What can we learn from eye-tracking? (resources list)

Amy Alberts and I hope you enjoyed our talk at #data17 about eye-tracking and what it can teach you about building better dashboards.

This post is a list of links and resources we talked about in the talk:

 

 

Future Media Forum, Moscow, November 2014

US Road Fatalities

US Road Fatalities (click to see interactive version)

I spoke at the Future Media Forum in Moscow this week. I was speaking about the key role data visualisation is playing in the media. I also showed Tableau Public to the audience.  This post contains the resources I used.

To follow me and keep up with updates, you can find me on Twitter: @acotgreave.

Here are the slides I used:

The images below are the dashboards I featured in the talk. Click the images to see the interactive versions.

Ebola: Illustrates trends

ebola

Hunger: Facilitates comparison

global hunger

 

French road mortality: hits close to home

french road deaths

Other links

David McCandless at #GuardianLive: thoughts

Data ? interconnected knowledge. Same as Atom ? Organism
Data ? interconnected knowledge. Same as Atom ? Organism (photo: Sophie Sparkes)

I went to see David McCandless speak at a #GuardianLive event tonight: he’s promoting his new book, Knowledge is Beautiful. In the past I have been critical of him: I’ve parodied his style, critiqued his work at meetups and madeover his vizzes.

It might come as a surprise then that I thought his talk was entertaining, inspiring, well-structured, well-meant and funny. I agreed with virtually everything he said.

I was very impressed with his new model for the pursuit of data-led knowledge. Raw data are the atoms. They become structured data (molecules) which become linked information (chromosomes). And so on to inter-connected knowledge (organisms).  David applied this model to the field of climate science and it fits. It’s a model I could use when talking to companies and journalists.

When talking about his motivation, it’s the same we all feel: all he wants to do is tell engaging stories with data and design.

McCandless focused on how he got into being a graphiste: accidentally. He was a programmer, then a journalist, then in advertising, and finally it all came together as a visual designer. This resonates with me. I never planned to get into dataviz, but my history as budding comic artist (I was young!), geographer, journalist, software engineer and database admin gave me the tools that, when data viz turned up, were all I needed to pursue a passion.

He’s also modest, funny and engaging as a speaker. He doesn’t preach his thoughts, he shares them. He doesn’t say his way is the right way, he just explains the way he does it and what happens when he does. His ultimate advice is to just get out and play with the data.

What then, are the criticisms? These days I measure a visualisation against Alberto Cairo‘s 5 values of visualisation:

Beauty? Yes. Insight? Yes. Enlightenment? Yes.

Truthful? Mostly. If you’ve ever seen Tim Harford dismantle Debtris (“Misinformation can be beautiful too“) you’ll know how hard it is to compare different numbers.

Functional? This has always been the most contentious for those of us who first learnt our craft from people like Stephen Few (who also has harsh words to say on the topic). McCandless’ charts are not designed to best align to visual perception. In so many cases, boring bar charts would be better if the aim is to aid fast comparison of values.

What I realized tonight is that there’s a problem trying to critique McCandless. I suspect his response to any criticism would be “Yes, you’re right. I’m just trying to communicate a story and somehow people seem to like the way I do it. I’m not saying I’m right. I’m not saying I’m the best. I just do it my way.”

As for truthfulness, he’d probably agree and say: “Every single data source is linked to on my site. I may not be wholly accurate but I am open with where I get my data.”

I do believe he needs some more practical advice for people who look to him not just for inspiration but for practical ideas of how to get started. Currently he makes it sound harder than I believe it is.

Where does that leave me? I used to be a disciple of the Stephen Few world, but am no longer so zealous. Data visualization needn’t be polarizing and McCandless’ motivation and humility earns my fullest respect.

100yrs of Data Visualisation: my talk from #data14

I had an amazing time delivering my session about Willard Brinton at the Tableau Conference. Today we made the recordings of the session available to people who attended the conference. If you couldn’t make the session, you can go here to watch the recording.

Along with conference session, I am on a mission to bring Brinton the fame he deserves, and am also cataloguing the amazing things he talked about in his book over on my tumblr, http://100yrsofbrinton.tumblr.com/.

If you coudn’t make it, I’ve uploaded the slides for you – you can see them below. Without the talk track, I fear they are not much more than just pretty pictures. Nice pictures, though.

Have you heard of Brinton before? Will you help me make him famous?

Note: the vintage office photos used in my deck are from the excellent Office Museum.

100yrs of data viz: and we’re still making mistakes – #data14 preview

Don't go overboard on your infographics
Don’t go overboard on your infographics

I’m off to Seattle next week for my 11th Tableau Conference. I’ve spoken at each one I’ve been to but have rarely been as excited about the talk I’m giving, and a new blog that’s going to follow.

The session: 100 yrs of data visualisation and we still make the same mistakes (Thu, 10.45am, room 6B)


Answer me this: who wrote the definitive book about effective data visualisation? Alberto Cairo? Stephen Few? Edward Tufte? They certainly wrote best-selling books. But they were late to the party.

In fact, the first, and I will argue, the best, book on effective data visualisation is 100 yrs old this year. That’s right. 1914. The year of the first commercial airline flight, the first skyscraper in Seattle, and first official Mother’s Day in the US.

 

We had all the answers 100 years ago.
We had all the answers 100 years ago.

 

Graphic Methods for Presenting Facts was written by Willard C Brinton.

My session is based around that book. We’re going to look at

  • how his guidelines for effective best practice are just as valid today.
  • how technology has changed but is always one step behind our imaginatoin
  • how society has changed but the need to share data hasn’t.

By the end of the session I hope everyone will be inspired to ensure that, in 100 more years, our great great grandchildren are visually literate.

The blog: #100yrsOfBrinton (over on tumblr)

Which map pin should you use?
Which map pin should you use?

In just one hour I won’t possibly be able to pack in everything there is to know. Today I am launching a new tumblr, 100 Years Of Brinton. Over the next few months, I’ll be posting snippets from the book. My hope is these will inspire and entertain you. The ultimate goal? For everyone, not just dataviz nerds like me, to know about Willard C Brinton’s amazing book.

I hope you come along to the session. If not, follow the blog, and let me know what you think using the hashtag #100yrsOfBrinton.

 

7 learning points from The Graphical Web

Last week I attended The Graphical Web in Winchester. Tableau were sponsors and I was lucky enough to get to spend time with the people at the cutting edge of open source web graphics. Here’s 7 things I learnt:

1.     Google’s maps are like leaves

http://commons.wikimedia.org/wiki/File:Grapevine_leaf.jpg
Leaf with “hierarchy” of veins (Wikipedia)

One key theme from all cartography sessions was that effective cartography (and, by extension, data visualization) is about taking out as much information as possible. Ed Parsons showed the iterations of Google’s maps as an example. In the past, Google feel into a typical cartographer’s trap of trying to show all the info.

Now, when you search, you get much less information. The colours are more subtle. Ed explained how they took the simplicity of a leaf as inspiration for their newer road network palettes.

2.     Circular diagrams can work

Click to see interactive version
Click to see interactive version

I’ve never really liked chord diagrams, thinking there is always a better way to show the data. Nikola Sander changed my opinion in her explanation of the migration data she works with. Not only was the transition from a table of numbers to a chord diagram visually appealing, I came to realize that I’m not sure there is a better way of looking at this kind of data.

Chord diagrams cannot generally be digested quickly, but once the user has trained themselves to use them, they are an effective method for complex data.

3.     You don’t need to be a proficient public speaker to be engaging on stage

jason davies

Jason Davies, co-author of D3 led the afternoon keynote. From a public speaking perspective, he session not great: not much structure, a bit hesitant, and Jason doesn’t always project his voice well.

So how come this was one of the best sessions of the conference?

Answer: because his work speaks for itself. What Jason has done is push interactive graphics forward with great humility. A showreel of his work is enough to engage an audience as he walks through one after another amazing piece of geometric madness.

4.     Twitter’s Visualisation Lab doesn’t sit still

Click to see the slide deck
Click to see the slide deck

Nicolas Garcia Belmonte led a fantastic review of the interactive work at Twitter (slides here). What amazes me is that his team comes up with such varied ideas. We often see teams have one or two great ideas and then overwork the same idea until it is no longer inspiring. One look at Twitter’s interactives page tells you this is a team with inspiration.

I get the feeling that these visualisations don’t get enough exposure outside the field of data visualisation. Do you agree? What can we do to change this?

5.     “It depends” is the only right answer.

The path to a successful design? (Tim Brennan)

Scott Murray’s talk “The Keys to a Successful Data Design Process” (slides) generated a good debate. How should you go about your design process? It depends. How should you design your chart? It depends. What data should I use? It depends.

This is something I’ve touched on before in my post on data storytelling: you can’t have rules or laws in Data Visualisation – everything depends on something else.

6.     Weather guarantees viral content

Earth: click the image to see the real thing
Earth: click the image to see the real thing

My favourite session was Cameron Beccario’s story of how he created Earth, the amazing live wind map of the globe. I love this kind of story: a project of passion that uncovered many many side projects and problems. It’s a story of data hunting, skill learning, and serendipity that ends in huge success.

7.     I had dinner sat next to a cannon.

The Gun Deck on HMS Warrior

That’s cool. Alan Smith and the Office of National Statistics did an amazing job organizing a great conference. I had been suspicious of the need to drive to Portsmouth for a good evening reception, but a tour around the harbor followed by dinner on the gun deck of HMS Warrior was amazing.

Terrific tooltip tricks: European conference session

Thanks for visiting the blog – if you are visiting here as a result of my Tableau European Customer Conference session, welcome along. The best way to keep up to date with new posts is via my twitter feed (@acotgreave).

My session was all about tooltips, and ways you can use them to enhance your visualisation and make your audience’s lives a lot easier. I have posts on various tooltip topics:

If tooltips aren’t your thing, then have a browse of the blog for other Tableau tips and tricks.

At the time of writing, the conference workbook I used isn’t yet available for download. Follow me on twitter where I will update everyone when it is put onto the Tableau Conference website. There will also be a video recording of the session should you wish to revisit some of the specific content.