recommended reading: Info We Trust

Info We Trust: How to Inspire the World with Data is a beautiful book. It feels nice to hold. The colors are vibrant. The language is poetic. The content is inspiring.

If you work with or have an interest in data, you should own this book.

I read it from cover to cover in a two day sprint a few weeks ago in preparation for a conversation with author—and friend of mine—RJ Andrews. It’s the first book I’ve read so thoroughly in quite some time: pouring over not only the main content, but also the preface and end matter. Nearly every inch of this book is filled with information: margins are full of quotes from wide-ranging sources (RJ read hundreds of books over the course of development) and other relevant tidbits. The text and margins are interspersed with hand-drawn images (even the graphs are drawn by hand!) that help reinforce and illustrate concepts. Here’s an example 2-page spread:

The chapters are relatively short in length but dense in ideas and concepts, which provides good balance. The book is divided into six main sections: (1) Origin, (2) Metaphorical, (3) Mathemagical, (4) Sensational, (5) Informational, and (6) Onward. Also don’t miss the impressive and cleverly formatted bibliography and RJ’s essay on how the book came to be.

While I enjoyed it all, I especially appreciated the Mathemagical chapters: Create to Explore, Explore to Create, and Uncertain Honesty. I’m commonly asked questions about exploratory data analysis, and together these chapters pose a number of thought-provoking questions that can help direct those working with data through this process. I also really appreciated the Sensational chapters, which explore a number of other areas (e.g. Museum design), imploring the reader to draw their own parallels to data storytelling. Chapter 16 “Inspire Trust” was another standout section for me, with some great insightful discussion on people’s belief systems and the resulting difficulty of changing minds.

Info We Trust is definitely not a how-to book, and yet it is interlaced with practical advice. To give you a sense of language and style, here is one excerpt I highlighted, from Chapter 3, Embodied Encoding (pages 43-44):

There is a candy shop full of ways we get to communicate meaning visually. For example, the concept of importance is naturally associated with size. Big things are important. Why might this be? We start off small. When you are a child, big people like your parents are important. Bigger people, the ones who were already grown up, are much more powerful. Sometimes big adults are even scary. Even longer ago, big animals, you must remember, used to eat us.

Big things, whether parent or predator or palm tree, are also important because, to our eye, big things are closer. Ultimately, big things occupy a larger portion of our visual fields. There, big things vie for more of our attention. Important big things stretch, conceptually, into our language (e.g., “I wish you would stop focusing on small matters and see the giant issue we have”). Embodied metaphors transcend language because all people have similar embodied experiences. Big things are important in Zulu, Hawaiian, Turkish, Malay, and Russian. When we make pictures of important things, we do not have to abstract all the way to language metaphors. Just draw important things bigger on the page.

At one point, RJ discusses sparking curiosity in your audience. He says—and I’m paraphrasing—that good stories leave space for the audience to make connections. The book itself does this beautifully—not prescribing “do this” or “don’t do that,” but rather making observations and leaving the reader space to make connections and extrapolate to their own work.

I found myself experiencing both excitement and sadness as I neared the end: excitement, as I could tell it was building in a grand crescendo, sadness that it would soon be over. That sadness abated quickly, however, when I got the chance soon after ending my own experience with the book to talk with RJ about it. You can listen to our conversation:

There are a lot of fun and inspiring surprises throughout Info We Trust that I won’t spoil for you. Let me just end by saying that I highly recommend this book and I hope you enjoy it as much as I did.

Thank you, RJ, for creating Info We Trust and for sharing it with us all!

recommended reading: #MakeoverMonday

I arrived home from a trip a few weeks back to a fun package containing a thematically wrapped copy of MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time. I had a chance to review and provide feedback on an early draft chapter of this book, cowritten by Andy Kriebel and Eva Murray, which was published last month.

Just yesterday, I spoke with Andy and Eva about #MakeoverMonday: the project, the book, their writing process, and more, which you can listen to in the latest episode of the SWD podcast.

At more than 400 pages, #MakeoverMonday is a hefty book and contains hundreds (300, to be exact!) of visuals created by more than 50 people. The book was born out of the weekly #MakeoverMonday project that Andy has been doing for a number years (joined by Eva in 2017). Each week, they select a graph and invite people to critique and improve it. People share their creations (see Twitter: #MakeoverMonday). Andy and Eva also host weekly live viz reviews, where they provide feedback to a subset who volunteer their work, with the expectation that the creators each iterate based on that feedback and re-share. More info can be found at makeovermonday.co.uk. Andy and Eva curated examples from this weekly project as the basis for their book.

Given the sheer number and variety of visuals in #MakeoverMonday, it’s great to flip through to see examples of things done well—and some cases of things gone wrong. Many learnings and lessons are recounted, from the habits of a good data analyst to working with incomplete data to trying new things. In particular, I appreciated Chapter 8, “Iterate to Improve,” which focuses on the important role of giving and receiving feedback and illustrates through a number of before and after examples how minor changes can have major impact on the overall effectiveness of a visual. If you analyze and visualize data—or would like to—this is a book you will likely want to have on your shelf.

As a bonus, data from the weekly challenges that feed the visuals profiled in the book are all available for download. This is a great resource if you ever find yourself in need of data to visualize or if you want to recreate or further improve upon any of the examples in the book.

#MakeoverMonday can be purchased on Amazon. Listen to my chat with Andy and Eva in Episode 11 of the SWD podcast.

recommended reading: The Big Book of Dashboards

It's a big book indeed: at 432 pages, it is wider and thicker than many of the other books on my shelf, and it is filled with dashboards. I've been recommending The Big Book of Dashboards regularly at my workshops since its publication in April of this year, and am overdue on my official endorsement of it here. If you build dashboards, you should own this book.

When creating a dashboard, if you've found yourself wondering, What would be a really good way to show this?—you will find a number of inspiring potential answers to that question in Wexler, Shaffer, and Cotgreave's book. The meat of the tome is Part II, where they present 28 dashboards from various industries on a wide-ranging set of topics. In each chapter, they introduce the full dashboard, briefly discuss the business scenario, then break the dashboard into its component pieces with commentary on both what works well and what they might have done differently. You will find inspiration here. This is enveloped by Part I on the front-end, which covers some data visualization basics, and Part III on the back-end, which covers real-world challenges the authors have faced in their combined 30+ years of working with dashboards and ideas for overcoming these challenges.

In addition to buying the book, I recommend checking out the companion site (where you can find additional resources, including many of the actual dashboards featured in the book) and following the authors' work: Steve, Jeff, and Andy. Nice work, guys!

recommended reading: Better Presentations

My copy of Better Presentations is filled with shakily written notes on post-its (I've been reading it during take off and landing of my last few flights). While the subtitles says it's for "scholars, researchers, and wonks"—and the book is clearly written with them in mind—nearly all of of Jon's thoroughly researched and well written tips and strategies are applicable to business presentations as well. If you ever give presentations, you should read this book.

Better Presentations is organized into three sections: 1) designing your presentation, 2) building your presentation, and 3) giving your presentation. The first section includes chapters on planning, color and type (some standout resources in this part of the book include the Presentation Worksheet, hourglass structure for ordering a presentation, and discussion on how to pick a color scheme). Section two is divided into the text slide, the data visualization slide, the image slide (yes! I'm always looking for a good resource to point people to in response to questions about this and I took a ton of notes in this section) and the scaffolding slides. The final section has a chapter on presenting—one of my only gripes with the book is that I wish this part had been longer...but alas, it mainly comes down to practice, practice, practice, so I guess it's difficult to turn that into more than a chapter—and a final section on the technical nitty gritty. Each chapter ends with a schematic of "visualize, unify, and focus," with the main points summarized along these dimensions. 

Jon and I are quite aligned in our thinking, and as I read the book I found myself saying, "yes! yes!" in response to many of his points and tips. (One area of clear agreement—Jon writes—"Even more difficult than discerning information from a single pie chart is discerning information from two pie charts.") He includes a number of awesome straightforward slide redesigns, all using real examples (mainly from the public sector—eduction, government, socio-economic stuff that anyone can understand and relate to). He discusses multiple strategies for many of the scenarios presented. Jon also includes super practical/tactical tips (e.g. step-by-step to set up the color palette in your presentation software, or how to remove the background of an image in PowerPoint).

I came away with a list of "food for thought" items—things I either haven't been doing, or new potential language to describe and reinforce ideas that I also recommend:

• Delete the actual bullet points (ah, the irony of starting out my bulleted list with this one! ...but this isn't a presentation, so my bullets are ok, right?) and instead using space to differentiate the points. He's totally right. The points themselves have no purpose and add clutter!
• Use icons in place of text for category names in graphs where there is something easily recognizable (Jon uses an education example where the dollar sign is used to represent tuition, a house icon is used to represent housing, etc.). I've done this with logos for brands in the past, but never considered the use of icons in this manner, which could be interesting.
• Make use of the "Picture Superiority Effect"—Jon points to research that indicates an audience is twice as likely to recall a topic if it includes and image and also cites several studies with findings supporting images help recall and comprehension. Images used well will serve your presentation well.
• Design for the back row. I love this simple advice. I'm always advocating that text should be bigger than you think it should be, but this language gives something more concrete to that idea—I actually picture the room when I think about it, which I think could help lead anyone to a more audience-centric presentation.
• Aim for "Twitter-like" headlines. I find myself using words like "active, pithy slide titles" for this same concept (clearly, Jon is more concise!).
• Use more slides. I actually wrote "YES!!!" on a post-it note where this tip is written. Jon describes and illustrates what he calls the layering approach, which is similar to how I use animation in PowerPoint to build a slide or graph, one piece at a time, drawing the audience's attention to where you want it as you talk about the relevant point. You may end up with a ton of slides using this approach: a ton of slides that are super easy for your audience to process and reinforce what you're saying. Win!

Overall, Better Presentations is a great and relatively fast read that I'd recommend to anyone who is preparing or delivering presentations. Also be sure to check out the many great supplementary resources on Jon's site.

the functional art

It's a little beat up and has scraps of paper sticking out in various directions marking pages I want to refer back to: it's my copy of the functional art by Alberto Cairo, and it's been everywhere with me over the past month - from LA to DC to Milwaukee, and several places in between (yes, that probably means I'm a slow reader). I finished it on my latest plane ride home. In a word: it was awesome.

As the subtitle declares, the focus of the book is information graphics and visualization. Alberto has a conversational, super accessible writing style. His research is augmented with his extensive experience in data journalism and the book is filled with illustrative stories and examples.

the functional art begins with a section on Foundations - what visualization is and does, the importance of building a narrative structure, and introduces a visualization wheel to evaluate competing priorities. It then moves into Cognition - discussion of the eye, the brain, and how people see. The third section focuses on Practice - the infographic creation process and interactive graphics. While I enjoyed the entire book, the final section, Profiles, was my personal favorite - it recaps Alberto's interviews with various practitioners working with infographics. I also enjoyed examining the various examples throughout the book and seeing the progression from sketches to final product.

The book was inspiring, as is Alberto's work in general. I had the pleasure of speaking with him a couple of months ago, when he was getting ready to launch the first massive online course on an Introduction to Infographics and Data Visualization through the Knight Center. This 6 week course filled up quickly, so a second was recently announced that begins in January (details here). Alberto also teaches at the University of Miami and blogs at www.thefunctionalart.com. His passion in this space is clear and from what I've seen, permeates through all that he does.

For those interested in infographics or data visualization in general, I highly recommend the functional art; you can purchase a copy of it here.

visualize this

Nathan Yau writes one of my favorite data visualization blogs, FlowingData. His recently published book has been sitting on my shelf untouched for much too long. Earlier this week, I decided to remedy that.

His book is Visualize This. Subtitle: The FlowingData Guide to Design, Visualization, and Statistics. It's written in the first person and is super accessible, full of examples and anecdotes to make the lessons real. The book includes references to a lot of publicly available data and also has links to each dataset used, so the reader can follow along through the steps that are explained.

After starting with an introduction on telling stories with data (obviously near and dear to my heart), the book jumps into the practical question of how. There are step by step instructions for scraping data from websites, using Python to reformat it, and the strengths and weaknesses of various out of the box applications and programming languages for analyzing and visualizing data.

By his own words, Nathan's book is "example-driven and written to give you the skills to take a graphic from start to finish." It accomplishes this goal. The middle chapters each focus on a different kind of visualization problem: visualizing patterns over time, visualizing proportions, visualizing relationships, spotting differences, and visualizing spatial relationships. Yau follows a thorough, hands on approach. For example, in the chapter focused on time series, he goes through what to look for, the best types of graphs to use in different scenarios, how to load the data into and plot in R, and how to fine tune the visual using Illustrator. Relevant statistical methods are incorporated as makes sense, for example, smoothing and estimation.

While there is some very solid foundational material, the majority of the book is focused on the practical question of how to actually analyze and visualize the data. It seemed to me most tailored to the person who is looking to move beyond Excel and the like and get started using R and Illustrator (with some time devoted to interactive graphics as well).

Throughout, Nathan's graphics are beautiful and accessible - great examples of effective data visualization. He follows the rules he sets forth in every one:

• explain encodings,
• label axes,
• keep your geometry in check,
• include your sources, and
• consider your audience.

The final chapter focuses on designing with a purpose. He says he always assumes that people are showing up to his graphics blindly and puts the onus on himself as the designer to prepare the audience with the relevant context and insights. "After you learn what your data is about, explain those details in your data graphic. Highlight the interesting parts so your readers know where to look. A plain graph can be cool for you, but without context, the graph is boring for everyone else."

Well said, Nathan!