Interactive Data Visualization

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A01=Daniel Keim
A01=Georges Grinstein
A01=Matthew O. Ward
Abdominal Aortic Aneurism
advanced data visualisation techniques
Albers Equal Area Conic Projection
Ang Le
Author_Daniel Keim
Author_Georges Grinstein
Author_Matthew O. Ward
Category=UML
Category=UYZF
Choropleth Maps
Computer graphics
Conjunction Search
Data Set
Dense Pixel Displays
Document Visualization
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eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
geospatial mapping techniques
Google Map API
human perception
human-computer interaction
indian Edition
information visualisation
Information Visualization
information visualization techniques
Informative Visualizations
Iris Data Set
Line Integral Convolution
Low Level Visual System
Marching Cubes
mathematical and statistical graphs
multivariate data analysis
Node Link Diagram
Parallel Coordinates
Preattentive Processing
Static Temporal Data
techniques for time-oriented data
two- and three-dimensional scientific displays
usability evaluation methods
Va Ri
Vice Versa
visual analytics
Visualization of Data
Visualization Pipeline
Visualization Research
visualization systems
Visualization Techniques
visualizations in knowledge discovery

Product details

  • ISBN 9781482257373
  • Weight: 1500g
  • Dimensions: 191 x 235mm
  • Publication Date: 10 Jun 2015
  • Publisher: Apple Academic Press Inc.
  • Publication City/Country: CA
  • Product Form: Hardback
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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.

Web ResourceA 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.

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.

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