EO Applications and Visualisation

I’m concluding my trio of conference blogs by focussing on Earth Observation (EO) and visualisation.

Within the data visualization session at ESA’s Living Planet conference Planetary Visions Limited gave a great talk entitled ‘Presenting Data and Telling Stories’. They highlighted the importance of knowing the audience that you’re communicating with, particularly the difference between presenting data to the general public versus fellow scientists.

The key element of communication to remember is that it’s only complete when the recipient understands the message. Scientific figures are often presented using a colour palette, which is applying artificial colours to black and white images (the rainbow palette is shown below, going from low values being purple / dark blue to high values being red). These enables scientists to easily extract values and get a detailed view of the results. Fine for scientists who understand this principle, but for anyone who doesn’t they may not understand the data presented or even worse may draw incorrect conclusions.

Rainbow Colour Palette

Rainbow Colour Palette

To make data widely understood, it needs to be presented in a way that makes it immediately clear what is being shown. This means that sometimes you need to focus only on the overall message, and sacrifice elements of the detail that allow the extraction of values, differences and trends.

Infographics is the on-trend term for the visual representation of complex data in a chart or graphic, so it’s quickly understood. There’s recently been an explosion of software, and websites, offering to create infographics for you. However, infographics aren’t new. A long running example is the London Underground Map; it isn’t a precise map of the tunnels, but it gives everyone the information they need to use the underground.

The key to a good infographic, and other graphs and charts, is keeping it simple. Focus on the information that you want to convey, rather than graphical embellishments. Edward Tufte argued in ‘The Visual Display of Quantitative Information’ that graphics should be assessed in terms of the data-to-ink ratio, such that the data should be presented with the least amount of ink.

Look at your figures and ask yourself whether the axis, grid lines, legends, numbers, borders or any other of the fancy bits in PowerPoint add anything to the image; or do they make it more confusing and less understandable?
Next time you have present, don’t just pull out the presentation you gave to the other conference last month and think it will do. Think about who is going to be listening to you? Will they understand the data as you’ve presented it? If you don’t think they will change it!

Scientists need to think about visualisation of data, as well as the raw data, if it’s going to be understood by more than those who created it. Data becomes information when it’s presented in a context that makes is useful. Always turn your data into information; your audience will thank you!