Digital Humanities, University of Bern Digital Humanities, University of Bern Introduction to Digital Humanities
  • Course
  • Syllabus
  • Assignment
  • GitHub
  • Resources
  • Student Projects
  • About
  • DH Lab ↗
  1. Syllabus
  2. Session 3
  • Course
  • Syllabus
    • Session 1
    • Session 2
    • Session 3
    • Session 4
    • Session 5
    • Session 6
    • Session 7
    • Session 8
    • Session 9
    • Session 10
    • Session 11
    • Session 12
    • Session 13
    • Session 14
  • Assignment
  • Working with Git and GitHub
  • Resources
  • Student Projects
    • How to add your project here
  • About

  • DH Lab (companion course)

On this page

  • In this session
  • Forms of data (Schöch)
  • Metadata (Pomerantz)
  • Exercise: metadata in your own Zotero library
  • GitHub introduction
  • Reading for Session 4
  • Edit this page
  • Report an issue
  1. Syllabus
  2. Session 3

Session 3

What is data? Forms of data and metadata

Author
Affiliation

Tobias Hodel

Walter Benjamin Kolleg / Digital Humanities, University of Bern

Published

29 September 2026

Modified

2 September 2026

Hodel Taught by Tobias Hodel.

In this session

  • Forms of data in the humanities, following Schöch
  • Metadata, following Pomerantz
  • Explaining metadata concretely, through your own Zotero library
  • GitHub introduction (approx. 45 minutes)

Forms of data (Schöch)

Schöch’s four adjectives — big, smart, clean, messy — are a useful grid:

  • Humanities data is usually smart and small, or big and messy, rarely both big and smart.
  • What does it cost to clean data, and what is destroyed in the cleaning?
  • Which of your own materials sit where in the grid?

Metadata (Pomerantz)

  • Descriptive, structural, administrative, preservation and use metadata
  • Metadata as a statement about a resource — and therefore always someone’s statement
  • Controlled vocabularies and authority files: why “Bern” is not a sufficient answer
  • Standards as social agreements, not technical ones

Exercise: metadata in your own Zotero library

Open your library from last week and look at it as data:

  1. Pick five records. Which fields are filled, which are empty, which are wrong?
  2. Where did each record come from — the connector, a DOI lookup, manual entry? Does the provenance show in the quality?
  3. Export a small collection as CSV or BibTeX and look at the raw file. What does the export keep, and what does it quietly drop?
  4. Which of Pomerantz’s metadata types are present in a Zotero record, and which are missing?

This is the first time your bibliography is treated as a dataset. It will not be the last.

GitHub introduction

TipStanding reference

Everything in this part of the session, and a good deal more, is written up on the Working with Git and GitHub page — including three routes through Git depending on how far you want to go, and a list of further introductions and videos. Come back to it whenever you get stuck.

  • Repositories, commits, branches — the model, before the commands
  • The web interface: creating a repository, editing files, opening an issue
  • README, LICENSE, and why a repository without them is not a publication
  • How this connects to the Lab, where you meet Git on the command line
TipIn parallel in the Lab

The DH Lab covers Markdown, Obsidian, GitHub and VSCodium the same week. If you take both courses, do them in that order.

Reading for Session 4

Flanders, Julia, and Fotis Jannidis. 2018. “Data modeling in a digital humanities context: An introduction.” In The Shape of Data in Digital Humanities. Routledge.

Not openly available — a scan is in the ILIAS course space.

Back to top
Session 2
Session 4
  • Edit this page
  • Report an issue