I was very intrigued by the drawing data visualizations that were presented in the Bowe article such as the “Know the Symptoms of Coronavirus” diagram, the flowchart, and the “How is New York Changing” diagram. What particularly struck me about these diagrams, as I pointed out in class, was the personal and human aspect of them. They no longer take the all-knowing/god’s eye view/omniscient perspective. Instead, they are from the perspective of personal experience and individuality–they speak to the “self”. Possibly, because these types of visualization are more engaging and personal, people are more likely to respond and take the necessary action, as oppose to when looking at a highly scientific and impersonal bar-graph. But at the same, I can’t help wonder if these more seemingly playful and relaxed visualizations (about an in fact very stressful and serious issue) may take away emphasis on the severity of the pandemic and cause people to have a more care-free response instead. Is it possible for a data visualization to be too personal or too human? Is there some way to combine the hard-lined seriousness of a graph visualization and the playfulness of a flow chart to make a data visualization that highlights the immense gravity of an issue such the pandemic, but also has a more personal/individualistic bent that speaks to the human and is calming and socially accessible? I am trying to think if we’ve come across a visualization in our class thus far that I think has both of these qualities. Possibly photographs as data visualization are effective in this regard. By showing a representation of reality, there is an implied seriousness in that this type of data visualization shows an affect on people in their daily life, but at the same time, there is something more personal about seeing a photograph that depicts a reality that an individual can relate to.
Maya, this is a great question. We don’t know enough about how people make sense of data visualizations and feel them. This is definitely a great topic for ethnographic research. Perhaps that data vis that Rei and Lauren shared is one good model for bringing together the personal with the abstractness of big data.