recommended reading: Data Points

I've been a long-time fan of Nathan Yau and his work. He writes the popular (and prolific) blog, Flowing Data and published his first book, Visualize This, in 2011 (you can read my review of that book here).

Nathan's second book, Data Points, came out earlier this year. When a client of mine said the following -

"I've only read chapter 1 so far of Data Points, but it's the best chapter 1 on data vis I've read. He talks about the data being an abstraction for reality, and he uses his own wedding pictures to explain. Great idea, and great example."

I promptly ordered my copy and, upon arrival, consumed its contents. I must agree, this is a fantastic book. Moving beyond the aesthetics (it's the right size and has that sort of matte cover that just feels nice - one of the reasons an e-book will never satisfy me), the lessons are clearly articulated and well demonstrated through creative and varied examples.

In Data Points, Yau focuses on data visualization as a medium, rather than a tool, and discusses the importance of context when figuring out what the right medium will be (which he argues can run the gamut, from the informative to the entertaining). Rather than a narrow focus on the visualization step, Nathan spends a good portion of the book discussing the data itself and strategies for exploring and analyzing it. One example used early on effectively was based on car crash data: he showed how you can aggregate in different ways to highlight different aspects of the data - the difference if you show hourly vs. daily vs. monthly vs. annual data, with discussion on the specific context that might lead you to choose one view over the other.

When it comes to visualizing the data, Nathan breaks it down into four "working parts" -

1. Visual cues - how you encode the data in things like shapes, sizes, and color; 
2. Coordinate system - Cartesian vs. polar vs. geographic;
3. Scale - linear, logarithmic, categorical, etc.; and
4. Context - clarifying what values represent, explaining how people should read your visualization.

There is a good deal of explanation on each of these to make the concepts clear. Yau refers to the above as the ingredients and describes putting them together to get a complete visualization worth looking at. He says,

"To make the jump from data to visualization, you must know your ingredients. A skilled chef doesn't just blindly throw ingredients into a pot, turn the stove on high, and hope for the best. Instead, the chef gets to know how each ingredient works together, which ones don't get along, and how long and at what temperature to cook these ingredients."

If I had to find fault in this book, it would be that Yau's discussion of context is mostly limited to the context of the data and helping your audience understand your visual, than about the broader situational context and helping your audience understand how the data fits into something bigger. For me, this is the storytelling piece, the step that helps make the data visualization relevant.

Still, it was an excellent read that I would recommend without hesitation. It's a thorough and accessible overview of data exploration, analysis, and visualization. For those already familiar with this space, it serves as a good reminder of some of the things we should make sure to pause and think about as we are working with and visualizing data.

I found the book to be such a great overview, in fact, that I will be using it as one of my required texts in Introduction to Information Visualization, which I'll be teaching in MICA's MPS in Information Visualization this fall.

You can purchase Data Points in the storytelling with data bookstore.

"animation" with power point

Let me begin this post by stating clearly that the only types of animation in Power Point (or substitute your presentation application of choice) that I endorse are: appear, disappear, and (sparingly) transparency. Please steer clear of any bouncing, flying, or fading in/out (as well as any other "slick" animations by which you may be tempted). To use an analogy, flashy animation is to presentation software as 3D is to a graph: unnecessary at best, and distracting at worst.

But that's slightly off topic. Today, I want to show you how you can use Excel and Power Point together with some simple screencasting with QuickTime Player to simulate a fully animated video.

When I solicited examples for a recent workshop, one participant sent me a graph they had created, along with this explanation:

This graphic summarized the key finding of the LAC (Latin America & Caribbean) middle class flagship we just launched. It is clearly not difficult to understand but my frustration was knowing that it could be more effective as an animated chart that could tell in a few seconds how far LAC has come. I tried to no avail to find someone who could do it for us. At the end, The Economist did what I would have liked to have done for our launch (link). 

Could we have done this ourselves? Or who could have done this for us and for how much? What kind of skills are required?

General consensus when I asked around was that The Economist's version was probably done using D3. I don't have any experience with this, and when I read the first part of the summary on the site ("D3 allows you to bind arbitrary data to a Document Object Model (DOM), and then apply data-driven transformations to the document." ...that's a mouthful!), my inclination to use tools more familiar to my audience was confirmed.

What I'll show you here should probably be considered a brute-force approach. There are certainly more eloquent solutions out there, but in case you aren't familiar with those (or don't have time or interest to learn the tools that would allow for them), this is a workable solution using good old Excel and Power Point, together with QuickTime Player.

My approach was to build the final graph in Excel, and then make a number of copies of it, eliminating some of the data elements from each so that I could focus on one component at a time to tell the story. Then I copied and pasted each of these into Power Point (making sure the visual was in exactly the same place on each slide). I pasted onto separate slides, so you see the progression as you move through them. You could also do this on a single slide with animation in Power Point (appear/disappear), which just takes a little more time and patience to set up. Patience is key throughout this process - it's a little painstaking to set up, but in the end I think achieves the desired result. Finally, after my slides were created, I used QuickTime Player to record my computer screen and voice.

Here's my resulting video:



The Excel file used to create the graphs can be downloaded here.
The Power Point file used to create the video above can be downloaded here.

This was my first time using QuickTime Player to create a screencast. I found it to be pretty straightforward; the instructions I followed can be found here.

Note how you could use this same approach in Power Point to focus your audience's attention in a live presentation as well.

200 words on infographics

Recently, I was asked to share my thoughts on the "future of infographics" for an article Arnie Kuenn was writing for the Content Marketing Institute. The words I shared with him are below; the full article, where four other experts weigh in with their thoughts as well, can be found here.

Infographics run the gamut, from fluffy to informative. On the former side, we are presented with elements like over-sized numbers and portions of filled in little man-shapes. The graphics appear glamorous and have a sort of sex appeal that draws you in. Unfortunately, upon further evaluation, these visual displays are often shallow and leave me dissatisfied. On the other end of the spectrum are infographics that actually inform; many of the good examples I’ve seen here are in the area of data journalism (e.g. Alberto Cairo’s work).

There are critical questions an information designer must be able to answer before they begin the design process: who is your audience? and what do you need them to know or do? It’s only after the answers to these questions can be succinctly expressed that an effective method of display that will best aid the message can be chosen. Good data visualization (infographic or otherwise) tells a story.

While I’m not certain what the future will bring when it comes to the landscape of infographics, my hope is that the trend will be away from the fluffy data-dump and towards visualizations that are thoughtfully designed to impart information and tell a story.

REMINDER! registration is open for upcoming storytelling with data workshops in San Francisco and Chicago: details can be found here.