Part 3: Analyzing and Critiquing Data Visualizations :
1) Coronavirus Data Dashboard: The presented data is readable. Each circle is an activity and the risk level varies from low to high in getting the virus based on that activity. Increased size of the  circles and  color change of circles should be clearly marked in the representation, because it is not. However, one could conclude a increase risk level based on change of the size of the circle and the change in the circle color as well. This could be something one could extract as a conclusion based on a perceived recognized pattern. I am personally not a fan of the structure of the graph and will probably only remember a few selected items from each risk level. 
2) Based on a *True* True Story: Its colorful. It does not tell you how many sciences each movie has, just how much as a percentage the movie is historically accurate. The only movie that was accurate was Selma. Since it was the only 100% and Th big Short was the only one in the 90's then it will probably be the only two I will remember. The movies wee not broken down by percentage in descending or ascending order. No were the movies in alphabetical order. Either of these two would be good for the structure of the representation. 
3) Best in Show - What’s the best Dog Breed: The intelligence was hard to read read from the graph. the quadrant titles were biased in my opinion (Example: Rightly Ignored, Overlooked Treasures"). Categories of why these does were chosen in the data set were not mentioned. The data's purpose is not meant to extra future or predictable information. No real explanation as to the number of non-sporting doge being inexplicably overrated. To much information in the graph and I did not see the reason for choosing the particular breeds to each data set. I have mixed feelings on the readability of the graph. I think the author was trying to do two much, which can overwhelm his audience.

Catalyst Notebook