Workshop one of a two-workshop series for graduate-level English students. Find part two here: https://www.slideshare.net/gesinaphillips/data-visualization-through-network-graphing-100293824

1. Creating metadata for
data visualization
CRAFTING AN ARGUMENT USING DIGITAL TOOLS

2. https://io9.gizmodo.com/rappers-ranked-by-vocabulary-size-v2-0-1615347822

3. Sources as data
Often, digital scholarship methods apply to primary sources in familiar ways:
 Collect
 Transcribe
 Organize
The preparation and presentation of underlying data, however, is where digital
scholarship methods are unique:
 Visualization
 Text analysis
o Mapping
o Network analysis
o Distant reading

4. Distant Reading
A researcher can read and analyze a single text more effectively than any
machine
A computer can “read” and recognize patterns in 100 books (or other large
corpus) far more efficiently than a human
Each method will reveal different connections and patterns, and yield different
results*
Examples:
 Mark Algee-Hewitt: The Performance of Character
 Micki Kaufman: Quantifying Kissinger
 New York Times: Clichés of ESPN
* For a different perspective see: all ongoing debates regarding the nature of the digital humanities
What is distant reading?

5. Moretti, F. (2003). Graphs, maps, trees: Abstract models for literary history—1. New Left Review, 24, 67-93.
(Presented with apologies)

6. Quantifying Kissinger

7. Mapping
Does what it says on the tin
Example: marking all the locations in a book or set of letters and mapping them
Goal: to find patterns of (re)location or illustrate movement that is otherwise
difficult to see
Examples:
 Vincent Brown: Jamaica Slave Revolt
 Mitch Fraas: Mapping the State of the Union
o See also: The Language of the State of the Union

8. Mapping the State of the Union

9. Jamaica Slave Revolt

10. Network Analysis
Finding and visualizing connections between people, groups, movements, etc.
Goal: to find influential people or actors who may not otherwise have been
noticed
Examples:
 Chris Warren, Daniel Shore, Jessica Otis: Six Degrees of Francis Bacon
 Chronicle of Higher Education: Who Does Your College Think Its Peers Are?

11. What is distant reading?

12. Six Degrees of Francis Bacon

13. Data in the humanities
All of these example projects required the collection and organization of
underlying data
Traditional humanistic research employs qualitative analysis to bring sources
into conversation or to conduct close reading of a primary source
Digital humanities methods use quantitative methods to enable, supplement,
and/or enhance humanistic inquiry, and to offer research outputs that constitute
visual/interactive arguments
Data visualization is not an end in and of itself—it purports to tell a story, make
an argument, or explicate hidden information

14. An introduction to
metadata

15. Metadata!

16. Metadata!

17. Biographical data
Name
Date of birth
Place of birth
Date of death
Place of death
Country of origin
Etc.
Metadata!

18. Brief network context (more next time)
Nodes: people, objects, or concepts
existing in some sort of relationship
Edges: connections between nodes

19. Metadata workshop

20. Metadata
Notice that the data dictionary is very specific about the language and
punctuation in some fields. This is because “not only are computers as dumb as
a billion marbles, they’re also positively Stradivarian in their delicacy” (Ford,
2015).
For example: to Palladio, 01/10/1990, 01-10-1990, and 1990-01-10 are
completely different and irreconcilable concepts
Other fields are set to controlled vocabulary options (look at Relationship to
Loy) in order to limit the number of possible responses
Certain fields direct you to include commas and/or semicolons between
elements; this will make data cleaning easier down the line

21. What stories do these data tell?
What do they simplify?
What do they leave out?
What are the implications of the choices
made in order to organize the data?

22. Coming soon:
Data visualization using Palladio
Gesina A. Phillips
Digital Scholarship Librarian
phillipsg@duq.edu