Assessment
I enjoyed how Kieran Healy discussed the successfulness of a visualization in terms of visual perception. In the past, I’ve done some reading on how to determine if a visualization is “satisfactory.” However, in those conversations that I’ve come across, the deciding factor centered on if the reader acquired information and knowledge from the piece. I found it interesting to read about the connection between principles of visual perception and visualization adequacy. While valid and important, I always felt the former was quite hand-wave-y—a way to give an answer to something without actually giving an answer. This felt like it dove deeper into the mechanics of how the visualization process works.
In those previous readings, there was reference to developing a form of criticism for visualization, similar to art criticism*. The four outlined rules to this still-hypothetical criticism didn’t include mention of these visual perception techniques.
Additionally, I liked how this discussion of visualization adequacy was framed early in the chapter by addressing audience differences. I think this is a critically important (and seemingly overlooked) aspect of visualization, a consideration that should occur early in the process as it shapes later steps.
Bringing in the pieces by Carl Bergstrom and Jevin West, I liked how this collection of readings attempted to integrate definitional taxonomies with visualization conversation. I feel the field—the journalism corner, in particular—is growing rapidly, I think it’s important to include precise language in these foundational discussions as it allows for concrete discourse and critique, which is all in hopes to push the evolving field forward.
Questions Raised
As visualization discussions progress alongside visualization education, I’m curious how we address this seemingly slippery slope of creating misleading and deceptive output? There are so many intricate details to consider when designing a visualization while so many tools are so openly available: how do we help ensure solid visualizations are published in the community while also being critical of what’s already there? Do we teach it earlier in the classroom?
I felt as if a lot of the bad examples were testaments to why packaged software isn’t particularly apt for data storytelling, appearing in support of more flexible programs such as D3 that allow a designer to have control over more aspects of a visualization (and I may be biased because I’ve wrote papers on this, haha). Do others feel differently? Does it matter on the audience? On the stage in the visualization process? What the visualization is meant for?
*R. Kosura, “Visualization criticism: The missing link between information visualization and art,” 11th Int. Conf. on Information Visualization, July, 2007.