007

[Springer, 2007]

Type: Softcover
Editors: Andreas Kerren, Achim Ebert, and Jörg Meyer
Pages: 403
Publisher: Springer
Publication Date: July 2007
Series: Volume 4417 of LNCS Tutorial

This tutorial book features an augmented selection of the material presented at the GI-Dagstuhl Research Seminar on Human-Centered Visualization Environments, HCVE 2006, held in Dagstuhl Castle, Germany in March 2006. It presents eight tutorial lectures that are the thoroughly cross-reviewed and revised versions of the summaries and findings presented and discussed at the seminar. After an introduction to human-centered visualization environments, the book shows the fundamental principles and methods in that area, such as human-centered aspects, interacting with visualizations, visual representations, as well as challenges and unsolved problems. The book also includes lectures on domain-specific visualization describing geographic visualization, algorithm animation, and biomedical information visualization. [Springer, 2007]

ISBN 978-3-540-71948-9

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Table of Contents

• Preface
• List of Contributors
• 1 Introduction to Human-Centered Visualization Environments (A. Kerren, A. Ebert, and J. Meyer)
• 2 Human-Centered Aspects (O. Kulyk, R. Kosara, J. Urquiza, and I. Wassink)
  • 2.1 Human-Centered Approach
  • 2.2 Usability in Human-Centered Design
    • 2.2.1 Defining Usability
    • 2.2.2 Evaluating Usability
    • 2.2.3 Improving Usability
    • 2.2.4 Usability and Information Overload
  • 2.3 User Aims and Requirements
    • 2.3.1 Characteristics of Good Visualizations and User Interfaces
    • 2.3.2 Essential Elements of Successful Visualization
    • 2.3.3 Dimensions in Visualization
    • 2.3.4 Steps in Visualization Design
    • 2.3.5 The Design Cycle
    • 2.3.6 User Analysis
    • 2.3.7 User Requirements
    • 2.3.8 Task Analysis
    • 2.3.9 Task Modeling
    • 2.3.10 Designing for and with Users
  • 2.4 Evaluation of Visualization Environments
    • 2.4.1 Human-Centered Evaluation in Visualization Practice
    • 2.4.2 Evaluation Methods
    • 2.4.3 Designing Experiments
    • 2.4.4 Challenges in Evaluation of Collaborative Visualization Environments
  • 2.5 User Studies and a Science of Visualization
    • 2.5.1 Survey of Information Visualization Studies
    • 2.5.2 The Future of User Studies
  • 2.6 Chapter Notes
• 3 Interacting with Visualizations (W. Fikkert, M. D’Ambros, T. Bierz, and T.J. Jankun-Kelly)
  • 3.1 Interaction
    • 3.1.1 Describing Interaction
    • 3.1.2 Defining Interaction
  • 3.2 Influences of Display Technologies
    • 3.2.1 Survey of Display Technologies
    • 3.2.2 Scales of Interaction
    • 3.2.3 Display Interaction Modalities and Media
    • 3.2.4 Interfaces and Usability for Novel Displays
    • 3.2.5 Display Device Challenges in Visualization
  • 3.3 Multimodal Interaction
    • 3.3.1 Unimodality Versus Multimodality
    • 3.3.2 Issues to Deal with in Multimodal Interaction
    • 3.3.3 Myths of Multimodality
    • 3.3.4 Survey of Enabling Technologies
    • 3.3.5 Overview of Approaches to Multimodal Interaction
    • 3.3.6 Enabling Multimodal Interaction
  • 3.4 Visualizations in Multi-party Environments
    • 3.4.1 Collaborating with Visualizations
    • 3.4.2 Models for Distributed Collaborative Visualization
    • 3.4.3 Evaluation Criteria
    • 3.4.4 Survey of Collaborative Visualization Systems
    • 3.4.5 Challenges for Multi-party Visualizations
  • 3.5 Chapter Notes
• 4 Visual Representations (C. Görg, M. Pohl, E. Qeli, and K. Xu)
  • 4.1 Perceptual and Cognitive Issues
    • 4.1.1 The Visualization Process
    • 4.1.2 Types of Data
    • 4.1.3 Preattentive Processing
  • 4.2 Information Visualization Criteria and Metaphors
    • 4.2.1 Information Visualization Criteria
    • 4.2.2 Metaphors
  • 4.3 Multivariate Visualization Techniques
    • 4.3.1 Low-Dimensional Data Visualization
    • 4.3.2 Multidimensional Data Visualization
    • 4.3.3 Usability Issues on Multidimensional Data Visualization
  • 4.4 Graphs and Trees
    • 4.4.1 Applications
    • 4.4.2 Background
    • 4.4.3 Aesthetics vs. Graph Readability
    • 4.4.4 Layout vs. Graph Readability
    • 4.4.5 Large Graphs
    • 4.4.6 Integrated Graph Drawing
    • 4.4.7 Labeling of Graphs
  • 4.5 Multiple Views
    • 4.5.1 Classification
    • 4.5.2 The Design of Multiple Views
    • 4.5.3 Interaction
    • 4.5.4 Comparison with Integrated Views
  • 4.6 Chapter Notes
• 5 Challenges and Unsolved Problems (R.S. Laramee, R. Kosara)
  • 5.1 Classification of Future Challenges and Unsolved Problems in Human-Centered Visualization
    • 5.1.1 Human-Centered Challenges
    • 5.1.2 Technical Challenges
    • 5.1.3 Financial Challenges
  • 5.2 Chapter Notes
• 6 Geographic Visualization (M. Nöllenburg)
  • 6.1 Goals of Geovisualization
  • 6.2 Driving Forces of Geovisualization
  • 6.3 Cognitive Aspects
    • 6.3.1 Visual Thinking
    • 6.3.2 Graphic Variables
  • 6.4 Visualization Methods and Techniques
    • 6.4.1 Geospatial Data
    • 6.4.2 2D Cartographic Visualization
    • 6.4.3 3D Cartographic Visualization
    • 6.4.4 Visual Data Mining Tools
    • 6.4.5 Animation
    • 6.4.6 Spatio-Temporal Visualization
    • 6.4.7 Interactive User Interfaces
    • 6.4.8 Combining Visual and Computational Exploration
  • 6.5 Geovisualization Tools
  • 6.6 Usability of Geovisualization Systems
    • 6.6.1 Involving Users in the Design of Geovisualizations
    • 6.6.2 Results from User Studies
    • 6.6.3 Geovisualization to Support Group Work
  • 6.7 Chapter Notes
• 7 Algorithm Animation (A. Moreno)
  • 7.1 Overview
  • 7.2 Users of Algorithm Animation
  • 7.3 Taxonomies for Algorithm Animation Tools
  • 7.4 Review of Tools and Their Evaluations
    • 7.4.1 Concept Keyboards for Algorithm Visualization
    • 7.4.2 Matrix and MatrixPro
    • 7.4.3 Alvis and Alvis Live!
    • 7.4.4 Alice
    • 7.4.5 Jeliot 3/Jeliot 2000
    • 7.4.6 JHAVÉ
    • 7.4.7 WinHipe
    • 7.4.8 User Studies Compilation
  • 7.5 Chapter Notes
• 8 Biomedical Information Visualization (M. Lungu, K. Xu)
  • 8.1 Phylogenetic Tree Visualization
    • 8.1.1 Small Trees – Working in Euclidean Space
    • 8.1.2 Large Trees – Using Focus and Context
    • 8.1.3 Very Large Trees – Hyperbolic 3D Space
    • 8.1.4 Discussion and Further Reading
  • 8.2 Sequence Alignment
    • 8.2.1 Sequence Logos
    • 8.2.2 Editing and Visualizing Sequence Alignment: Jalview
    • 8.2.3 Vista: Online Visualization of DNA Alignment
    • 8.2.4 Sequence Walkers
    • 8.2.5 Dot Plots
    • 8.2.6 Arc Diagrams
    • 8.2.7 Discussion and Further Reading
  • 8.3 Biochemical Network Analysis
    • 8.3.1 Cytoscape
    • 8.3.2 Biochemical Pathway Analysis
    • 8.3.3 Layout for Large Biochemical Networks: LGL
    • 8.3.4 Discussion and Further Reading
  • 8.4 Microarray Data Visualization
    • 8.4.1 TreeView
    • 8.4.2 Hierarchical Clustering Explorer
    • 8.4.3 Evaluation of Microarray Visualization Tools
  • 8.5 Medical Records Visualization
    • 8.5.1 LifeLines: Visualizing Patient Temporal Data
    • 8.5.2 The Cube: Multidimensional Analysis of Medical Records
    • 8.5.3 Visualizing Medical Practice Guidelines and Protocols
  • 8.6 Chapter Notes
• Bibliography
• Author Index
• Index

References

[Springer, 2007] Book description page [1]