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Interactive Data Visualization: Foundations, Techniques, and Applications

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Overview

Visualization is the process of representing data, information, and knowledge in a visual form to support the tasks of exploration, confirmation, presentation, and understanding. This book is designed as a textbook for students, researchers, analysts, professionals, and designers of visualization techniques, tools, and systems. It covers the full spectrum of the field, including mathematical and analytical 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 building one's own visualization tools. Numerous data sets have been made available that highlight different application areas and allow readers to evaluate the strengths and weaknesses of different visualization methods. Exercises, programming projects, and related readings are given for each chapter. The book concludes with an examination of several existing visualization systems and projections on the future of the field.

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Editorial Reviews

From the Publisher

A 2010 CHOICE Outstanding Academic Title

College-level collections strong in concepts and theory surrounding data visualization will find Interactive Data Visualization: Foundations, Techniques, and Applications to be a powerful addition, covering all the details and tools needed for building visualizations around data. From math and statistical graphs to cartography and scientific displays, this offers plenty of details for creating visual displays of data, offering color illustrations throughout and plenty of refinement details.
The Midwest Book Review, August 2011

With chapters on elaborating on the importance of visualization, understanding the data without it, the relation to the human eyes and mind, what technology has brought in the avenues of displaying and interacting data, no concept is really left untouched. Enhanced with example data, samples, a history of computer graphics, and more, Interactive Data Visualization is a solid text to have on hand for any community or college library collection.
—James A. Cox, The Midwest Book Review, August 2010

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Product Details

  • ISBN-13: 9781568814735
  • Publisher: Taylor & Francis
  • Publication date: 6/14/2010
  • Series: 360 Degree Business Series
  • Pages: 513
  • Sales rank: 1,197,344
  • Product dimensions: 7.50 (w) x 9.50 (h) x 1.00 (d)

Meet the Author

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.

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Table of Contents

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

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