I launched this page at the 2017 Pleiades National Planetarium Conference. If you’re interested in my talk from that session, I’ll be posting it to SlideShare soon; otherwise, all the resources I mentioned (and more) appear below. This is (I hope needless to say) a living document, and I’ll be adding to it continually…

My Stuff

You can find a fairly succinct statement of my overall views on visualization in my article “The Language of Visualisation” (available as a PDF here), originally written for the Communicating Astronomy with the Public Journal as part of my “Visualising Astronomy” column. (A European journal, which explains the variant spelling of “visualising.”)

Here’s a YouTube video featuring 40 minutes of me talking about “The Power of Data Visualization” at the Forum on Digital Media for STEM Learning: Climate Education held at WGBH in November 2015. I talk a lot about planetariums.


Science Visualization

Jen Christiansen is senior graphics editor at Scientific American and a spectacularly insightful thinker. You should read everything she writes for the SciAm blog. Thoughtful, wonderful stuff.

Data Visualization

Albert Cairo’s The Functional Art is a must read, with frequent, detailed posts about the choices made in depicting data and the ways in which visuals trick us, often deliberately. Cairo has also recently launched his Visual Trumpery tour, a series of lectures on “how to fight against fake data and visualizations—from the left and from the right.”

Nathan Yau’s Flowing Data offers regularly updated insights into various applications of data—from visualization to analysis, with more emphasis on technical processes than Cairo.

Noah Iliinsky doesn’t update his Complex Diagrams blog much, but there’s some great stuff there! The Properties and Best Uses of Visual Encodings PDF is probably my favorite (along with an IBM whitepaper on how to use it), but I also like the Four Pillars of Visualization.

At some point, I rean across Ross Ihaka’s online resources for his Statistics 120 – Information Visualisation class, which he evidently taught for the University of Auckland from 1999–2002. There’s some great stuff here—for example, a discussion of Stephens’s Law he describes in Lecture 11 and Chapter 5 of his notes. I wish I could have taken the class!

You also learn by looking at (and critiquing) questionable work. My favorite site for this is WTF Visualizations, which explicitly showcases “visualizations that make no sense,” typically with little or no comment. (Once upon a time, Terrible Infographics on Tumblr provided several more examples, often with a little more to say about each egregious example; sadly, it sparked and fizzled six years ago.)


Everyone should definitely read Rob Simmon’s six-part “Subtleties of Color” article, written when Rob worked for NASA. It covers all the bases and points you to many useful resources.

(And just for kicks, everyone should read Randall Munroe’s xkcd color survey results, which underscores the highly subjective nature of color perception.)

I’m colorblind, so I feel compelled to share some resources that will help designers accommodate me and my fellow differently-abled viewers.


Colin Ware’s Visual Thinking for Design is a slim, easily digestible must-read for anybody interested in the visual representation of data. His longer, heavier, more obliquely titled Information Visualization Perception for Design (I have the second edition, but it’s currently in its third) is also a valuable resource, albeit less user friendly.

Julie Steele and Noah Iliinsky’s Designing Data Visualizations is an even slimmer volume, but it’s packed with good advice, especially for people who want to deploy a standard toolkit of charts and graphs effectively. If you purchase the book, I recommend its digital edition—the print-on-demand version is in black and white, which makes portions of the book practically indecipherable.

The aforementioned Nathan Yau has written a couple interesting books, and I think my favorite is Data Points (subtitled “Visualization That Means Something”), which avoids more technical digressions to focus on questions of design. That said, his more recent Visualize This offers great advice on the nuts and bolts of creating visualizations with a variety of common tools, with actual code examples in JavaScript, Python, and R.

I guess I have to mention Tufte.


I mention Noah Iliinsky a couple times above, so what’s one more reference? His whitepaper for IBM, “Choosing visual properties for successful visualizations,” is a quick and easy introduction to some core concepts in thinking about visualizing data. Available via Dropbox as a PDF.

In May 2017, Northeastern University’s Storybench published the results of interviewing “72 data journalists, web developers, interactive graphics editors, and project managers in leading digital newsrooms around the world,” extracting lessons learned and sharing them in the form of a paper, “Collaborative, Open, Mobile: A Thematic Exploration of Best Practices at the Forefront of Digital Journalism,” available here as a PDF.


I currently co-chair the Gordon Research Conference for Visualization in Science and Education, recently held in August 2017 and coming up again in 2019. A remarkable, highly interdisciplinary gathering of academics and practitioners.