Summer School: Machine Learning for Digital Scholarly Editions - Keynote 2

Ulrike Henny-Krahmer is Junior Professor for Digital Humanities at the University of Rostock. Her research focuses on digital scholarly editing, computational text analysis, and questions on the sustainability and evaluation of digital scholarly outputs. Since 2012, she is a member of the Institute for Documentology and Scholarly Editing (IDE) and since 2019, she has been one of the managing editors of the journal RIDE - A Review Journal for Digital Editions and Resources. Since 2025, she is a member of the Technical Council of the Text Encoding Initiative (TEI).

"Machine learning and scholarly editing - a contradiction or an exciting partnership?" Traditionally, scholarly editions aim to produce a reliable text based on historical documents that can be used as a basis for further research in the respective subject area(s). Depending on the type of source, this methodologically requires a precise text comparison and a detailed examination of the nature of the underlying documents and their textual contents. How does this fit in with machine learning methods that recognise patterns based on large amounts of data so that we can obtain models with which we can make probability-based predictions for further data? Are these approaches even compatible with each other and how can we resolve the methodological contradictions or seek connections between the methods? The lecture will discuss these questions using the concrete example of letters from the edition of the works of the German writer Uwe Johnson (1934–1984), for which topic models were created. It will also be about how far humanities scholars, digital humanists, and computer scientists can delve into the other domain in order to understand the respective methods. This understanding not only provides exciting opportunities, it is also a prerequisite for the successful application of machine learning methods in the humanities.
Online: https://unimeet.uni-graz.at/b/sch-pwq-3w3-ioy