This workshop demonstrates a complete research data workflow for digital humanities scholars from digital publication to computational text analysis in line with the FAIR principles. The workshop is aimed at digital humanities scholars with a background in text-based research areas such as literary studies, history, (computational) linguistics, digital humanities, and related fields. Participants are required to bring their own laptop.

The first section guides participants through publishing textual data in the TextGrid Repository, a long-term digital archive for humanities research. Participants will use a user-friendly publication workflow that combines familiar tools like TEI, XPath, and Jupyter Notebooks. During this part of the workshop, participants will work with the TEI corpora prepared by the team. However, participants are also invited to bring their own TEI documents for discussion. No prior knowledge of TEI is necessary.

The second section focuses on textual analysis by means of the Python-based NLP library MONAPipe. Participants will execute analyses through Jupyter Notebooks, gaining hands-on experience with linguistic tasks (coreference, morphosyntactic analysis), entities (NER and entity linking), or spatial and narrative analysis. Participants will work with both traditional machine learning and LLM-based approaches, including language-specific and multilingual implementations. For this section of the workshop, participants should have familiarity with Python. Prior experience with NLP is helpful but not required.

Participants will have access to the high-performance computing infrastructure of the GWDG, enabling efficient text processing for GPU-intensive and LLM-based methods. Annotations will be stored stand-off and visualised aligned with the published data.