Göttingen Projects in Digital Humanities

The Integrative Lecture aims to introduce various research projects in the field of Digital Humanities, which are based in Göttingen, and thus give an overview of the diversity of DH research at the Göttingen Campus.
The lectures will last about 45 minutes. Afterwards, there will be time for questions and lively discussions.

The lecture takes place in ZHG 002 and online, via BigBlueButton

All lectures will start at 6pm c.t.

  • 08.11.2022
    Terry Ruas
    A short introductions to Bias and Ethics in NLP; GElections: The German Elections under the Microscope

  • 15.11.2022
    Jörg Wettlaufer
    The Göttingen Digital Academy. Supporting sustainable basic research in the humanities

  • 22.11.2022
    José Calvo Tello
    The Library Catalog as Qualitative Data for Quantitative Analysis: An Example from Romance Studies

  • 29.11.2022
    Marco Coniglio
    The WiN Corpus. Digital analysis of translations of High and Low German incunabula

  • 06.12.2022
    Alexander Zawacki
    Image Science and Digital Palaeography

  • 13.12.2022
    Deborah Ehlers
    VR4Study: Exploring Perspectivity with Avatars

  • 20.12.2022
    Benjamin Gittel, Thomas Haider
    Semantic Change in Literary Criticism

  • 10.01.2022
    Michael Schlee
    Semi-Supervised Scene Recognition on Attic Vase Paintings: A Novel Approach for Fusioning Image and Text Data

  • 17.01.2022
    Jörg Wesche
    Translation in Baroque Poetics. A digital Approach

  • 24.01.2022
    Johanna Sophia Störiko
    Advertisements in the magazine "Die Jugend" (1896-1900). Digital acquisition of the advertisements and evaluation of the advertised goods

  • 31.01.2022
    Daniel Kurzawe, Christoph Kudella
    Libraries in the 21st Century: Research and Development, Digital Editions at the SUB Göttingen

  • 07.02.2022
    Anna Dorofeeva
    Retro-engineering the medieval book: the possibilities of digital fragmentology

  • 14.02.2022
    Marta Kipke
    What is style? Methods, insights and challenges of painter attribution on Attic vase paintings using artifical neural networks