Blog Post: Reflection on Data Visualization

What are the key features that make it stand out?

The blog provided a list of features that made it stand out from other figures and graphs. I think that its success in representing various information is similar to many other excellent figures and graphs, but the idea of ‘using the smallest effective differences’ is inspiring and outstanding. When making graphs I would usually point to things that are most important by highlighting them, but it could also distract the reader from understanding other content in the graph, thus either my graph would convey less data, or I would need to make another graph to put data in. Maintaining the balance of data is something I need to learn more about.

How would you improve on it, if you were to take a stab?

This is rather personal but one thing I could improve is to NOT rotate any of the numbers. I dislike turning my head 90 degrees to read those numbers and I think since the marks were rather small, rotating them is unnecessary.

Reflections on Visualizing Humanities Data

One thing to keep in mind in visualizing humanities data is that I should be communicating with my reader. This is to say that I should make all the details of my presentation more human-approachable and readable as possible. This might include the following:

  • Showing my purposes, an example would be if the ‘area’ of structures in the graph matters, I should not use bubble plots for entities since it’s hard to compare the area of circles, especially when there are other circles between them.
  • Lessening the work of my reader, for instance, sometimes I have to use color coding for different entities, and I should ‘attach’ a color to each entity and keep the colors consistent among multiple graphs.
  • Remembering that I conveyed more than data. As mentioned in class, the choice of font (serif versus sans serif) affects the feeling of the reader. More generally, every detail matters and contributes to the representation.

2 thoughts on “Blog Post: Reflection on Data Visualization

  1. I think it’s interesting how you mentioned highlighting important points and how sometimes that may translate to making another graph altogether. It reminds me of our discussion with Lin and how sometimes overlaying graphs (like the NYT pandemic graphs) can overwhelm viewers, rendering the presentation ineffective.

  2. I also think the numbers on Minard’s map were pretty difficult to see, now that you mention it. I didn’t say this in my post, but if I could change another thing on Minard’s map, I would make those numbers a bit bigger.

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