Most designers know that yellow text presented against a blue background reads clearly and easily, but how many can explain why, and what really are the best ways to help others and ourselves clearly see key patterns in a bunch of data?
This book explores the art and science of why we see objects the way we do. Based on the science of perception and vision, the author presents the key principles at work for a wide range of applications--resulting in visualization of improved clarity, utility, and persuasiveness. The book offers practical guidelines that can be applied by anyone: interaction designers, graphic designers of all kinds (including web designers), data miners, and financial analysts.
*First work to use the science of perception to help serious designers and analysts optimize understanding and perception of their data visualizations.
- Major revision of this classic work, with a new chapter on visual thinking, new sections on face perception and flow visualization, and a much expanded chapter on color and color sequences.
*New to this edition is the full color treatment throughout, to better display over 400 illustrations.
Professionals in user interface/user interaction designer; computer graphics, including those who are the techie type as well as those who are graphics designers; financial analysts; research scientists and engineers; data miners; and managers faced with information-intensive challenges
Figure Credits Foreword Preface Preface to the First Edition Chapter 1: Foundation for a Science of Data Visualization Chapter 2: The Environment, Optics, Resolution, and the Display Chapter 3: Lightness, Brightness, Contrast, and Constancy Chapter 4: Color Chapter 5: Visual attention and information that Pops Out Chapter 6: Static and Moving Patterns Chapter 7: Visual Objects and Data Objects Chapter 8: Space Perception and the Display of Data in Space Chapter 9: Images, Words, and Gestures Chapter 10: Interacting with Visualizations Chapter 11: Thinking with Visualization Appendix A: Changing Primaries Appendix B: CIE Color Measurement System Appendix C: The Perceptual Evaluation of Visualization Techniques and Systems Bibliography Subject Index Author Index About the Author
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- © Morgan Kaufmann 2005
- 7th April 2004
- Morgan Kaufmann
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The author takes the "visual" in visualization very seriously. Colin Ware has advanced degrees in both computer science (MMath, Waterloo) and the psychology of perception (Ph.D., Toronto). He has published over a hundred articles in scientific and technical journals and at leading conferences, many of which relate to the use of color, texture, motion, and 3D in information visualization. In addition to his research, Professor Ware also builds useful visualization software systems. He has been involved in developing 3D interactive visualization systems for ocean mapping for over twelve years, and he directed the development of the NestedVision3D system for visualizing very large networks of information. Both of these projects led to commercial spin-offs. Professor. Ware recently moved from the University of New Brunswick in Canada to direct the Data Visualization Research Laboratory at the University of New Hampshire.
Data Visualization Research Lab, University of New Hampshire, Durham, USA
"This unique and essential guide to human visual perception and related cognitive principles will enrich courses on information visualization and empower designers to see their way forward. Ware's updated review of empirical research and interface design examples will do much to accelerate innovation and adoption of information visualization." —Ben Shneiderman, University of Maryland "Colin Ware is the perfect person to write this book, with a long history of prominent contributions to the visual interaction with machines and to information visualization directly. It goes a long way towards joining science to the practical design of information visualization systems." —from the foreword by Stuart Card, PARC "Better than anyone else that I've encountered in my work, Colin Ware explains how visual perception works and how it applies to data presentation." - Stephen Few -- Intelligent Enterprise