Digital Humanities: Humanities research in the digital age - training sessions scheduled

The OOC DTP are pleased to be able to offer a number of training sessions to accompany the newly developed online course in Digital Humanities

These sessions are open to 1st and 2nd year OOC DTP students, who will have completed the online course before the training commences. Please book this training via Inkpath.

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Dates: 9 - 10 February 2021

Session Resources: 


Access to:



“Distant reading” has become a common buzzword in the area of Digital Humanities, but what does it mean to read texts with the help of computers? Is the human(ist) reader relinquishing control to a machine or using it to uncover details that are otherwise invisible? This workshop will introduce participants to the main issues and debates on computer-assisted text analysis. Participants will also consider critical perspectives on the use of digital texts and the tools currently available to study them. No knowledge of programming is required and participants will be using tools accessible from their internet browser for the practical component of the course, including the Voyant and CLiC online platforms.


Session Plan:

9 February, 10:00 - 12:00: Introduction and main session

9 February, afternoon: 2 hours of independent study

10 February, 10:00 - 12:00: Second session and final Q&A


Dates:  2 - 4 March 2021

Session Resources:

Web browser to access Recogito 

The Recogito tutorial:

Texts or images (copyright-free) supplied by student for own practical exercises



This workshop will introduce students to the area of Spatial Humanities, the application of geospatial perspectives to the study of the Humanities. The workshop will provide an introductory overview of Spatial Humanities methodologies and tools, with a focus on semantic annotation of places, people and events through the award-winning Recogito platform. Participants will reflect on the benefits and limitations of Spatial Humanities approaches and on their application to their own disciplinary area. No knowledge of programming is required and participants will be using tools accessible from their internet browser for the practical component of the course.

Session Plan:

Preliminary work (1 hour): Read the Recogito tutorial and register for the site

2 March, 10:00 - 12:00: Introduction and main session

3 March, afternoon: 2 hours of independent study

4 March, 10:00 - 12:00: Plenary


Date: 6 May 2021

Session Resources:

Students will need to sign up in advance of the session for a free Internet Archive library account. Information will be provided upon registration.



Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected source texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding key issues they are likely to encounter and developing practical methods for delving into massive digital archives.

Session plan:

In the first half of the training there will be a short introduction to massive digital archives, a challenge task to complete followed by related critical input and discussion; the second half will be a hands on workshop in which participants work through a sequence of tasks to test out different ways of using the search capabilities.



Date: 13 May 2021

Time: The training will comprise of two live sessions of 1 hour with time for self-directed learning and lunch in between. Session 1 is 11am – 12 am, session two is 2-3pm. The time between the sessions is a required part of the course where students will be working on a small project of their own which they will present and discuss in the final live session.



Machine vision systems can potentially help humanities researchers see historical and cultural image collections differently, and could provide tools to answer new research questions. This session provides an introductory overview of basic tasks in machine vision, such as Image Matching, Comparison, Classification, Captioning, Object Detection and Facial Recognition within a critical framework highlighting the challenges of algorithmic bias and the limits of automation as a method for humanistic enquiry. Students will have the opportunity to explore some demos developed by the Visual Geometry Group at the University of Oxford and create a small image-based Machine Learning project using Google’s Teachable Machine platform which will explore the challenges of applying machine vision to historical document collections. No prior knowledge of computer vision or of coding is required to follow the session.