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  • Omeka
  • Data standards
  • The API
  • What to use when
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  1. Programme
  2. Session 8

Session 8

Introduction to Omeka

Author
Affiliation

Tobias Hodel

Walter Benjamin Kolleg / Digital Humanities, University of Bern

Published

3 November 2026

Modified

2 September 2026

Hodel Taught by Tobias Hodel.

In this session

  • Omeka: publishing a collection
  • Data standards and controlled vocabularies in practice
  • The Omeka API
  • What to use when: GitHub Pages or Omeka?

Omeka

  • Omeka Classic and Omeka S — what the difference actually means for you
  • Items, item sets, media, sites
  • Templates and exhibits: presenting a collection as an argument
  • Users and permissions, for projects with more than one person

Data standards

Omeka is built on Dublin Core, which makes the abstractions from the Intro concrete:

  • Filling in the fifteen elements for a real object — and noticing which ones fight you
  • Resource templates: constraining what may be entered, and why constraint helps
  • Controlled vocabularies: attaching values from GND, Getty AAT, GeoNames or Wikidata instead of typing strings
  • Linking items to each other, and to the outside world

The API

  • The Omeka S REST API: reading and writing items
  • Bulk import from CSV
  • Getting your data back out — the test of any publication platform

What to use when

An honest comparison, since you now have both:

GitHub Pages Omeka
Best for a text-led argument, a small documented dataset an object-led collection with rich metadata
Metadata whatever you define Dublin Core, enforced
Who can edit anyone comfortable with Git anyone with a login
Hosting free, static, near-indestructible needs a server and maintenance
Longevity very high; it is just files depends on whoever maintains the instance
Cost of exit none export, and hope

The real question is not which is better. It is: who will maintain this in five years, and what happens when they stop?

ImportantFinal-year meeting (II) — 16:00

Students in their final year report on the status of their projects.

TipIn parallel in the Intro

Data analysis: networks

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