Table of Contents I. Data Visualization I.1 Introduction II. Principles II.1 A Brief History of Data Visualization II.2 Good Graphics? 57-70 Scales, Sorting and Ordering, Plot data, Legends, Size and Aspect Ratio, Color 70-78 Scatterplot Matrices, Parallel Coordinates, Mosaic Plots, Trellis Displays, Time Series, Maps II.3 Static Graphics II.4 Data Visualization Through Their Graph Representations 103-114 Graph Layout (Force techniques and Multidimensional Scaling) II.5 Graph-theoretic Graphics 121-142 Trees, Directed Graphs, Treemaps II.6 High-dimensional Data Visualization 151-178 Mosaic Plots, Trellis Displays, Parallel Coordinate PLots, Grand Tour II.7 Multivariate Data Glyphs: Principles and Practice 179-198 Existing Glyphs, Ordering of Data Dimensions, Glyph Layout Options II.8 Linked Views for Visual Exploration 200-203 Linked Views II.9 Linked Data Views 235-240 Examples of Linked Views II.10 Visualizing Trees and Forests III. Methodologies III.1 Interactive Linked Micromap Plots for the Display of Geographically Referenced Statistical Data III.2 Grand Tours, Projection Pursuit Guided Tours, and Manual Controls III.3 Multidimensional Scaling 316-318 Proximity Data, Similarity Measures III.4 Huge Multidimensional Data Visualization: Back to the Virtue of Principal Coordinates and Dendrograms in the New Computer Age 350-387 Principal Component Analysis, Hierarchical Clustering, Partitioning clustering III.6 Structured Sets of Graphs III.9 Smoothing Techniques for Visualisation III.11 Visualizing Cluster Analysis and Finite Mixture Models 561-580 Dendrograms, Heatmaps, Cluster analysis, Neighborhood Graphs, Self-organizing maps III.13 Mosaic Plots and Their Variants III.14 Parallel Coordinates: Visualization, Exploration and Classification of High-Dimensional Data III.15 Matrix Visualization http://www.springer.com/978-3-540-33036-3