An Updated Guide to the Visualization of Data for Designers, Users, and Researchers
Interactive Data Visualization: Foundations, Techniques, and Applications, Second Edition provides all the theory, details, and tools necessary to build visualizations and systems involving the visualization of data. In color throughout, 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.
New to the Second Edition
- New related readings, exercises, and programming projects
- Better quality figures and numerous new figures
- New chapter on techniques for time-oriented data
This popular book continues to explore the fundamental components of the visualization process, from the data to the human viewer. For developers, the book offers guidance on designing effective visualizations using methods derived from human perception, graphical design, art, and usability analysis. For practitioners, it shows how various public and commercial visualization systems are used to solve specific problems in diverse domains. For researchers, the text describes emerging technology and hot topics in development at academic and industrial centers today.
Each chapter presents several types of exercises, including review questions and problems that motivate readers to build on the material covered and design alternate approaches to solving a problem. In addition, programming projects encourage readers to perform a range of tasks, from the simple implementation of algorithms to the extension of algorithms and programming techniques.
A supplementary website includes downloadable software tools and example data sets, enabling hands-on experience with the techniques covered in the text. The site also offers links to useful data repositories and data file formats, an up-to-date listing of software packages and vendors, and instructional tools, such as reading lists, lecture slides, and demonstration programs.
Table of Contents
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.
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.