Bang Wong hits the nail on the head early in our conversation on how the collaboration of art and science might benefit scientific research.

"The topics are so broad that it's hard to get your head around them," he tells Information Age.

But he's been on a mission to bridge science and art over a number of years, and that mission has brought him to Australia as part of the Vivid Festival in Sydney where he's speaking about "visualising the future of biomedicine" at the Garvan Institute.

It's by no means unfamiliar territory - Wong's a medical illustrator and the current creative director of the Broad Institute of MIT and Harvard, which prides itself on breaking ground on techniques to research and present the findings of biomedical science.

He's also the founding author of the Points of View column published in the Nature Methods journal, which - over a number of years - has given scientists insight into how they can tweak the way they visually analyse and present their findings.

For Wong, it's not about creating visual masterpieces with science data, but it is about knowing enough to make "graphical choices about how to represent data in the hopes of bringing out the right types of patterns for that scientific need".

"I don't think it's a high bar," Wong tells Information Age. "We're not asking scientists to be a Monet or Matisse with colour theory, or to draw for likeness."

Wong sees benefits both for the researchers and eventually the public consumers of that research if work can be presented in a visually-appealing format.

"I think visual representation is the currency of science communication," Wong said.

"In slide presentations, in publications and in other mediums, you never see published scientific work without a lot of plots and figures."

Creating those visuals is likely to involve some form of design trade-offs, and Wong is particularly interested in simple design decisions that can make a big difference to the visualisation of research.

"In my experience researchers just tend to reach for colour because it's the most familiar thing, but colour comes with a bag of issues," Wong said.

"With colour I think there's some insufficiencies with just the 'hardware' we have, for example. We have fewer short wavelength cones to see blues than we do reds and yellows, so if we were to show subtleties of the data in blue we wouldn't be able to see it as much as we would in another colour range.

"So even making a colour choice could be supported by physiological reasons for doing it."

Other trade-offs in the visualisation of scientific data might be necessary for legibility.

"I think as a researcher there's an allure to having all the data all at once because it represents the richness and complexity of the space," Wong said. "But I think as humans there's a cognitive threshold there to be able to understand everything at once."

Wong suggests using an interactive UI to abstract detail, while still allowing the underlying data to be drilled into, should that level of detail be required.

"One approach is to roll up the data and abstract it progressively to higher views," he said.

"With each level of abstraction you'd probably lose some detail of course but you probably gain a different perspective on the data.

"And if it's an interactive UI, you're able to abstract up, get a broad overview, but then dig back down to the detail as part of the data experience."