Critique: Community influence
Today’s poster was sent in by kindly contributor David Selby. It was created for the useR! conference in Brussels earlier this year. Click to enlarge!
useR! poster: ranking influential communities
The main data visualization gives this poster a strong graphic element at its core. The visulizations almost look like abstract art. David did the right thing by making these as big as possible. You wouldn’t be able to interpret these otherwise.
David has skillfully mixed both a serif and sans serif font in the type in a way that is not distracting.
There may be a mild problem with reading order. Looking at the text, this was the pattern I expected to follow:
Instead, I realized that I was supposed to go like this:
In fairness, the acknowledgements can be skipped, so I don’t have to drag my eyes all the way back to the lower left. But still, I was confused when I realized that black of text was acknowledgement. “Wait, I’m not supposed to read this yet!”
David was very clever to link the “Web of Science” data and “Statistics” data using colour. But it still bothers me that the two “Statistics” graphs are spatially separate, rather than adjacent.
David has a brief blog post about the poster, and wrote:
David has skillfully mixed both a serif and sans serif font in the type in a way that is not distracting.
There may be a mild problem with reading order. Looking at the text, this was the pattern I expected to follow:
Instead, I realized that I was supposed to go like this:
In fairness, the acknowledgements can be skipped, so I don’t have to drag my eyes all the way back to the lower left. But still, I was confused when I realized that black of text was acknowledgement. “Wait, I’m not supposed to read this yet!”
David was very clever to link the “Web of Science” data and “Statistics” data using colour. But it still bothers me that the two “Statistics” graphs are spatially separate, rather than adjacent.
David has a brief blog post about the poster, and wrote:
One of the key things when doing the analysis was to keep everything reproducible. To this end, all code for the graphs and results is presented in a GitHub repository and vignette, along with the Scribus file for the poster itself. All software used was free and open source. Modulo the raw data, anybody can recreate the design and repeat the analysis for themselves. I also used the vignette to track my ideas during the design process and list some sources of inspiration, even though it’s not really relevant to the actual research.
Here is the poster on the board (photo: Oscar de León):
I am pleased to report that this was an award winning poster: first place (shared with two others, like the Nobels)!
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