Assignment

Published

2 September 2026

Modified

2 September 2026

The course is assessed through one piece of work carried across the semester: an annotated bibliography, built in Zotero, and published as a small website that you make yourself.

The point is not the bibliography as such. The point is that you take one small body of material through the whole chain the course describes — collect it, model it, describe it with metadata, publish it on the open web, and explain in your own words how and why you did it that way.

What to hand in

1. A bibliography in Zotero

Build a bibliography in Zotero covering digital approaches to your own field of research — your major or minor subject, the field of a Hausarbeit or Übung, or whichever discipline brings you to this course. If you do not want to work from your own field, take Digital Humanities in general, but then narrow it to a sub-topic: “DH and manuscripts”, “network analysis in social history”, “OCR for non-Latin scripts”, and so on. A sharp sub-topic is much easier to write well about than a broad survey.

Guidance:

  • Choose a topic connected to the humanities. It may come from your field of study or simply from your interests.
  • Use Zotero from the start, not at the end. Collections, tags and notes are part of the work, and they are what makes the later steps possible.
  • Keep the metadata clean. You will be asked to look critically at your own records in Session 3, and to reuse them as data in Sessions 5, 8 and 9.

2. A website about your bibliography

Publish a small website — GitHub Pages is introduced in Session 6, written up in the Git and GitHub guide, and is the expected route — that presents the bibliography and, more importantly, your reading of it. It should contain:

  • Structure. How you have organised the bibliography, and why that organisation and not another. Sections, categories, a chronology, a set of themes — whatever the material calls for. Make the structure visible to a reader.
  • Comments. Annotations on the entries: what a given text contributes, how it relates to the others, where the debates are. Not every item needs a paragraph, but the site should read as a commented bibliography rather than a list.
  • Links to the course. Point out where your material connects to specific sessions and concepts from the course — data modelling, Linked Open Data, editions, network analysis, machine learning, FAIR/CARE. Link to the session pages directly.

3. An About page explaining your workflow

A page on the same website that documents how you worked:

  • Which tools you used and why (Zotero, plugins, editor, Git, hosting, anything else)
  • How you got the data out of Zotero and into the site
  • What you tried that did not work, and what you would do differently
  • Where you used an LLM or an AI assistant, and for what — this is expected and legitimate, but it must be documented (see below)

The About page is where the reflective work happens. Treat it as part of the argument, not as an appendix.

Deadlines

Topic chosen To be confirmed in class
Draft site online To be confirmed in class
Final submission To be confirmed in class
WarningDates still to be fixed

The exact deadlines are agreed in Session 1 and 2 and will be entered here.

How the work is assessed

The course is graded. Your work is assessed on:

  • Coherence of the topic — is the sub-topic well chosen and clearly delimited?
  • Quality of the bibliography — are the sources relevant, are the records clean and complete, is the coverage plausible for the topic?
  • Quality of the annotation — do the comments show that you have read and understood the material, and do they relate the items to each other?
  • Structure and presentation — is the site legible, navigable and honest about what it is?
  • Reflection on the workflow — does the About page explain the choices, including the ones that went wrong?

Technical polish is not a criterion. A plain, well-organised site beats a decorated one.

Using LLMs and AI assistants

You may use LLMs and AI assistants for this assignment. In fact Session 2 asks you to. Two conditions:

  1. Document it. State on the About page which tools you used and for which steps.
  2. Check it. You are responsible for every claim and every reference on your site. LLMs invent bibliographic references convincingly and often; verify each one against the actual source.

Relation to the DH Lab

If you are also taking the DH Lab, its assignment is separate: the Lab asks for a workflow (data model, analysis, publication) with a written account published on GitHub Pages.

The two are designed to connect. Sharing a topic and sharing data is encouraged, and the Lab write-up is required to link its three underpinning texts back to this site — so build your bibliography with that in mind. The two are nonetheless handed in and graded separately. See the Lab assignment.

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