Lectures

Computer as Archive, Computer as Agent: Tracing the Evolution of the Digital Humanities from the 1960s to an Uncertain Future

Tessa Gengnagel

In order to understand the current state of the digital humanities, we must look towards its past. Although some histories have been written, much remains undiscovered and underdiscussed. This lecture will propose a narrative of the field’s trajectory through the lens of ‘ideologies of knowledge work’. Starting with the international symposium for literary and linguistic computing in Tübingen in 1960, the lecture will spotlight both global and local developments with a particular focus on discourses split between East and West Germany during the Cold War. Leading up to present times, the lecture will reflect on meaning-making in DH and the challenges that arise from frameworks of operation beyond academic control. This includes agentic AI and the question of interdependence.

Dr. Tessa Gengnagel is managing co-director of the Cologne Center for eHumanities (CCeH) at the University of Cologne. After completing her B.A. in History and Latin Philology of the Middle Ages at the University of Freiburg, she studied European Multimedia Arts & Cultural Heritage Studies at the Universities of Cologne and Graz. During her M.A., she began working at the CCeH in 2013 as a student assistant. She defended her doctoral thesis, supervised by Prof. Manfred Thaller, in January 2021. It was published as a monograph in February 2024 and awarded with the Offermann-Hergarten-Prize. Her research interests are the digital scholarly edition of multimodal cultural heritage, modelling theory, and the epistemology and history of the digital humanities.

Structured Data Approaches to Historical Collections: Methods and Insights

This lecture showcases three projects using structured data to explore historical collections. Participants will see how interactive Jupyter notebooks, machine learning-assisted OCR, and data-driven visualization can transform textual and image-based sources, from pamphlets to private libraries. Each project approaches different materials and research questions, yet together they demonstrate the diverse ways structured datasets and computational methods can illuminate cultural heritage. The lecture emphasizes both common methodological frameworks and the unique challenges of analyzing and visualizing varied historical sources, offering a practical and engaging perspective on the potentials of structured data in digital humanities research.

Sonja Dorfbauer is a software developer at the ONB labs. She develops and refines technically driven Jupyter notebooks that build a bridge between computational methods and digital humanities.

Simon Mayer is a software developer at the Austrian National Library. He works on the design, development and implementation of projects that leverage artificial intelligence and machine learning for the cultural heritage sector.

Workshops 

Data Cleaning, Analysis, and Visualization with OpenRefine and Orange

Lars Kjær

This two-day workshop covers working with datasets using computer programs.

On the first day, we focus on messy datasets that may be easy for humans to read but difficult for computers, and learn how to improve datasets using OpenRefine. OpenRefine is open-source and a practical tool for improving data quality in Excel or CSV files.

On the second day, we focus on well-organised datasets for analysis and visualisation using Orange Data Mining. Orange is also open-source and helps understand data science concepts such as filtering, analysis, visualisation, and machine learning; it can also assist with everyday tasks.

Lars Kjær is Special Advisor in Digital Humanities at Copenhagen University Library | Royal Danish Library. He holds an academic background in history from the University of Copenhagen; and has completed examinations in Digital Data Analysis and Data Mining from the IT University Copenhagen. Lars is skilled in Python programming, linguistic software, natural language processing, text and data mining, photogrammetry, and GIS tools. Through his work in facilitating workshops and providing guidance at Copenhagen University Library, he assists students and researchers at Copenhagen University in acquiring new digital humanities skills. Additionally, by building new cultural heritage datasets, he helps the Royal Danish Library transform its collections into research data packages.

Network Analysis for Humanists

Giovanni Pietro Vitali

Using LLMs in Humanities Research via API

Valdis Saulespurēns

In this workshop, participants will learn how to access large language models via API and utilize them for bulk data analysis using Python. Through practical examples, we will explore prompt engineering techniques for tasks such as concept mining and named entity recognition in textual data. Additionally, we will examine challenges associated with historical digitized texts, including optical character recognition (OCR) errors, which may affect compatibility with language models. Participants will gain insights into how these models can be leveraged for error correction and translation, enhancing the usability of imperfect textual data.

The workshop is designed for researchers, data analysts, and professionals in text analysis, digital humanities, and computational linguistics. Only a basic familiarity with Python is required, which can be gained by attending introductory workshops at the summer school or reviewing the provided preparatory materials.

Valdis Saulespurēns works as a researcher and developer at the National Library of Latvia. Additionally, he is a lecturer at Riga Technical University, where he teaches Python, JavaScript, and other computer science subjects. Valdis has a specialization in Machine Learning and Data Analysis, and he enjoys transforming disordered data into structured knowledge. With more than 30 years of programming experience, Valdis began his professional career by writing programs for quantum scientists at the University of California, Santa Barbara. Before moving into teaching, he developed software for a radio broadcast equipment manufacturer. Valdis holds a Master's degree in Computer Science from the University of Latvia. When not working or spending time with his family, Valdis enjoys biking and playing chess, sometimes even at the same time.