Welcome back to the recap series for Real World Fake Data. This time we are looking at work submitted for the Citizen Service Request dataset.
Before I dive in, I want to take a moment for a bit of housekeeping.
First, I want to thank everyone for participating. You’ll notice that we are playing fast and loose with the timing of new datasets. We polled the datafam and saw that overwhelmingly people are busy (and trust us, we know!) so we are going to continue to let the project ebb and flow. But, I want to thank the folks who are continuing to pick up the older datasets and contribute their work! I even saw a couple of Viz of the Days coming out of the RWFD datasets; AMAZING! Thank you for your continued participation in the project, Jacqui and I really appreciate it!
Alright, for CSR we had three that we wanted to highlight.
The first came from Varun Jain. (Link to Viz)
There are a lot of things to like about this viz. I like the layout that moves from left to right; first looking at the management and then moving into more detailed visualizations. I like the consistent use of color regarding the classification of the request type. There are two elements I’m not crazy about. The first is the row banding on the table. When I first looked at it I thought the row banding was changing the color of the bar at the end (which I didn’t realize was a bar until I scrolled down). I might have opted for a lighter row banding, or maybe I would have removed it completely. The second is the near reuse of color. for the Year over Year indicator is Red and Blue, which are also the colors of the Emergency and Standard request types… so when I look at the bar in the table it could potentially cause some confusion.
The next one comes from Elisa Davis (Link to Viz)
When I think about something for the general public, this is the direction I would lean. Simple, clean, and easy to understand. Focused on what is overdue, a bright teal color is a nice contrast to the black of the requests within the SLA. The one thing here that I’d question is the bubbles. It’s hard to judge the size in these cases, and while it’s easy to see what’s bigger, the actual scope of the difference is hard to judge. Also, by using a different chart type, the user has to cognitively reorientate themselves. A cool alternative might have been a 100% stacked bar chart? The truth of it is that no chart is ever 100% correct, it’s all design trade-offs.
The last one comes from Pawan Sachdeva (Link to Viz)
First of all, if you are going to emulate a style, you can find no better role model than Ellen Blackburn in my book. When it comes to business dashboards, she’s the first one I will generally reference. You did an amazing job with your inspiration and execution while making it your own; Beautiful work!
I can’t really see anything I’d change here. It’s clean and clear. The simplified color palette is sharp and the visualization choices are spot on. I’m a big fan of marginal histograms, so I love the inclusion of that here in this use case. The detail table and the filter toggle are nice finishing touches here as well. Bravo.
The next dataset will come out in October, and the rumor is it will be a collaboration with another community project, so stay tuned!