Introduction to Digital Humanities

Data Visualization

This week we will examine some of the promises and pitfalls of visualizing humanities data with the end goal of making big data accessible and meaningful to broad audiences. 

Annotation #6

1.Johanna Drucker, “Humanities Approaches to Graphical Display,” Digital Humanities Quarterly 5, no. 1 (2011). http://www.digitalhumanities.org/dhq/vol/5/1/000091/000091.html

2. Catherine D’Ignazio and Lauren Klein, Data Feminism (PubPub, 2018), Introduction https://data-feminism.mitpress.mit.edu/pub/frfa9szd/ and Chapter 2 https://data-feminism.mitpress.mit.edu/pub/ei7cogfn. Make sure to annotate with hypothes.is and not the platform's (PubPub) custom commenting feature.

Assignment #6

Find a humanities dataset a build a simple data visualization with TableauRaw Graphs, or Morph . (For this assignment you can, but do not need to, use Miriam Posner's Tableau Tutorial.) Embed your visualization on your "Assignment #6" page and discuss what your visualization tells you that you couldn’t see from the data itself, why you selected a particular visualization tool, and how you might relate and/or interpret your dataset and visualization in light of the assigned readings. 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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