Miranda Kalbach

Good Example

Source: http://www.gannett-cdn.com/experiments/usatoday/2014/11/arrests-interactive/

I think this is a fantastic visualization! First, the spatial data is shown on a map of the entire United States (overview). Then the user can drill down (zoom) and look at the state level, then further down to look at each county. What's interesting is that at the upper levels (national and state), the user can see the overall level of disparities in arrest rates between races. It made me think of the activity we did in class, when we were asked to pick out the red circle and the line between the sets of shapes; both these activities and this visualization engage our pre-attentive processing with the use of color. As a result, we are quickly able to see the counties where the disparities are highest.

The rates of disparity are continuous and represented with four different colors, one for each category of disparity. The rates of arrest are being compared to that of Ferguson, Missouri; smaller, larger, or equal to Ferguson. However, I'm not in love with how the spatial data is shown in this visualization. Why show the roads and the waterways if they're barely visible? Once the user gets down to the county level, they are able to see the rates of arrest based on race (details-on-demand).

Bad Example 1

Source: https://www.learnalytics.com/wkar/

I'm not a fan of this visualization for several reasons. First, the use of a line graph for the students and the Tukey box plots for the postsecondary and adults seems a bit misleading. For students in grades 1 through 12, why aren't there ticks across the X-axis so that we can see the numbers per year, instead of just over time? Additionally, clumping together college and career doesn't make sense to me; the readings are going to be extremely different between these two groups. And how were the specific book and journal categories selected for adults?

My other issue comes from the stick figures. Why are they there? Upon my first look, I was trying to differentiate between gender (because of the figures and the use of two colors). It took me a minute to realize that the colors weren't connected to the figures. Additionally, the figures seem unnecessary and distract from the message. They would have been better if we were looking to compare differences in reading between genders. Overall, I fail to understand exactly what this visualization is trying to convey, and I wouldn't be able to remember much except that there seem to be more articles read than books.

Bad Example 2

Source: http://www.nytimes.com/2015/10/11/us/politics/wealthy-families-presidential-candidates.html?ref=politics&_r=0

This visualization is supposed to show us...I'm not actually sure. The donor families are represented by the red dots, but they aren't identified. Furthermore, each of the dots are the same color, so the viewer can't tell if the money is going towards the Democratic or Republican candidate. I think it would have been more effective a monochromatic color scheme was used, and the states with more donor families were darker than the states with zero or one. This would look cleaner and would show the data in a way that engaged with our pre-attentive processing.

I'm also confused as to why Hong Kong is included in this visualization. It is clear that this is a biased visualization, but I don't think it achieves much of anything except for showing that many donors come from large cities.

Botanical Tree Visualization

There was a lot going on in figures 12 and 13. First, linear perspective makes it so that objects that are further away are smaller. However, this seems to make the smaller branches seem insignificant and difficult/impossible to see. It makes me wonder if the larger objects are more important, or if it is based on my perspective of the 3D visualization.

Another thing that is throwing me off is the use of shapes. From far away, like in Figure 12, the pyramid shapes on the spheres appear to be flat spots. This is misleading, because there are some spheres that really are covered with flat spots of color. I wonder if it is possible to actually use too many elements that stimulate the pre-attentive processing? Here we have size, color, and 3D depth cues, to name a few of the pre-attentive features. In Figure 13, I was unsure if one of the branches was dark green as a result of the shadow, or whether it was meant to be that color. Finally, there is not enough contrast between all of the colors; the yellow is too close to the green in the branches, and the blue against the green hurts my eyes.

I have neither given nor received aid while working on this assignment. I have completed the graded portion BEFORE looking at anyone else's work on this assignment. Signed Miranda Kalbach