On September 2nd, I attended an introductory workshop on some of the tools we use in the Digital Humanities (DH). The workshop was held via Zoom, with thirteen participants, including the instructor, Filipa Calado, and Rafael Portela, their helper. Filipa is a Graduate Center Digital Fellow and a Ph.D. candidate. She has been running these introduction workshops for a few years, but this was the first time she had done it remotely. The workshop was structured this way:
- Filipa did a brief overview of DH, stressing the collaboration is very important because most projects involve teamwork.
- We broke into small groups to introduce ourselves.
- Then we returned to the full group, and Filipa discussed the five areas of Digital Humanities (DH), some of the tools used, covered contextualizing methodology, and offered links to additional readings.
- We ended with an online evaluation.
We began with an overview of DH, including the use of the word “tool” in the computational sense and that DH brings these tools to its methodology. Generally, DH brings digital methods of research to the humanities, with most projects either producing data or processing data to organize, clean, manipulate, or transform it.
RESOURCE: Read Johanna Drucher’s article on “Humanities Approached to Graphical Display”, see http://www.digitalhumanities.org/dhq/vol/5/1/000091/000091.html
Where does data come from?
It can be audio/visual, web scraped (taken from other sites), text analysis (using programs), text encoded (tag it so the computer can read it), and geocoded (tagged to use with digital maps).
How do we capture audio/visual data?
When it comes to audio capture, begin by reading Kelsey Chatlosh’s blog post on their GCDI workshop on sound, see https://digitalfellows.commons.gc.cuny.edu/2017/10/10/kicking-off-the-gcdi-sound-series-a-workshop-on-sound/. Generally, open-source tools are recommended because they are free and have great support around their user-community.
This is when we use software to gather specific content from static websites and social media platforms. It is always wise to consider the terms of service on the sites you scrape.
This is when we use programming to extract the data we want from text. Examples like Word-clouds were shown.
This is when we use a mark-up language to encode a text for specific details. We reviewed in some detail how XML was used in the Shelley-Godwin Archive, including some pages from Shelley’s Frankenstein, which showed her text and her husband’s edits; see http://shelleygodwinarchive.org/.
These software tools let us make our own maps. QGIS is the most often used tool for this need.
We reviewed in some detail the work done by Mapping Arts NYC, which shows where cultural events are supported in the five boroughs over time using funding as its primary marker.
Displaying and Analyzing Data.
Some tools automatically create a display when given data. For example, spreadsheets can be used to generate basic graphs and charts. This implies an analysis. What do you show, and what do you leave out? Have a critical awareness of the tools you use.
Display / Analyze it: Visually
Some time was spent on the Quantifying Kissinger site, which did “A Computational Analysis of the National Security Archive’s Kissinger Collection Memcons and Telcons” and then presents this data in 3-D map form, see https://blog.quantifyingkissinger.com/.
Display / Analyze it: Narratively
Archiving platforms like OMEKA, the CUNY Commons CMS, or Manifold were cited as platforms that store digital assets and can also be used to present them.
RESOURCE: The Graduate Center Digital Fellows (GCDI) team can help you figure out what tools to use for a project. Visit their site and sign up for a consultation.
RESOURCE: Visit the GCDI calendar to learn about future events, see https://commons.gc.cuny.edu/groups/gc-events-and-workshops/events/
RESOURCE: Here is the link to their slide presentation: https://bit.ly/toolsfordh.
I learned a lot in a short time. Please do read their slide presentation, as it has links to all the tools mentioned.