Who doesn’t like a good data visualisation?

Co-founder of IIB creative studio David McCandless gives us his thoughts on where data visualisation is now and where it might be heading

In this age of info-overload, condensed, visualised information cuts through the noise, helping us quickly understand, navigate and find meaning in a complex world. It reveals the invisible patterns and connections in the seas of data around us. It’s memorable, impactful, enduring and funky. What’s not to like, writes David McCandless.

But there’s a lot of it out there. Along with its bed companion, Big Data, dataviz is a rising trend across many disciplines: journalism, science, marketing, business, digital. Everyone’s at it. The scene is wild and unbridled in its creativity, good, bad and ugly. So how do we find and honour the good stuff?

This was a question I was exploring when approached by Kantar’s creative director, Aziz Cami, in 2011, to form an infoviz awards. I’d been playing with the idea of instigating ‘creative challenges’ with cash prizes on Information is Beautiful to help support and inspire fledgling practitioners. Creative challenges and international prizes seemed like a good marriage. The IIB Awards were born. The vision? To exhibit and celebrate great data-visualisations and infographics from around the world.

(What’s the difference between ‘data-visualisations’ and ‘infographics’? In my view, a data visualisation is a singular visualisation of data. So bar graphs, pie charts, scatterplots are all data visualisations. And so are the cooler forms like treemaps, network diagrams, and bubble maps. Meanwhile, an infographic is a collection of multiple visualisations exploring a theme or story. Think: ‘scrolling tower infographic’.)

Though they often look simple, neither forms are easy wins. To pull off a good information visualisation, you need skills from both sides – information and visualisation. So you need visual skills like graphic design. But you also need information skills – concepting, factual research, storytelling – commonly known as ‘journalism’. But this is ‘data journalism’. That means using data as a source, and using computational techniques like mining, scraping and statistical analysis to find your stories. So the art of visualisation is combining and harmonising design thinking, statistical rigour and storytelling without compromising any element. No mean feat. It’s no surprise then that infoviz is a difficult and time-consuming form with a high failure rate. The successful ones deserve to be celebrated!


Innovative it may be, but historically, infoviz is not new. There have been several waves. Back in 1854, Florence Nightingale was rendering polar grids to try to convey to her superiors the scale of preventable, infection-related deaths of soldiers in the Crimean War. In the 1930s, Otto Neurath and Gerd Arntz developed the pictographic based visualisation-language IsoType. And, if you’ve got ten minutes, Google ‘vintage Victorian infographics’ images. You will be amazed. All these movements simmered for a while, but then faded.

My hunch is that these previous waves lacked a medium to convey visualised information. And their audiences weren’t fully trained to receive them. Today, we’re accustomed to the marriage of design and information. From road signs to news graphics to websites to apps – the two now go hand in hand. Information design literacy in the general population has never been higher. We all expect and demand information to be visualised. And that demand is being met. Big time.

Big Data

Another strong factor is the rise of Big Data – another buzz term that has various meanings: the huge load of data we have lying around these days; the combining of multiple, varied data-streams into singular ‘big data’ sets and the process of managing, analysing and discovering insights, patterns and other ‘gold’ in huge datasets. Visualisation is a very quick and direct way to find and surface meaning in data. It’s also a great way to polish your leaden data into a shiny spectacle to present to your clients, customers or investors … just saying.

This shininess, combined with the pure imperative to do something – anything – with all this data, has part-fuelled the rise of infographics and drawn business dollars into the scene. The largest company in the world, GE, funds the dataviz challenge website Visualizing.org. Mega market research company Kantar sponsors the Information is Beautiful Awards. Google and Facebook have data viz divisions. Other companies are circling.

But the biggest boost to data viz was the revelation that it needn’t just be applied to boring old business data or snorey scientific statistics. You can apply it to everything. There’s data everywhere now. Pop culture, music, web stats, research, surveys. It’s not a big step to imagine everything as data – even your life, your movements, your moods, your diet, your bus choices, your bowel movements – all this data can be harvested, processed and baked into beautiful information graphics.

The scene

The current data viz scene is a constellation of various sub-scenes. Loosely: data artists, data journalists, information designers, creative coders and business intelligence wonks.

Studios show the expected concentration in the UK and US. New York is the home of influential data-tracker Nicholas Feltron, the always impressive, ever dynamic New York Times graphics team and their former data-artist-in-residence, Jer Thorp (at blprnt.com). Other outfits like HyperAkt and Guardian America soak up the business. West Coast sees outfits like map-savants Stamenamong popularist shops such as Column Five, JESS3 and Pitch Interactive.

Globally, Italy is a major hotspot. Practitioners like Accurat Studio, Density Design and Francesco Franchi have developed and promulgated a distinctive ‘Italian style’ of infographic. Coarsely: a high-brow, intellectual topic flowingly visualised on a sepia background. Franchi’s recent book, Designing News (Gestalten, £45) sets the tone, exhibiting much of his work for the Italian business paper Il Sole 24 Ore and its magazine Il, both passionate dispensers of infographic work. We’ve also seen other mainstream activity in France, Russia and Germany.

Infoviz’s recent, unexpected re-emergence has generated a unique side-effect: a truly level playing field. Individuals, small freelance outfits, studios, and in-house teams all compete, communicate and collaborate in the same mind space and market. Individuals have a chance to score big with homebrew projects and can land global clients. Pro teams have to be nimble enough to keep up with tech innovations and aesthetic standards set by prolific ‘amateurs’. Hackdays and cash prized visualisation challenges allow unknowns to spike big. Many winners go on to start their own shops or get snaffled by giants.

This freewheeling cuts both ways. Incredible uninhibited creativity alongside wastelands of dross. Low grade work sluiced out by infographic sweatshops as typified by the garish, empty linkbait ‘tower infographic’, scrolling eye-vomit pumped out by soulless marketeers.

The process

Upvoting and viral physics usually ensure that the best work surfaces. But the best leveller of all is the difficulty level. Infoviz is creatively challenging and difficult to pull off. The synthesising of data, story, and design is a very difficult brew.

It’s not just the labour, the research and the refining. Each graphic takes days and weeks of work. It’s also tough on the mind. The cognitive load is high. There’s lots of thinking. And lots of different types of thinking: logical and computational, creative and imaginative, design and colour, narrative and story, structure and flow. It also has a high fail rate and is highly iterative. There’s much whittling down through doubt and failure, trying to find the ideal expression of the data. Often, entire routes become too ‘spaghetti’ or ‘high concept’ and have be sacrificed.

Personally, I think infoviz has some built-in error correction. Because the raw material is information and the sought-after affect is ‘understanding’, ignorance and confusion become useful guides. In my process, if I don’t understand something, that’s the thread I follow. If I’m confused, I work to clarify the data. If I still don’t get the data, it means something is missing.

I bounce around these feelings like a pinball, until, eventually, there’s a sensation of things snapping into place, and a clear path emerging. The painful birth canal section of the process can be particularly long. But finally, it harmonises and breaks suddenly. Each element – information, story, design – sliding into place like overlaid opticians’ lenses.

So after all that labour, you have something that is enduring in the mind of the viewer. The easier a complex article is to read, typically, the longer it’s taken to write. It’s the same with the infographic. The simpler the graphic, the more hours have gone into it. Audiences can regard visualised information as they might a painting or a landscape. Take it in. Explore it with their eyes. Drink in the information. It’s relaxing. Enjoyable. But that’s because you as the designer have done all the processing, all the hard work.

You need a strong concept to survive this tough-ass process. The infoviz scene may revel in new techniques and wazzy interpretations, but the graphics that punch through and go viral – and many winners of this year’s awards – are often the strongest concepts, embodying the techniques of good journalism. That is, sharp or interesting ideas, with a provocative or topical hook, told well. Many of the highest trending datavizzes of all time are ugly but interesting.

The fails

Many of the fails you see in this work are familiar. On the journalism side: banality, poor ideas, lack of insight, too much information. On the design side: garishness, over-design, or scant data polished into ‘chart junk’.

Good practice is policed on the scene by dedicated purists and zealots of good design or good data pratice or, worse, both. My work at Information is Beautiful is routinely hosed by passing purists, upset that I’ve used bubbles or chosen not to clearly label an axis. Among this group, there is a strong aversion to decorative colour, pictograms and design touches. They are seen as frivolous impediments to the conveyance of data. Functionality is prided here. ‘Data ink’ is a concept from legendary visualiser Edward Tufte to describe the elements of an image that impart essential information. Anything ‘non-data ink’ is at best, pointless, at worst, a crime against the cloth. Author and dashboard design expert Stephen Few is the high priest of this sect, regularly issuing edicts and lambasts. But then, what’s a scene without a little drama?

The goods

Despite the occasional tension, the overall vibe of the scene is of creative adventure and excitement and potential. Much is unestablished. New work appears every day. Studios are popping up all around the world. The community is warm and active. A great set of blogs led by FlowingData, Infosthetics, and the literally endless Visual Loop stoke the fire. Bustling conferences such as New York’s Visualized event and the Eyeo Festival in Minneapolis sport warmly supportive and applauding audiences who savour the joy of this (somewhat) lawless frontier.

It’s into this party that we wanted to bring the Kantar Information is Beautiful Awards, in order to celebrate and honour the best work. It’s been a lot of fun.
There is a feeling that infoviz is a new way to communicate. In a world where everyone is reading information – emails, texts, websites, status updates – there’s a refreshing novelty to seeing information. It can be relaxing and enjoyable again to learn something or be informed. There’s potential in education, science, even psychology. Many realms could be unlocked with visualisation. People could understand stuff again.

Aside from the utopia, for practitioners, the specificity of this form means other work is always useful: for inspiration or for theft. So the whole field becomes like a single, rich self-fertilising moodboard, a garden of data-visualisation flowers, continually sprouting from a ground soil of infinite data. What’s not to like?

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