Designing Data Visualizations Paperback – 2 Oct 2011
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Intentional Communication from Data to Display
About the Author
Noah Illinsky has spent the last several years thinking about effective approaches to creating diagrams and other types of information visualization. He also works in interface and interaction design, all from a functional and user-centered perspective. Before becoming a designer he was a programmer for several years. He has a master's in Technical Communication from the University of Washington, and a bachelor's in Physics from Reed College.
Julie Steele is an Editor at O'Reilly currently working on titles related to Python, SQL, PHP, web frameworks and CMS, databases (relational and non-relational), big data and cloud computing, and data visualization. She's also interested in data transparency and open government, and recently completed a master's degree in political science at Rutgers University.
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Top Customer Reviews
Contrary to their own advice ("Are you using color to represent quantity? Stop it.", p. 92), the authors reserve considerable space for discussing color. That's weird, but what is even weirder is that some of these discussions are illustrated with color scales and samples -- which are actually printed in grey scales! Having read the book, I can understand why the publishers may not have wanted to invest more in the manuscript than necessary. But that does not make it less problematic.
More importantly for me, I got increasingly annoyed by the verbosity and use of boilerplate language. Take this "tip" from page 49: "Consider the following challenge. For every visualization you see, ask yourself these two questions: Are the axes all well defined? Are they used effectively? Unfortunately, the answer to these is often 'no'. Better use of axes will be the first step to improvement." Yes, this all makes sense, doesn't it? Who wouldn't want to have their axes "well defined" and "used effectively"? So how can I do this? Ah, right, I am supposed to start with "better use of axes". Thank you, question answered.
This may come across as sarcastic, but this is the style that much of the book is written in. This is somewhat ironic. The authors talk a lot about how crucial it is for designers of visualizations to reduce the noise and focus on the story or message. However, they do not seem to have applied the same principles to their own text.Read more ›
- Easy to read
- Good examples
- Contains a good reading list
- Black and white where colored figures were intended
- Could be more referenced
- A bit short and
- Does not include any interactive features
It's a very relevant book to many as we strive to communicate the growing amount of data we are capturing. The book introduces the many different types of data visualisations including info-graphics and the use of charts, tables, graphs etc. The authors spend a lot of time explaining the reasons behind the visualizations which is very important, but often overlooked in other books. There is lots of information about colors, fonts, audiences and purposes and the channels used.
The authors support each piece of information with examples and external references, which adds lots of credibility to their arguments. There are some really insightful ideas and a lot of examples of good and bad visualizations which help make each point easier to understand.
It's great that the authors spend time talking about color blindness and the psychology behind colors, locations, shapes and proximity. I found this chapter incredibly useful indeed.
At times it felt like the book repeated itself, especially in the first few chapters. I got the sense I was reading the same information again, but thankfully the later chapters made the content more distinct.
Overall this is an easy to read and fun book that gives you the background, insight and tool ideas needed for you to get cracking with building visuals. It's a good book for dipping in and out of to get inspiration and ideas on visualizing data.
Very good book indeed.
Most Helpful Customer Reviews on Amazon.com (beta)
It deals with graphics and design, including colors ... but it is printed in black and white!
Very useful to judge the "good" or "wrong" color of any logo or diagram (p. 36) ...
In addition, the print quality is poor: some diagrams are illegible (p. 44, 46).
The book does a decent job of giving you a clear overview of the basics of good data visualizations. It also helps bring across the message that you should think about why you're designing it and urge you to focus on that.
If you haven't read any books about Data Visualizations then this book is a great introductory tour. If you've already delved deeper into the subject, then the book might not hold much news for you.
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