Introduction to Information Visualization

Description

Contents 1. Introduction to Visual Representations 1.1 Presentation 1.2 Explorative Analysis 1.3 Confirmative Analysis 1.4 Information Visualization 1.5 From Data to Wisdom 1.6 Mental Models 1.7 Scientific Visualization 1.8 Criteria for Good Visual Representations 1.8.1 Graphical Excellence 1.8.2 Graphical Integrity 1.8.3 Maximize the Data–Ink Ratio 1.8.4 Aesthetics 1.9 Conclusion 2. Creating Visual Representations 2.1 A Reference Model 2.1.1 Preprocessing and Data Transformations 2.1.2 Visual Mapping 2.1.3 Views 2.2 Designing a Visual Application 2.3 Visual Representation of Linear Data 2.4 2D vs. 3D 2.5 Conclusion 3. Perception 3.1 Memory 3.2 Preattentive Properties 3.2.1 Color 3.2.2 Form 3.2.3 Spatial Position 3.2.4 Movement 3.3 Mapping Data to Preattentive Attributes 3.4 Postattentive Processing 3.5 Gestalt Principles 3.5.1 Figure and Ground 3.5.2 Proximity 3.5.3 Similarity 3.5.4 Closure 3.5.5 Continuity 3.5.6 Other Principles 3.6 Conclusion 4. Multivariate Analysis 4.1 The Problem of Multivariate Visualization 4.2 Geometric Techniques 4.2.1 Parallel Coordinates 4.2.2 Scatterplot Matrix 4.2.3 TableLens 4.2.4 Parallel Sets 4.3 Icon Techniques 4.3.1 Star Plots 4.3.2 Chernoff Faces 4.4 Pixel-Oriented Techniques 4.5 Conclusion 5. Networks and Hierarchies 5.1 Network Data 5.1.1 Concept Maps and Mind Maps 5.1.2 Complex Network Data 5.1.3 Geographic Representations 5.1.4 Transport Networks 5.1.5 3D Graphs 5.2 Hierarchical Data 5.2.1 File System 5.2.2 Representing Evolutionary Data with Trees 5.2.3 Cone Tree 5.2.4 Botanical Tree 5.2.5 Treemap 5.3 Conclusion 6. World Wide Web 6.1 Website Maps 6.2 Website Log Data 6.3 Visual Representation of Search Engine Results 6.3.1 Clustering 6.4 Analysis of Interactions in Blogs 6.5 Conclusion 7. Interactions 7.1 The Problem of Information Overload 7.2 Types of Interactive Visual Representations 7.3 Manipulable Representations 7.3.1 Scrolling 7.3.2 Overview + Details 7.3.3 Focus + Context 7.4 Transformable Representations 7.4.1 Filtering Input Data 7.4.2 Data Reordering 7.4.3 Dynamic Queries 7.4.4 Magic Lens 7.4.5 Attribute Explorer 7.5 Conclusion 8. Evaluations 8.1 Human–Computer Interaction 8.2 Evaluation Criteria 8.3 Evaluating Visual Representations 8.3.1 Analytic Methods 8.3.2 Empirical Methods 8.4 Conclusion References Index A B C D E F G H I K L M N O P Q R S T U V W X Z