Lauren Manning, a New York based designer, explores various methods to visualize one single data set for her thesis. The data at hand is as basic as it gets: food consumed and has been gathered from two years of meticulous life documenting. She describes her reasoning behind the project as follows:
“It’s like comparing apples to oranges.” This phrase is the best way to describe the current state of data visualizations. For the designer, its easy to find good visualizations and bad ones, but how to apply the successful elements of particular designs to one’s own data set starts to get a little more complicated. Data sets vary tremendously, so one man’s brilliant solution can be another’s complete failure. Instead of seeing many excellent visualizations of all different data sets, what if you could see tons of visualizations of the same data set? What new comparisons, knowledge and structure might be developed from this?
The matrix above was installed as part of the thesis presentation and organized the different visualizations from simple to complex on the x-axis and from literal to abstract on the y-axis. The idea of the matrix is create a live space for comparison and contrast of the different methods of visualization. Instead of viewing the individual charts one at a time, this overview helps to create a truly effective comparison.
During the presentation, Lauren asked the viewers to actively participate in her research. By filling out what she called Experience Cards a viewer could document their interaction with the installation by marking which visualization they see first, look at the longest, think is most effective and this is least effective.
As her thesis is not fully published yet, we have to wait for insights into how the different visualizations performed and what conclusions she takes away from her research.