Introduction to Digital Humanities

Data Visualization


How can you make big data accessible and meaningful to broad audiences? In Histography.io, embeded above, Matan Stauber provides us with one answer to this question by visualizing 14 billion years of history, from the Big Bang to 2015, so users can access and make sense of Wikipedia as a whole.

Keeping this example in mind, we will examine some of the promises and pitfalls of visualizing humanities data.

Annotation #6

1. Yau, Nathan. Data Points: Visualization That Means Something. Indianapolis, IN: John Wiley and Sons, 2013. Chapters 3 and 4. Hypothesis link.

2. Johanna Drucker, “Humanities Approaches to Graphical Display,” Digital Humanities Quarterly 5, no. 1 (2011). Hypothesis link.

Assignment #6

Use the dataset that you cleaned in the last assignment from the Powerhouse Museum to build a simple data visualization with Tableau, Raw Graphs, or Morph doing your best to adhere to the principles Nathan Yau lays out in Data Points.  Embed your visualization on your "Assignment #6" page and discuss what your visualization tells you that you couldn’t see from the data itself, and why you selected a particular visualization tool. Be sure to follow the instructions on the "Assignment" page of our workbook to make sure that it shows up in the contents of your personal page and the "Assignment #6" page. 

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