Notes from Malofiej 20 speakers: visualization, truth and beauty
It’s a packed schedule at the University of Navarra in Pamplona, Spain, the site of Malofiej 20. Speakers on the first day focused on data visualization, comprehension of infographic forms, the process of making graphics and more. Here are highlights from some of the sessions.
Andrew Vande Moere
The tyranny of the pixel
Andrew Vande Moere, associate professor at the Department of Architecture, Urbanism and Planning of the University of Leuven in Belgium, talked about how our perception of data has changed and how the idea of information overload is reinforced because we take in virtually all of our data in a singular way — through a screen. Through pixels.
He showed examples of ways people can understand information in a more “calm” way, using different senses, such as the sculpture of a car’s CO2 emissions that took up actual space, puffing out of an actual car, a USB drive that fattens up when it gets more full and an installation that represents demographics with different piles of rice, each grain representing a single person. The pile of XX billion Australians was quite large whereas the grain representing Tony Blair was a single grain.
His studies concentrate on how some of these methods can be used to change behavior such as a speed limit sign that shows a driver’s speed, thus causing them to slow down to the limit, or various ways of showing a household’s energy consumption.
Showcase of data visualization techniques
Andy Kirk is a freelance data visualisation design consultant and trainer based in the UK. Founder and editor of the website VisualisingData.com. He outlined a process for understanding and executing data visualizations.
With the exploding popularity of Big Data, Kirk focused on how to go about starting and executing a data visualization emphasizing the importance of having a clear goal and idea, spending time to understand and perfect the data and iterating during the design process.
He outlined these steps:
- 1. Identify the purpose of the data visualization
- 2. Identify the questions you aim to answer
- 3. Acquire, explore and prepare the data
- 4. Conceive the visualization
- 5. Construct and launch
A few of the examples Kirk showed: