Interview: Mitchell Whitelaw & Geoff Hinchcliffe (Part Two)

Published:  February 28, 2013
Heath Killen
Interview: Mitchell Whitelaw & Geoff Hinchcliffe (Part Two)

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.

Experimentation and and prototyping seem to be at the core of data visualisations, generative art, and emerging technologies such as 3D printing. As educators as well as a practitioners, I’m wondering how you go about encouraging your students to embrace failure and to be adventurous in their work?
MW: Connecting students with a culture of practice is one way: the whole “creative code” scene is blossoming, and along with networked “maker” culture in general, it celebrates openness, process, and experimentation. So there are plenty of great models for students to look to – people like Karsten Schmidt, Jer Thorpe, and Stamen.

GH: That focus on process means that experimental works are seldom a failure, in the same way that a negative result in a science experiment can be productive. Knowing why something doesn’t work can help you understand the important characteristics of a successful piece. The emphasis on making is another theme that I think really resonates with graphic design. Like the “creative code” scene, graphic design as a discipline understands that production is not simply a means to an end but an important creative act requiring significant expertise. Given this common concern with making, it’s not surprising to find that there is a good representation of graphic designers amongst the creative code scene.

MW: I also encourage students to build on all the knowledge they bring from outside this little field – whether they come from architecture, visual art or graphic design. Building on strengths, and treating digital techniques as ways to augment or extend students’ core knowledge, helps maintain students’ confidence, and that is crucial for adventurous work.

Where do you draw inspiration for your own work from?
GH: There are two primary principles that inspire much of the work we complete: exploration – providing people with the tools to explore datasets in rich and engaging ways; and discovery – revealing exciting new perspectives of a data source.

MW: “Inspiration” seems to be a whole industry on the web; there’s this torrent of design and creative work coming past us every day. I find it pretty hard to take, actually – a bit suffocating. Data, on the other hand, is reliably inspiring and intriguing: at its best, it’s an alien world, a complex mystery or a code to crack. As well, data is a great way of puncturing the bubble, because it often comes from a whole other context: whether it’s a museum collection, or climate records, it brings its own conventions, questions, debates and significance, and that stuff is fascinating.

Weather Braclet by Mitchell Whitelaw. 365 days of Canberra weather data was collected, and input into the open source software Processing followed by 3D modelling suite Blender to create this design.

Weather Braclet by Mitchell Whitelaw. A wearable piece made from 12 months of Canberra weather data (July 08 — June 09). The outer edge is daily temperature data; the holes are weekly aggregated rainfall. 3D printing by Shapeways

In terms of that process of discovery, how do you go about defining a purpose or context for a new project?
MW: Stamen have a motto that I love – “doing the next most obvious thing.” It’s a very self-deprecating statement for a firm who are leaders in this field, but it makes the point that often, here, we are joining the dots – taking data, techniques, conventions and ideas that are already lying around, and putting them together. Innovation isn’t a radical leap into the unknown, it’s a more workmanlike process of learning and experimentation. That takes technique and intelligence, of course, but for adaptable designers this field is wide open. There’s a lot to do.

In practice, every project comes with constraints and contexts – from partners, from the data, from the techniques or tools, or from my own research questions – often all at once. Getting the work right is a matter of finding the “obvious” response to those constraints.

Twitter Physics by Geoff Hinchcliffe. Once authorised, this project uses your Twitter stream to create a generative visualisation.

Twitter Physics by Geoff Hinchcliffe. See this project in action (along with others) here —

How does one make design choices or set aesthetic parameters for generative projects?
MW: In some senses it’s very traditional – the brief, or the context of the work, provides some constraints or parameters, and the designer hones in on something interesting, or challenging. The difference is that generative design will actually encode those constraints into a computational process – so the result isn’t a single solution, but a sort of machine that represents the problem and proposes some responses. That’s not to say it takes over from the designer, or makes choices for them; the idea that generative design is “automatic” is only half correct. A generative system is a machine that enacts human decisions and choices.

GH: Patterns are incredibly significant in design. We see it in the way that graphic designers constantly appropriate and recontextualise to create new interest, and in most cases that process of reinvention is highly intuitive. For me, a really interesting aspect of creating generative works is transforming intuitive design sense into explicit form – dissecting and codifying the aesthetic qualities of a graphic composition. It sounds cold and analytical but it’s actually very natural to graphic design – grids, styles guides, templates, they are all attempts to codify graphic aesthetics. Generative works just go the extra step of automating the rules – instead of relying on a human to enact the rules, we employ a machine to do the work. Obviously, that requires a much more fine-grained definition of the rules.

The term “generative” has a lot of connotations and can seem quite alien to designers, but if we include some more familiar forms under the generative umbrella it becomes easier to understand what the term entails and how designers might contribute. For example, a webpage template is generative; it is a system designed to adapt to a constantly changing set of data and display parameters. The designer of a web template must address both practical issues to do with the quantity and qualities of content, and aesthetic concerns regarding its presentation on screen. In terms of the aesthetic parameters, they will be guided by the genre of the website, its audience and a host of technical constraints. While the precise form of each page cannot be predicted, it is not entirely random either. That is really the crux of generative aesthetics – working within ranges rather than surrendering to complete randomness.

Tweet Report by Geoff Hinchcliffe. Once authorised, this online software provides a comprehensive report of all Twitter statistics. See this project in action (along with others) here —

Generative typography by Mitchell Whitelaw, used as logo for Whitelaw's Master of Digital Design course at University of Canberra. Grow your own here —

Do you see tension emerging between independent, open-source platforms and proprietary, cloud-based technology? The later seems to becoming an increasingly dominant force, at least in the mainstream.
MW: It will be an ongoing arm-wrestle, and the two will continue to coexist. Many of us will continue to sign up for shiny corporate monocultures, but open source has certainly changed the whole playing field. The ethos of open source, if you follow it far enough, is pretty interesting, but also quite challenging for art and design.

GH: The line between open-source and commercial software is actually quite blurry. More important than the price of a software application is the culture of production that it supports. The bigger issue here is not necessarily the brand of software tools that a designer uses but the application of open-source concepts to all forms of design. It’s easy to talk of open-source when its someone else’s software or music, but it’s worth reflecting on how it applies to one’s own work. How can we produce work that can be shared freely without eliminating all commercial opportunity? The music and movie industries have shown that simply clinging to old distribution models is not the solution. There are some interesting times ahead for all design industries.

Where are things headed in the immediate future for data visualisation?
GH: I predict data visualisation becoming a normal part of graphic design practice. Data viz cannot be considered a special case, something to be ignored or left to others to deal with. Data is a constant in our society and its significance is only increasing. It’ll take a bit of work for graphic designers to become completely comfortable with the practices of data representation but as they do I think we’ll see data being used more commonly and creatively – something that I look forward to.

Read Part One of this interview here.

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One Response

  1. Very interesting subject.

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