DH Lab
Autumn Semester 2026 · Tuesdays 14:00–17:15 · Unitobler, Lerchenweg 36, Room F-123
The Lab runs alongside Introduction to Digital Humanities on the same fourteen Tuesdays. The Intro supplies the concepts — what data is, how it is modelled, published and analysed. The Lab is where you build it: the command line, Git, SQLite, APIs, TEI, OpenRefine, notebooks, eScriptorium.
What the Lab is
The Lab is a workshop, not a lecture. Every session is hands-on: you install something, you break something, you get it working, and you write down what you did. The point is not to become a software developer. The point is to reach the level of technical fluency where you can judge what a digital method is doing to your material — and where you can build a small, honest research workflow of your own from beginning to end.
Across the semester you will:
- Get comfortable with your own computer — the command line, file paths, how storage actually works
- Set up a working environment: Markdown, Obsidian, Git and GitHub, VSCodium
- Replace a spreadsheet with a database and learn to model data properly
- Move from Linked Open Data to the formal ontologies used in cultural heritage: RiC-O, LRM, CIDOC-CRM
- Call APIs — Zotero’s and those of cultural heritage institutions
- Encode a text in TEI and understand editing as a form of data publication
- Publish a collection in Omeka, and judge when to use it rather than GitHub Pages
- Run analyses in notebooks (Colab / Noto), including topic modelling
- Clean and reconcile messy data with OpenRefine
- Produce your own training data for handwritten text recognition in eScriptorium
- Put multimodal LLMs to work on humanities material — and check what they return
Who the Lab is for
The Lab is aimed at students of the MA Major and MA Minor Digital Humanities at the University of Bern, and is where the practical part of the programme happens. It also carries the programme’s own business: introductions to the Major and Minor, individual consultations, and the meetings where final-year students report on their theses.
Students from other programmes are welcome. No prior programming knowledge is required — the first sessions assume nothing beyond being able to use a computer — but the Lab does ask for patience with things that do not work the first time.
The Lab and the Intro are designed as a pair and work best taken together. Each is comprehensible on its own; taken together, the concept in the morning and the tool in the afternoon reinforce each other week by week.
Organisation
| Semester | Autumn Semester 2026 (HS 2026) |
| Time | Tuesdays, 14:00–17:15 — the Lab starts at 14:00 sharp |
| First session | 15 September 2026 |
| Last session | 15 December 2026 |
| Room | Unitobler, Lerchenweg 36, F-123 |
| Language | English |
| Companion course | Introduction to Digital Humanities |
| Course materials | ILIAS course space |
| Assessment | Workflow presentation + write-up, see Assignment |
What to bring
- Your own laptop. Any operating system. The Lab installs software on it — if your machine is managed by an employer and you cannot install anything, tell us in Session 1.
- Accounts for GitHub and Zotero (set up in the Intro, weeks 1 and 2)
- Membership of the DH UniBe Zotero group — ask to be added
- A willingness to type commands you do not yet understand
Weekly programme
| # | Date | DH Lab | Introduction to DH |
|---|---|---|---|
| 1 | 15 Sep | Programme information, introductions, consultations Course team | Welcome · What is DH Course team |
| 2 | 22 Sep | Get to know your computer Demleitner | What is DH? · What is data? Hodel |
| 3 | 29 Sep | Get to know useful stuff Hodel | Forms of data and metadata Hodel |
| 4 | 06 Oct | Replacing Excel with SQLite Beretta | Data structures Beretta |
| 5 | 13 Oct | From LOD to RiC-O, LRM and CIDOC-CRM Hart | Linked Open Data Beretta |
| 6 | 20 Oct | Introduction to APIs Hodel | The web as interface Hodel |
| 7 | 27 Oct | Scholarly editing as data publication (TEI) Spadini | Data modelling: editions Spadini |
| 8 | 03 Nov | Introduction to Omeka Hodel | Data analysis: networks Hodel |
| 9 | 10 Nov | Introduction to Colab / Noto Hodel | Data analysis: text corpora Hodel |
| 10 | 17 Nov | Data cleaning: OpenRefine and reconciliation Demleitner | Geovisualisation Hodel |
| 11 | 24 Nov | Text recognition: eScriptorium Hodel | Algorithms to machine learning Hodel |
| 12 | 01 Dec | GenAI in action: multimodal LLMs Prada Ziegler | LLMs: stochastic parrots Hodel |
| 13 | 08 Dec | Workflow presentations Course team | Data feminism Hodel |
| 14 | 15 Dec | Final-year presentations (Major / Minor) Course team | FAIR, CARE, sustainability Course team |
Hodel Tobias Hodel Spadini Elena Spadini Beretta Francesco Beretta Hart Stephen Hart Demleitner Adrian Demleitner Prada Ziegler Ismail Prada Ziegler Course team all three convenors
Students in their final year report on their projects twice during the semester, at 16:00 on the days of Session 3 (progress report) and Session 8 (status report), with the full presentations in Session 14.
Assessment
The Lab is graded. It is assessed through a workflow: a data model, an analysis and a publication, presented in class and written up on GitHub Pages. See the Assignment page.
Contact and imprint
University of Bern
Walter Benjamin Kolleg / Digital Humanities
Muesmattstrasse 45
3012 Bern