In color throughout, this popular book provides all the theory, details, and tools necessary to build visualizations and systems involving the visualization of data. It explains basic terminology and concepts, algorithmic and software engineering issues, and commonly used techniques and high-level algorithms. Full source code is provided for completing implementations. This edition includes new related readings, exercises, and programming projects; better quality figures and numerous new figures; and a new chapter on techniques for time-oriented data.
In color throughout, this popular book provides all the theory, details, and tools necessary to build visualizations and systems involving the visualization of data. It explains basic terminology and concepts, algorithmic and software engineering issues, and commonly used techniques and high-level algorithms. Full source code is provided for completing implementations. This edition includes new related readings, exercises, and programming projects; better quality figures and numerous new figures; and a new chapter on techniques for time-oriented data.
Matthew O. Ward was a professor in the Department of Computer Science at Worcester Polytechnic Institute. Dr. Ward's research focused on computer graphics, animation, image processing, computer vision, and data and information visualization. Georges Grinstein is a professor in the Department of Computer Science and director of both the Institute for Visualization and Perception Research and the Center for Biomolecular and Medical Informatics at the University of Massachusetts Lowell. Dr. Grinstein's research encompasses visual analytics, human computing, perceptual computing, information computing, and visualization systems engineering. Daniel Keim is a professor in the Department of Computer and Information Science and head of the Data Analysis and Visualization group at the University of Konstanz. Dr. Keim's research interests include databases, data mining, information visualization, and visual analytics.
Inhaltsangabe
Introduction. Data Foundations. Human Perception and Information Processing. Visualization Foundations. Visualization Techniques for Spatial Data. Visualization Techniques for Geospatial Data. Visualization Techniques for Time-Oriented Data. Visualization Techniques for Multivariate Data. Visualization Techniques for Trees, Graphs, and Networks. Text and Document Visualization. Interaction Concepts. Interaction Techniques. Designing Effective Visualizations. Comparing and Evaluating Visualization Techniques. Visualization Systems. Research Directions in Visualization. Appendices. Bibliography. Index.
Introduction. Data Foundations. Human Perception and Information Processing. Visualization Foundations. Visualization Techniques for Spatial Data. Visualization Techniques for Geospatial Data. Visualization Techniques for Time-Oriented Data. Visualization Techniques for Multivariate Data. Visualization Techniques for Trees, Graphs, and Networks. Text and Document Visualization. Interaction Concepts. Interaction Techniques. Designing Effective Visualizations. Comparing and Evaluating Visualization Techniques. Visualization Systems. Research Directions in Visualization. Appendices. Bibliography. Index.
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