In a recent chat with Jérôme Cukier about the state of visualization related literature, he mentioned Julie Steele and Noah Iliinsky’s new book “Designing Data Visualizations” published by O’Reilly. Jérôme noted that it would be a good primer for people who are already working with data and looking for guidance about making their work more accessible. I thought of another group of people who might find themselves overwhelmed by the amount of choices they have to make while working on visualizations: designers with little knowledge about visual perception and how to apply its’ principles to their work. After reading it from cover to cover in just a few hours I can highly agree with Jérôme’s recommendation. Julie and Noah manage to introduce the basics of visualization in a very accessible and comprehensible way. Furthermore, the slim format and of the book makes it a great read for your next flight or train ride.
We are currently working with an intern here at Interactive Things: Flavio Gortana joined us three months ago and continues to surprise us with how fast he picks things up and how persistently he works on his ideas. After having worked on illustrations, iconography and interfaces it was time for him to get started with his first visualization project. “Designing Data Visualizations” should build the foundation for the work ahead. Here’s how Flavio experienced his first introduction to visualization, what he learned and how this helps him to move forward.
What the book taught me
Before starting something new, for me it is always important to know what I’m dealing with and to have a general knowledge about it. I’m not the kind of person able to just jump into something without thinking about it before. Since the only visualizations of real data I’ve made so far were some graphs in physics class, this book provided me with a basic vocabulary of terms and concepts needed to dive deeper into the topic.
I have been aware of my interest in visualized data for a long time and of course, I’ve already seen many different types of graphics that intended to explain a dataset. Until not so long ago, I have not given much thought to the quality, techniques or the concepts behind those. I just took them as they were and I tried to discern the information I was interested in. Of course, some even looked nice and had beautiful color schemes while others didn’t. The major benefit this book gave me was a fundamental change of how I look at a data visualization. It did so not by telling me how to analyze or criticize such graphics, but it provided a solid overview of visualization types and ways to distinguish between them. Furthermore, I learned about the underlying techniques and how to classify visualizations.
A good thing about Designing Data Visualizations — especially for a novice like me — is that it is rather practically oriented than theoretically. The explained concepts are very straight forward and I assume they are directly applicable to real problems. They are not some highly sophisticated theories without much practical relevance. Contrary to the “experimenting – mentality” of many design educations, the authors give clear advice what to do and what to avoid. They also state in the beginning that only one who knows the rules can break them in a suitable way. Of course, this may feel very constraining in the first place. But at the same time the book reveals the diversity of possibilities inside the given constraints. For me this will be helpful to get started very quickly. By exposing and explaining the different elements of data visualization, it also made me think of very trivial things I was not aware of before: Have you ever thought about color not having a natural order like saturation or the size of a shape? Or, have you ever thought about using the area instead of the radius while visualizing data with circles? I did not.
In conclusion I can say that the book answered many questions I had in the first place. It may not provide new or revolutionary concepts, but it shows and explains the existing ones in an understandable, manageable and accessible way. Although this won’t directly lead me to some groundbreaking visualizations, thanks to the good summary I will be aware of the variety of things to consider when visualizing data.
Flavio Gortana is an interaction design intern at Interactive Things. You can learn more about his work and experiences by reading his blog (German).