Since October 1, 2022 I am back at the University of Vienna, where I started with the Master's program Digital Humanities (DH for short).
Since digitalization is having a lasting impact on many areas of science and society, I thought this degree would be perfect for me to become an accessibility specialist, since screen reader users in particular benefit from digital content.
Over the next few months, I'll be updating you on what classes I'm taking, what I'm learning in class, and how I'll be applying what I'm learning to my goals.
Courses for this semester
I will participate in three courses. Let me give you a quick overview what these are about (copied from the course catalogue), their aims, contents and methods.
1. Introduction to DH Tools and Methods
The course is aimed at providing students with the skills necessary to understand the sheer potential of the digital methods for the humanities, using the Python Programming Language for a handful of common tasks in the domain.
The course will present a broad overview of methods and tools, specifically covering the following: OCR & Natural Language Processing (NLP) Pipelines, Visualization & Dashboards, Spatial Analysis, Image Analysis, Social Network Analysis (SNA), Sentiment Analysis, SQL and NoSQL Database Management.
2. Telling Data Stories - Diagrams, Graphs, Maps and other visual and physical representations of (research) data
The visualization of (humanities) research data by means of different tools and forms of representation is an essential part of the Digitial Humanities.
The aim of this course is the elaboration and critical reflection of different forms of representation of (humanities) research data. By means of a practice-oriented approach, we will get to know different tools for data visualization (e.g. QGIS, Palladio, R, Python, etc.), test them, and check the resulting representations for their suitability.
In doing so, we want to ask together what constitutes a "good" visualization, what significance data visualizations have in the (humanities) scientific knowledge process, and how narratives can be told with data.
3. Eye Tracking - Quantifying human gaze
The aim of the course is to get to know eyetracking technology and related research possibilities in the field of humanities in theory and practice.
In the theoretical part, the history, development and technological progress of eyetracking will be presented and discussed using the system(s) available in the MediaLab of the faculty.
This is followed by a practical approach to the system through data generation with actual eyetracking research. Participants will develop research questions that can be examined with gaze data, that will be captured during a recording session.
Top comments (1)
Hello!
Your post resonated with me because it perfectly captures the crossroads where a humanist today finds themselves. You're entered a Master's program in Digital Humanities, seeing it as a direct pathway to becoming an accessibility specialist—which is both practical and deeply meaningful. As a researcher constantly working at the intersection of philology, large text corpora, and computational methods, I find it particularly intriguing to look at your plan through the lens of my own experience. And I'd like to share a few observations that, I hope, will show that your courses are not just a set of skills, but keys to an entirely new way of seeing the world.
First, about the "Introduction to DH Tools and Methods." The list of topics—OCR, NLP, visualization, spatial and network analysis—is essentially the workhorses of our field. But for you, with your specific goal, there's a hidden yet crucial layer here. When we apply NLP to literary texts (as in my work on stylometry and attribution), we learn to formalize the unformalizable—authorial style, semantics, aesthetics. Now imagine turning this same skill toward accessibility: it becomes the ability to structure complex content for screen readers, identify semantic landmarks in a narrative, or automatically generate high-quality alternative descriptions. You're not just learning to code; you're learning to translate complex humanistic meanings into the language of strict algorithms—and that's invaluable for inclusivity.
Next, "Telling Data Stories." In my view, this is one of the most powerful courses. In my own practice, I've come to believe that a good visualization (whether it's a map of 18th-century Russian poetry or a timeline of writers) is not decoration but a method of inquiry. For an accessibility specialist, the ability to create a "good" visualization and then equally well "tell" it in words or tactile form is the foundation of the profession. After all, what makes a chart or map accessible to someone who cannot see it? A well-crafted textual description, grounded in critical reflection on what data we're showing and, more importantly, what story we're telling through that visualization. This course teach how to see the structure of data, which directly leads to the ability to create universal (textual, audio, tactile) interfaces to that structure.
And finally, "Eye Tracking." Honestly, this course intrigues me the most. As a philologist, I see eye tracking as a window into how a person actually perceives text: where their gaze stumbles, what it lingers on, how it moves across the page. Heat maps from sighted users could become a tool for generating hypotheses: what and in what order should a screen reader vocalize to create an optimal path of understanding for a blind user? It's this combination of empiricism and empathy that yields unique results.
Overall, your set of courses creates a beautiful balance.