Designing Data Visualizations: Representing Informational Relationships

by Noah Iliinsky, Julie Steele

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

Genres: Design, Nonfiction, Computers

108 pages, Paperback

First published January 1, 2011

Reviews

[René C. Nielsen · Rating 4 out of 5]

Great little book. Primarily for people not schooled in statistics and/or data analysis. I'm looking at you, journalists and graphic designers. I will definitely use it as a checklist when designing visualizations. There are quite a few pitfalls, and this book is good at explaining them.

[Mehdi]

There is an increasing abundance of tools, languages, and frameworks for data visualization. But success is built upon having a good design to implement, and that requires a linear process of encoding information for visual transmission and subsequent decoding by wetware (the reader's brain). Join us as we introduce you to this process, including some basic concepts and best practices, so that your message may be transmitted without interference.

[Bill · Rating 1 out of 5]

Not recommended, other than for a useful list of tools in an appendix. One of the few O'Reilly books that disappointed me. All figures printed in black&white - although color versions are available in PDF online. That might be reasonable way to defray printing costs, but in this case the book is still vastly over-priced.

[Gabriele · Rating 1 out of 5]

Not really useful even as an introductory booklet. Printing infographics and pictures in black&white while the half of the book is devoted to effectivenees of colors in data visualizations is offensive.

[Ahmed Alkatheeri · Rating 3 out of 5]

An interesting aspect of the book is its coverage of design elements such as color, size, typography, shape, icons, lines, and positioning when visualizing data. It suggests understanding and visualizing the data to try new things, question assumptions, iterate and adjust as you go, and let the data guide you. Additionally, it reminds readers to keep their goals in mind while trying to extract knowledge and insights from data.

The book's appendix contains useful resources such as design tools and questionnaires to consider as a part of the design process, keeping customer-centricity at the forefront when working on data visualization, extracting knowledge and insights, and determining the call-to-action for the reader.

It’s a small book reference that can be used and referred back to when working on data visualization projects.

[Aaron Adamson · Rating 3 out of 5]

Has some good principles and guidelines for visualization, but who in the world thought it was a good idea to publish this thing in black and white? It violates many of the book’s own principles. It would also benefit from more examples (show, don’t tell).

If you want a short reference text to remind yourself of the basics, though, without much extraneous content to dig through, this book will do the job.

[Rainer Mesi · Rating 3 out of 5]

This book helps to get a good overview of data visualization best practices.
It also dives a bit into details and practicalities and the reasoning behind them.

The second half of the book is a good checklist of do's and dont's (also for seasoned visualizers).

If you need to graph some data, and want to read a book about it, might as well pick this one.

[Nora · Rating 3 out of 5]

Good quick read on data visualization and basic design.

[David Nusinow · Rating 2 out of 5]

Didn't get a ton out of this because I had to learn most of it by experience. If I were just getting started moving beyond the basic defaults of visualization I would have gotten more out of it. There's some good references and such to help guide the visualization process, but most of the recommendations are fairly general. Still, it's a quick read, and the authors are commended on knowing the limits of what they wanted to say.

[Charles · Rating 3 out of 5]

A short book about designing data visualizations which is the skill of telling a story with numbers (data). This may sound tedious but let's face it - we see these graphics every day - on web sites, in magazines, newspapers. There is a useful checklist at the end of the book as well as a list of useful web sites and books.

[Daniel Galassi · Rating 3 out of 5]

This book covers pretty much the same topics found in Stephen Few's Information Dashboard Design.
It is good and interesting but I was probably looking for new details.
Interesting reading only if you haven't read Stephen Few's books before.

[Vojtech Rinik · Rating 2 out of 5]

Not much I didn't already know before.

[Jessy · Rating 4 out of 5]

Pretty good intro, though a little too short and focused on the design aspect; did not address exploratory data analysis, which would have been useful.

[André Gomes · Rating 3 out of 5]

A very small but yet very powerful book about dataviz.

[Neij Mehta · Rating 4 out of 5]

Decent primer on data visualizations. Lots of useful online design resources