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The problem with infographics

Submitted by Anne Odling-Smee
From introduction at the British Library Data Visualisation event
28 February 2013

I’m a designer – the type that used to be known as graphic designer before the internet effectively kiboshed the term – but broadly speaking I deal with communicating information. In 2011 I set up my second design company with 3 other colleagues called DesignScience, largely in response to some of the issues around visual communication we’re discussing tonight, and because I come from a science family. Alongside this I’m a part time teacher on a new course called Communication Design at Central Saint Martins. It was through this I realised the full extent to which my industry is responsible for the ‘public’’s usually very forgivable misunderstandings around data interpretation.

My main concern is with information conveyed by scientific data. The ability of people to understand science largely depends on their ability to interpret data correctly and their ability to understand the processes of science. But for all of its relevance and natural appeal to humans and to children who want to understand how their world works, scientific data are often widely misunderstood.

The most obvious reason for this is that although scientific data are factual, assuming they are based on accurate observations and measurements, their interpretation is always provisional, probabilistic and hypothetical. Science can never offer absolute certainty. Non-scientists often misunderstand this point.

Humans struggle with uncertainty, and designers in particular typically yearn to make order out of chaos due to the organisational nature of their work. Uncertain information is more difficult to communicate than are fixed data. The desire of designers to ‘clean up data’ and make them look beautiful at the surface level can corrupt the underlying message the data are really communicating.

Beautiful ‘info-graphics’ like these [not pictured here] are exactly the type scientists can’t stand, and rightfully so. I’ve spent many a tutorial scolding students in my objection to these self indulgent and ultimately useless outputs! But the desire for aesthetic beauty is very dominating.

As any mathematician will tell you, beauty doesn’t exist only on the aesthetic level, but equally on a conceptual level. The principle of form following function is imperative for effective design communication, but as an industry we need to get much better at prioritising content over appearance. Only then will we realise that fixed info-graphics may be the least helpful means of communicating science.

The possibilities of programming are far more promising when it comes to tackling the challenging issue of communicating uncertainty. Through programming (which we actually believe could be a shared language between design and science) recipients can participate with their data without that data having to be cleaned up, so enabling them to really understand what it means.

But it’s not just designers’ fault that they are struggling to know how to communicate science. Design as a profession didn’t exist until 60 or 70 years ago. Now we’re pandemic, as the information age provides ever-growing demands for dissemination of data of all kinds.

Design courses are situated within art schools through an assumed affiliation, based on our traditional routes which are now long outdated. This encourages a tendency towards aesthetic- rather than content-driven solutions, and students graduate believing that it’s quite OK to make things look good even if the content is at best unintelligible, at worst misleading, or even fraudulent.

This affiliation with art causes confusion both amongst designers, and amongst anyone wishing to employ our services. 90% of conversations I have with scientists who I am introducing to DesignScience don’t go anywhere until it’s been understood that designers are not artists, and that we need have no more to do with art than with any other subject.

Design can only communicate a subject when the designer sufficiently understands the subject. This can only be achieved if the design and subject specialist understand each other. In my view communication design courses should be situated alongside schools of all subject matters, in all countries, so by being in the vicinity of those subjects we could learn how to communicate them.

Designers coming out of art schools today are poorly educated about science so don’t know how to work with scientists. At present scientists don’t find designers useful and don’t understand their potential usefulness. For this reason designers and scientists aren’t working together. My students are only 5% British so this may be a global problem. It comes down to a long-embedded science vs arts split in education that seems to happen in schools in many countries.

Our aim at DesignScience is to start rectifying this by a) showing what design can do for science through projects, publications, workshops and events, and b) encouraging a generation of design students to learn how to work with science and scientists so as to be able to provide a useful resource that is so desperately needed, showing that data CAN be informative, as well as look beautiful.

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  • Martin Krzywinski, Circles of Life, 2013 (© Martin Krzywinski) Martin Krzywinski, Circles of Life, 2013 (© Martin Krzywinski)