Cómo crear infografías online. Discussion: Storytelling and success stories. I’ve not been able to keep up with all threads but it seems there have been a number of interesting discussions over the past few days covering various aspects of the role of data visualisation and what we should expect from it. Thought I’d join the party late and throw in a few thoughts of my own as I was planning on writing something about these subjects anyway. Firstly, I would recommend you take a look at Moritz Stefaner’s post about the different functions of visualisations – those that tell (or more specifically show) stories and those that don’t.
I particularly suggest you read the comment responses at the bottom of the post, I haven’t read them word-for-word but skimming through reveals some good discussions in there. Interestingly, you can see how often the nuances and semantics of the written word are at the root of many disagreements about perspectives when they are actually the same views just articulated differently.
The main issue is what does success look like? Best of the visualisation web… January 2013. At the end of each month I pull together a collection of links to some of the most relevant, interesting or thought-provoking web content I’ve come across during the previous month. If you follow me on Twitter you will see many of these items shared as soon as I find them. Here’s the latest collection from January 2013. You’ll see that I’m trying out a new structure in response to recent (and, to be fair, historic and avoided!) Feedback: Includes static and interactive visualisation examples, infographics and galleries/collections of relevant imagery. Creative Bits | Annual repots become infographics BitAesthetics | Paul Butler introduces a new way of looking at and visualising flight options New Scientist | Global view of warming temperatures, let’s you see how things have changed over time in a location of your choosing UX Blog | ‘People dots: Seattle area commuting’ – More magic from John Nelson.
FastCo Design | ‘How A Civil War Vet Invented The American Infographic’ Seven dirty secrets of data visualisation | Design. Data visualisation - and in particular, web-based data visualisation - is having its moment. JavaScript libraries like D3.js, Raphaël, and Paper.js, building on modern browser support for Canvas and SVG, have made it easier than ever to produce complex visualisations that, until recently, were the province of computer scientists and a handful of specialist designers.
Visualisation is the new 'must-have' element in project proposals and personal portfolios, and startups like Platfora, Datameer, and our own employers ClearStory Data and Chartio are raising millions for analytics platforms with browser-based visualisation interfaces. To some extent, the buzz is justified. Data visualisation is a wonderful way of exploring data, finding new insights, and telling a compelling story.
Secret #01: Real data is ugly Most data visualisation tutorials start with a pleasant fantasy: a pristine data set. Tools and strategies Budget significant time in any visualisation project for data cleanup. Reflections of a Newsosaur: Most newspaper stories are still too long. The news cognoscenti gasped when the Columbia Journalism Review recently reported that the nation’s leading newspapers aren’t writing as many long stories as they used to. But I think most stories are still way too windy. In a moment, I’ll tell you why, as briefly as I can. First the background: Tallying yarns topping 2,000 words on Factiva, CJR found the number of long-form stories at the Los Angeles Times dropped by 86% between 2003 and 2012.
In the same period, stories of similar heft fell by 50% at the Washington Post, 35% at the Wall Street Journal and 25% at the New York Times. “When it comes to stories longer than 3,000 words, three papers showed even sharper declines,” said CJR. The number of super-sized stories dropped everywhere but the NYT, which actually had a 32% increase in articles of 3,000 words or more. Back in the day, words often were the only way to tell a story. Now, in the interests of brevity, I will stop. The “art” of compromise: Is there room for compromise in designing data graphics? | viewtific. In my last post, I discussed how expectations and perceptions of designers are as important to quality data visualizations as are more conventional resources, such as time, people and money. But there is also a flip side to this–there are times when, as designers, we may be faced with a choice to compromise on how we present data.
The compromises we agree to–or reject–are as important to our field as anything else. (Kudos to me for resisting the urge to title this “drawing the line in infographics.”) A friend related to me a recent conversation in which an art director who, when presented with a bar graph of extreme values (very high and very low), asked the designer to “fudge” the size of the smaller bars. (They were visible–not hairline–but too small to comfortably fit the values inside of them.
But, once I calmed myself down, it occurred to me that this might be something interesting to write about. Here’s what came to mind after my conversations with other designers. My point?