Editorial Review:
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.
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Customer Reviews
Average Customer Rating: 
Classic introduction to InfoVis 2008-02-19
This is a basic introduction to InfoVis, covering topics from human perception to improving the decision-making processes with visualizations. It is worth having if you are in the field or are serious about improving your visualizations.
Some of the negative comments in reviews must refer to the first edition. My second edition has (some) color images as appropriate throughout the book. There are still a few errors, but not a large number. There are definitely a few low quality examples.
Not applicable and not a suitable text book  2007-06-02
The book gives sme guidleines (supported by research) but it won't be suitable for practioners but as a text book of no very good use for an information visualization course. It was tedious to have it as our text book I don't know if this is what I think or is it the actual case.
Great for Interface designers or visualizationers  2006-02-28
WOW. This guy did his homework! Ware covers the basics and more advanced topics. I felt he goes beyond most books on this subject by giving his suggestions and not just stating facts.
The best one volume book out there, but not perfect 2004-10-05
This is the best single volume book on the subject of information visualisation that I've read. Sure, there are other very nice books on diagrams, maps, data analysis, modelling and scientific visualisation. However, none of them have the scope of this book.And therein lies the problem. For a single volume book Ware's effort tries to cover too much and some of the chapters are quite weak (chapter 0 and 10). Also, the fact that it was written by a psychologist shows in a good and bad way: human visual cognition is correctly the foundation upon which to build visualisation. Unfortunately the examples and the ideas for implementation are often lacking or poor in quality. The first edition also has typesetting errors, so be sure to get the second edition. All in all, it's still a book worth getting if you're in any serious way connected with the practise of visualisation. However, don't expect it to be the bible of the field, as such a thing does not exist (yet).
Excellent, despite its flaws 2000-08-11
Ware's book provides a technically accurate and well-written overview of the gamut of issues pertaining to information visualization -- from basic visual anatomy and physiology to techniques for creating effective displays from multidimensional data. Yes, it's "introductory" in nature, but it's the most comprehensive introduction I've seen to this complex and emerging field. It would make an excellent reference or textbook. The 5-star content gets 4 stars because of the book's numerous editorial flaws. For example, several illustrations in the text reference color plate images that simply don't exist. And at least a half-dozen works cited in the text don't appear on the reference list. All-in-all, a rather slipshod editing job.
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