When they aren’t riding their bikes around the hills of Canberra, Mitchell Whitelaw (MW) and Geoff Hinchcliffe (GH) can be found teaching, researching, and digitally tinkering at the University of Canberra. Mitchell leads the Master of Digital Design, teaching data visualisation and generative design. His research investigates data as a creative material, from climate records to cultural collections. Geoff runs the Graphic Design program. He conducts practice-based research into interface aesthetics and emerging forms of computational graphic design.
How do you explain the concept of data visualisation to a novice?
MW: A data visualisation is simply any visual representation of data – and data in turn can refer to anything from weather patterns to Facebook friends. It can come in the form of an Excel chart or an artwork. We are interested in a continuum of practice here – between the prosaic or functional and the highly poetic. Data visualisation and infographics often get lumped together, but there is an important distinction between them – infographics are fundamentally exercises in visual communication, getting a message across. Data visualisation can be more exploratory and open-ended; visualisation can be a tool for discovering structures and patterns in complex data.
GH: In some respects “representation” is a better word than visualisation because data works can take forms other than the visual. In addition to graphics there is lots of interest in data installation, modelling using rapid prototyping technologies, and audio representation is a well established field in its own right. That said, graphics remains one of the primary areas of activity, not only because it is such an effective form for data representation but also because of the sheer quantity of screens that we surround ourselves with.
What are some of the primary uses for data visualisations today?
MW: Traditionally data visualisation has worked with static datasets such as census results or scientific measurements. In these cases the context and function of the data and its representation are quite well defined. But today – in the West at least – we live in data; every email, every tweet, every photo, every song is data. Data no longer comes in small, neat tables but in massive, endless flows and streams. So the applications for data visualisation are as endless as those data streams; and if this is our new everyday, the texture of our times, then design has a huge role to play. Digital data is invisible – it’s just abstract patterns and structures – but how it is represented is crucial to how we understand and interpret it.
GH: Probably the biggest application in data graphics at the moment is in personal analytics, visualising aspects of a person’s everyday activities – from how far they’ve jogged, to how much they’ve eaten, or how much fuel they’ve used while commuting. There is a narcissistic element here but on the positive side, awareness of behaviour helps people to alter their habits – get fitter, eat healthier, drive economically. The Nest thermostat is a clear illustration of how some very clever design can transform the potentially mundane topic of home energy usage into a seductive, game-like activity.
What about some of the speculative applications that the industry is leaning towards, or that key practitioners are pushing at?
MW: The scope for new work here is huge. In emerging areas like eHealth data representation is going to be crucial, and there will be clear functional imperatives. At the same time in the cultural sector and the humanities, digitisation is bringing incredible new resources online. How do you represent a digital collection of 50,000 museum items? We will continue to see data-driven work in a whole range of genres, from functional visualisation to fine art, as well as branding, industrial design, lighting, and so on.
GH: Many of the most speculative works simply find innovative ways to exploit the wealth of opportunities that already exist – we have immense amounts of data and a constantly increasing quantity of amazing technologies to work with. BERG have produced some wonderful works whose innovation lies in using familiar technologies in novel ways - printing a customer data viz on a conventional printed receipt is a good example. There are huge opportunities and genuine need for creative thinking about not only what we visualise but how.
What are some of the fundamental skills that one requires to start making sense of data, before even thinking about how to translate the data visually?
GH: First and foremost, you need to be curious. The most fascinating data visualisations give us unique insights into a dataset. To make discoveries you have to be keen to do some digging.
MW: One is an appreciation of structure; data is always an interplay of structure and variation. Designers in general are pretty good at structure, and seeing creative opportunities within formal systems. Another is the ability to approach data critically – to ask where it comes from, who made it, and why, or what’s missing.
How important is an aesthetic sensibility when it comes to creating data visualisations?
GH: Data viz has traditionally been a highly pragmatic functionally focused discipline and it’s great that we’re at a stage where we can discuss notions of aesthetic sensibility and even beauty. It demonstrates that there is a growing recognition that data viz can be more than prosaic, that it can surprise and delight, or even challenge an audience. Whatever the intent of a visualisation, it is clear that simply providing access to data is not enough and that it needs to be represented in ways that are culturally significant to an audience – that is where aesthetic sensibility is essential.
It’s important not to set beauty and functionality in opposition or as separate entities. It’s not a process of creating a functional chart and then styling it to look pretty. Like in any form of graphic design, data graphics require a designer to really engage with the content and gain a deep understanding, and then bring that to bear in the design of their graphic work. In the case of data viz that means designers need to develop a data literacy to be able to interpret and creatively adapt a data source.
What can your research offer to other design disciplines, such as graphic design, industrial design, and architecture?
MW: I use “digital design” to describe computational approaches across all these fields. There’s a lot going on in all those areas, but what is most interesting at the moment is the way techniques and concepts can move between them. There are shared, digital languages and cultures that are permeating all those disciplines. In our research and teaching, what we are trying to develop is a smart, skilled-up approach to that digital language, which can be applied in architecture, motion graphics, or publication design – and whatever all these fields turn into, next year.
GH: Despite the fact that all design disciplines are largely computer-based, most are tied to narrow conceptions of computing defined by a small selection of software packages. We want to liberate designers from those limits and help them to use the computer more creatively within their practices. Digital design does not have to mean software as the inevitable outcome – print, packaging, products, screen-media, models or even full scale architectural structures can all be produced using the digital design practices.
What are some of the applications and uses that you’re seeing emerge for governments, schools, and cities?
MW: The whole public sphere is increasingly – for better or worse – a digital space. As Dan Hill’s wonderful essay The Street as Platform shows, this isn’t some sort of perfect, rational state of seamless functionality - it’s a patchwork of data, protocols, and power. The same is certainly true of government and education. So if this is our world, this digital space, it will need a lot of designing. How that data is represented and how we interact with it, as well as, crucially, how how we contribute to it. Again, there’s a lot to do.
GH: The clients that most need the services of digital designers are those with the largest quantities and complexities of data – government is at the top of that list. Our particular proposition to large organisations such as government agencies is that their problem is as much about cultural translation as it is about access – making data available is a big step but is meaningless unless that data can be presented in a way that engages the community. Data viz is not a mechanistic act of illustration, it requires skilful, adaptable, creative practitioners to build those culturally engaging forms.
Enjoyed reading this feature? You can find more like it inside desktop magazine. Take a look at this month’s subscription special.