The “Look at data” section was informational in explaining the effectiveness of data visualization. The reading explained the importance of the different styles of charts and how each type of visualization has its strengths and weaknesses. It is important to think about the user’s accessibility and experience when designing visuals for data and the numerous variables that impact these decisions.
A few interesting points that stood out were the sections on the axis and color value. “Our ability to scan the “away” dimension of depth (along the z-axis) is weaker than our ability to scan the x and y axes.” For this reason, it is difficult to incorporate 3D elements into our graphs and the angle of the chart (which is used to show the perspective of 3D) can be misleading in delivering the data. Another interesting point was how people perceive brightness. The same shade of gray is perceived very differently depending on whether it is against a darker background or a lighter one. We are also better at distinguishing darker shades than lighter ones. The interaction also differs based on the scenario: “We will do better at distinguishing very light shades of gray when they are set against a light background. When set against a dark background, differences in the middle-range of the light-to-dark spectrum are easier to distinguish.”
Overall, it is important to think about the conciseness of the visuals when creating a chart. The type of chart must be optimized to the data being delivered and the visuals must be simple enough for the user to easily understand (junk-free), while also delivering honest information.