Designing Data Visualizations [Paperback]

Noah Iliinsky (Author), Julie Steele (Author)

Book Description

Publication Date: September 29, 2011

Data visualization is an efficient and effective medium for communicating large amounts of information, but the design process can often seem like an unexplainable creative endeavor. This concise book aims to demystify the design process by showing you how to use a linear decision-making process to encode your information visually.

Delve into different kinds of visualization, including infographics and visual art, and explore the influences at work in each one. Then learn how to apply these concepts to your design process.

• Learn data visualization classifications, including explanatory, exploratory, and hybrid
• Discover how three fundamental influences—the designer, the reader, and the data—shape what you create
• Learn how to describe the specific goal of your visualization and identify the supporting data
• Decide the spatial position of your visual entities with axes
• Encode the various dimensions of your data with appropriate visual properties, such as shape and color
• See visualization best practices and suggestions for encoding various specific data types

Editorial Reviews

About the Author

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.

Noah Iliinsky 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.

Product Details

• Paperback: 114 pages
• Publisher: O'Reilly Media (September 29, 2011)
• Language: English
• ISBN-10: 1449312284
• ISBN-13: 978-1449312282
• Product Dimensions: 7 x 0.2 x 9.2 inches
• Shipping Weight: 8 ounces (View shipping rates and policies)
• Average Customer Review: 2.9 out of 5 stars  See all reviews (10 customer reviews)
• Amazon Best Sellers Rank: #95,233 in Books (See Top 100 in Books)
  • #7 in Books > Computers & Technology > Computer Science > Artificial Intelligence > Machine Vision
  • #14 in Books > Computers & Technology > Graphic Design > Data & Information Visualization
  • #50 in Books > Computers & Technology > Databases > Database Design

Most Helpful Customer Reviews

26 of 27 people found the following review helpful

3.0 out of 5 stars O'Reilly ruined this book October 17, 2011

By hardcoreUFO

Format:Paperback

The goals of this volume are completely undermined by the publisher's choice to print greyscale figures. Entire sections on color and color selection are rendered useless because of this. There is no excuse, in 2011, to print a data visualization book (or any other book, for that matter) in greyscale and B&W. O'Reilly should know better.

10 of 11 people found the following review helpful

1.0 out of 5 stars Too bad ... December 15, 2011

By JYB

Format:Paperback

I am very disappointed by this book.
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).

4 of 4 people found the following review helpful

3.0 out of 5 stars Nice introduction to data visualization November 24, 2011

By Ivo Flipse

Format:Paperback

As the book mentions: "It is a set of steps and rules to follow that will get you 80% of the way to turning out great work."

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.