Assignment

The Lab is assessed on a workflow: you take a research question of your own through a complete chain — data model, data analysis, data publication — and you write it up.

Two deliverables:

1. A presentation of the workflow, in Session 13
2. A write-up, published on GitHub Pages

1. The workflow

Build and present a workflow that covers all three stages:

Data model

• What are the entities in your material, and how do they relate?
• Show the model — a diagram from draw.io, a schema from QuickDBD, an SQLite schema, an ontology mapping, a TEI customisation. Whatever fits the material.
• Justify it. Every model excludes something; say what yours excludes.

Data analysis

• Apply at least one method to your data: a query, a network, a topic model, a classification, a reconciliation, a text-recognition pipeline.
• Application of algorithms is expected — you should be able to say what the algorithm does, not only which button you pressed.
• A prototype is a legitimate outcome. It does not have to be finished, and it does not have to have worked.

Data publication

• Publish the result somewhere it can be reached: GitHub Pages, Omeka, a repository with a DOI.
• Data separate from presentation, with a licence and a README.

2. The write-up

Publish the account of your workflow on GitHub Pages. It should:

• Explain the plan. What you set out to do, how the three stages fit together, what you would do next if the semester were longer.
• Document the steps in enough detail that someone else could repeat them. Include the dead ends — a workflow write-up that reports only successes is not useful to anyone.
• Refer to at least three articles or chapters relating to your workflow. They should be texts that actually informed a decision you made, not decoration. Cite them properly — you have Zotero.
• Declare your use of AI tools: which ones, for which steps. Expected and legitimate; undocumented use is not.

ImportantLink the two assignments together

The three articles or chapters must be linked from your bibliography website built in the Intro course. The two assignments are meant to connect: the Intro site holds and annotates the literature, the Lab write-up puts it to work in a concrete workflow. Link across in both directions.

3. The presentation

10–15 minutes in Session 13, plus discussion. Show the actual artefacts rather than slides about them. See the session page for the structure and the feedback format.

Deadlines

Topic agreed	To be confirmed in class
Presentation	8 December 2026 (Session 13)
Write-up published	To be confirmed in class

WarningDates still to be fixed

The remaining deadlines are agreed in the first sessions and entered here.

Assessment criteria

The Lab is graded. Assessment is based on:

• Coherence of the workflow — do the three stages actually connect, or are they three unrelated exercises?
• Quality of the data model — is it appropriate to the material, and are its choices defended?
• Soundness of the analysis — is the method suited to the question, and are the results read with appropriate caution?
• Reproducibility — could someone else follow the write-up and get the same result?
• Engagement with the literature — do the three texts inform the work, or decorate it?
• Honesty about limits — failures documented and understood count in your favour.

Relation to the Intro assignment

The Introduction to DH assignment is separate: a Zotero bibliography published as a commented website with an About page on the workflow.

The two are designed to connect. The bibliography you build for the Intro is a perfectly good dataset for a Lab workflow, and the three texts underpinning your workflow must be linked from that Intro site. They are nonetheless handed in and graded separately, and neither substitutes for the other. See the Intro assignment.