Reading Post 7 — The Truthful Art Chapter 12: On Creativity and Innovation
In this chapter, Cairo discusses ways to introduce creativity and visual innovation into graphics in order to catch the eye of the reader, while still proving enough annotational content to inform the reader on how to view the graphic. He discusses how most American adults are able to read scatterplots due to the nature of visualizations in media and news. No matter how uneducated you think your readers might be, most of them can still understand graphs and visualizations, and it’s important to provide explanations on how to read graphics if you doubt their ability to understand the information. Cairo also talks about the usefulness of annotating transitions and the importance of describing and accurately annotating visualizations in news publications. Interactive multimedia storytelling, as the book calls it, is another method I think is highly engaging and effective for the viewer. Overall, visualizations, especially those published in news content with multiple other stories, bust be engaging and readable in order to get the viewer’s attention and produce understandable information. Making a visualization interactive and personal for the viewer is another good way to gather attention and keep it.
The two graphics in Figure 12.21 (Wind Map) and Figure 12.22 (Flickr Flow) caught my attention immediately when reading this chapter. They are stimulating, engaging, beautiful, and clearly take a new visual standpoint when displaying data. These types of visualizations make me wonder, as does the beginning of this chapter, about the importance of showing specific data trends, data points, and correlations in the annotation layer of a graphic. The two visualizations mentioned above, Wind Map and Flickr Flow, are aesthetically appealing and innovative, but they don’t really show specific data points or values. In science, by contrast, chart designers make a point to show axes, trend lines, and data points in a very numerically clear manner. My field of work is in communicating science to the general public using media, technology, and, of course, visualizations. I was talking to my boyfriend recently — he is getting his PhD in plant biology, so he is very much scientifically-minded and that is apparent when he is designing charts and graphs — and he was telling me about the importance of including correlation variables in scientific graphs (the image attached below is an example). Here, the r value numerically demonstrates the correlation, whereas in charts like the Wind Map and Flickr Flow, the correlation or specific value of data is more abstract.
I wonder about the usefulness and importance of including specific correlation and variable data in scatterplots…most general audiences might be able to read scientific scatterplots, but do they require seeing that r variable as well? Can they even understand that r signifies the exact correlation value? I appreciate the beauty and innovation of visualizations like Wind Map and Flickr Flow, but I also realize the importance of showing statistic correlation in order to prove a point or message, so I wonder how these two factors can be balanced and how variables like r and p can be numerically presented to viewers that may not have scientific backgrounds.
