In my last post we left off pondering what digital humanities are and how — especially in higher education — advanced cross-sections between the written word and digital technology are creating new areas of study in the humanities.

The field is in fact not as new as one might imagine. In the 1940s pioneering Jesuit scholar Dr. Roberto Busa, intended to study the concept of presence in the writings of Thomas Aquinas. In the process Dr. Busa concluded that, “philological and lexicographical inquiry into the verbal system of an author has to precede and prepare for a doctrinal interpretation of his works”.

Having succeeded in his analysis by hand (producing over 10 000 handwritten cards), and successfully defending his thesis in 1949, Dr. Busa nonetheless continued to advance his correlated theory that deep textual-research required machine assistance. Through a long and interesting journey (a delightful read) Dr. Busa finally convinced IBM to assist him in creating the Index Thomisticus — a replete digital concordance (an alphabetical list of the words present in a text, usually with citations and context) of the works of Thomas Aquinas.

Dr. Busa is quick to acknowledge that the idea of using computational machines in this way was not his own, but he is typically regarded as the progenitor of digital humanities, as his gargantuan efforts did indeed create the first digital artifact within the humanities academy.

Since then the field has all but exploded, as technology advanced, and humanities scholars became ever-more adept at blending technology and textual study. With this explosion has come an enticing word cloud of concepts. I thought the best way to produce a quick 101 introduction to the topic of digital humanities, was perhaps to design a concordance of our own, although in fairness it is more like a terminology.

Digital humanities in Higher Education

It is worth mentioning, before we dive in, that digital humanities and its key proponents, value what might be described as “The better angels of the internet”, (apologies Dr. Pinker). DH (Digital Humanities) places strong emphasis on openness, self-criticism and reflection, projects tend to be iterative and rely on crowd-sourced research, and using freeware and commons license tools.

Digital archiving

At its most fundamental level, digital humanities rely on access to raw digital archives of original source materials. Scanning, capturing, digitizing and storing ancient texts, original manuscripts, artworks, sketches, drawings, notes, letters and a variety of other documents is the work of a great many public, as well as private institutions. Good examples of reliable digital archives include the Library of Congress, Fold3 or The Old Time Radio Network.

Curating online collections of primary sources (primarily textual)

Another primary function of the digital humanities is to curate cross-discipline collections, relating to aggregating and indexing primary sources (both archived — as above and what in DH circles is called “born-digital content).

Quantitative analyses

As can be expected, qualitative analyses in the humanities is a foregone conclusion — seeking historical, biographical and sociological context with which to interpret a text is essential to the study. However taking a more data-based approach, and mining texts for repetition, references and patterns can in and of itself, as Dr. Busa’s doctorate revealed, be as illuminating. A good example of such work is the The Council on Library and Information Resources (CLIR) tool building and analyses project mining the largest and most continuous transcript archive of public hearings at The Old Bailey in London.

Big Data visualization

Ever-advancing graphical and analytical technology makes visualizing big data sets increasingly more useful and in-depth for scholars. In fact the sheer act of collecting, inputting and managing the data in this way affords scholars unique opportunities to see and evaluate the data. Stanford has a number of active data visualization projects that will no doubt prove to have interesting results.

Topic modeling

Practically a blend between quantitative analysis and visualization, topic modeling yields a schema of how certain topics (statistical word clusters) are treated, repeated and interrelate in any given text. Topic modelling assisted historian Sharon Block to “read” huge swathes of the Pennsylvania Gazette, discovering for instance that the topic of “runaway slaves” occupied 5.6% (the highest) topic ranking in the editions studied by the software.

Keep an eye on the NEO Blog!

The field of digital humanities continues to advance not only the development of more accurate digital humanities tools, but also yields an increasing variety of niche subject areas. Fascinating subsets such as media theory of composition, that establishes the literary and cultural effect of using new technologies to compose art, or critical code studies that approach studying code, as one would study literature, seeking elegance, artistry and expression in how code is written.

I think that there are many ways that K12 teachers could, and already are, using these wonderful tools to add dimension and interest to their history, literature, culture or EFL courses. I’d like to take a more narrow view next time, and share with you examples of how digital humanities are being practiced in a K12 environment. So keep an eye on the NEO Blog!

Stay in the loop! We’ll keep you updated with the most valuable EdTech tips and resources. Subscribe and never miss out!