Über den Autor
Matthew O. Ward is professor of Computer Science at Worcester Polytechnic Institute (WPI) in Worcester, MA. He has been an associate editor for IEEE Transactions on Visualization and Computer Graphics since 2006. Georges Grinstein is professor of Computer Science at the University of Massachusetts Lowell. He is the head of the Bioinformatics Program and codirector of the Institute for Visualization and Perception Research and the Center for Biomolecular and Medical Informatics. Daniel Keim is full professor and head of the Information and Visualization and Data Analysis Research Group at the University of Konstanz, Germany. He has been an associate editor of Information Visualization since 2001 and knowledge and Information Systems since 2006.
Introduction What Is Visualization? History of Visualization Relationship between Visualization and Other Fields The Visualization Process Pseudocode Conventions The Scatterplot The Role of the User Related Readings Exercises Projects Data Foundations Types of Data Structure within and between Records Data Preprocessing Data Sets Used in This Book Related Readings Exercises Projects Human Perception and Information Processing What Is Perception? Physiology Perceptual Processing Perception in Visualization Metrics Related Readings Exercises Projects Visualization Foundations The Visualization Process in Detail Semiology of Graphical Symbols The Eight Visual Variables Historical Perspective Taxonomies Related Readings Exercises Projects Visualization Techniques for Spatial Data One-Dimensional Data Two-Dimensional Data Three-Dimensional Data Dynamic Data Combining Techniques Summary Related Readings Exercises Projects Visualization Techniques for Geospatial Data Visualizing Spatial Data Visualization of Point Data Visualization of Line Data Visualization of Area Data Other Issues in Geospatial Data Visualization Related Readings Exercises Projects Visualization Techniques for Multivariate Data Point-Based Techniques Line-Based Techniques Region-Based Techniques Combinations of Techniques Related Readings Exercises Projects Visualization Techniques for Trees, Graphs, and Networks Displaying Hierarchical Structures Displaying Arbitrary Graphs/Networks Other Issues Related Readings Exercises Projects Text and Document Visualization Introduction Levels of Text Representations The Vector Space Model Single Document Visualizations Document Collection Visualizations Extended Text Visualizations Summary Related Readings Exercises Projects Interaction Concepts Interaction Operators Interaction Operands and Spaces A Unified Framework Summary Related Readings Exercises Projects Interaction Techniques Screen Space Object Space (D Surfaces) Data Space (Multivariate Data Values) Attribute Space (Properties of Graphical Entities) Data Structure Space (Components of Data Organization) Visualization Structure Space (Components of the Data Visualization) Animating Transformations Interaction Control Related Readings Exercises Projects Designing Effective Visualizations Steps in Designing Visualizations Problems in Designing Effective Visualizations Summary Related Readings Exercises Projects Comparing and Evaluating Visualization Techniques User Tasks User Characteristics Data Characteristics Visualization Characteristics Structures for Evaluating Visualizations Benchmarking Procedures An Example of Visualization Benchmarking Related Readings Exercises Projects Visualization Systems Systems Based on Data Type Systems Based on Analysis Type Text Analysis and Visualization Modern Integrated Visualization Systems Toolkits Related Readings Exercises Projects Research Directions in Visualization Issues of Data
Visualization is the process of representing data, information, and knowledge in a visual form. This book covers the full spectrum of the field, including mathematical and analytic aspects, ranging from its foundations to human visual perception; from coded algorithms for different types of data, information and tasks to the design and evaluation of new visualization techniques. Sample programs are provided as starting points for the reader to build their own visualization tools. Numerous data sets highlight different application areas and allow readers to evaluate the strengths and weaknesses of different visualization methods. Exercises, programming projects, and related readings accompany each chapter. The book concludes with an examination of several existing visualization systems and projections on the future of the field.