eBook Handbook of Human Centric Visualization, 1st Edition

  • Published By:
  • ISBN-10: 146147485X
  • ISBN-13: 9781461474852
  • DDC: 001.4226
  • Grade Level Range: College Freshman - College Senior
  • 743 Pages | eBook
  • Original Copyright 2014 | Published/Released May 2014
  • This publication's content originally published in print form: 2014
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Visualizations are visual representations of non-visual data. They are produced for people to interact with and to make sense of the underlying data. Rapid advances in display technology and computer power have enabled researchers to produce visually appealing pictures. However, the effectiveness of those pictures in conveying the embedded information to end users has not been fully explored. Handbook of Human Centric Visualization addresses issues related to design, evaluation and application of visualizations. Topics include visualization theories, design principles, evaluation methods and metrics, human factors, interaction methods and case studies. This cutting-edge book includes contributions from well-established researchers worldwide, from diverse disciplines including psychology, visualization and human-computer interaction. This handbook is designed for a professional audience composed of practitioners, lecturers and researchers working in the field of computer graphics, visualization, human-computer interaction and psychology. Undergraduate and postgraduate students in science and engineering focused on this topic will also find this book useful as a comprehensive textbook or reference.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Editorial Board.
1: Visual Communication.
2: Visualizing Thought.
3: Gryphon: A ‘Little’ Domain-Specific Programming Language for Diffusion MRI Visualizations.
4: Viewing Abstract Data as Maps.
5: Theory and Science.
6: Individual Differences and Translational Science in the Design of Human-Centered Visualizations.
7: Evaluating Visualization Environments: Cognitive, Social, and Cultural Perspectives.
8: On the Prospects for a Science of Visualization.
9: Principles, Guidelines and Recommendations.
10: Toward a Better Understanding and Application of the Principles of Visual Communication.
11: Pep up Your Time Machine: Recommendations for the Design of Information Visualizations of Time-Dependent Data.
12: Using Textbook Illustrations to Extract Design Principles for Algorithm Visualizations.
13: Methods.
14: Conceptual Design for Sensemaking.
15: An Introduction and Guide to Evaluation of Visualization Techniques through User Studies.
16: User-Centered Evaluation of Information Visualization Techniques: Making the HCI-InfoVis Connection Explicit.
17: Eye Tracking on Visualizations: Progressive Extraction of Scanning Strategies.
18: Evaluating Overall Quality of Graph Visualizations Indirectly and Directly.
19: Visual Analysis of Eye Tracking Data.
20: User Studies in Visualization: A Reflection on Methods.
21: Perception and Cognition.
22: On the Benefits and Drawbacks of Radial Diagrams.
23: Measuring Memories for Objects and Their Locations in Immersive Virtual Environments: The Subjective Component of Memorial Experience.
24: Human-Centric Chronographics: Making Historical Time Memorable.
25: Visualizing Multiple Levels and Dimensions of Social Network Properties.
26: Dynamic Visualization.
27: Adaptive Diagrams: A Research Agenda to Explore How Learners Can Manipulate Online Diagrams to Self-Manage Cognitive Load.
28: Dynamic Visualisations and Motor Skills.
29: Dynamic Visualizations: A Two-Edged Sword?.
30: Simultaneous and Sequential Presentation of Realistic and Schematic Instructional Dynamic Visualizations.
31: How Do You Connect Moving Dots? Insights from User Studies on Dynamic Network Visualizations.
32: Interaction.
33: Interaction Taxonomy for Tracking of User Actions in Visual Analytics Applications.
34: Common Visualizations: Their Cognitive Utility.
35: Distribution of Information Processing while Performing Complex Cognitive Activities with Visualization Tools.
36: Human-Centered Interactivity of Visualization Tools: Micro and Macro-Level Considerations.