About
Linked Open Exhibitions: A Curator’s Playbook
Catalogue exhibition contents using Linked Open Data and AI LLM assistants.
Data Science, GLAM, Open Science
Project
Linked Open Exhibitions: A prototype pipeline for publishing art exhibition data as Linked Open Data (LOD), developed with students of the Bachelor of Arts Information Management at Hochschule Hannover. The project is based on the Computational Publishing Service research
Motivation: A fundamental art history methodology is based on Johann Joachim Winckelmann cataloguing practice from the 18 Century which is to taxonomize artworks, famously detailed in his 1764 masterpiece Geschichte der Kunst des Alterthums (“History of the Art of Antiquity”).
Unfortunately current curating does not release open FAIR Data about items in an exhibition that easily allows this art history practice and instead either keeps the records in siloed private databases or in limited print only exhibition catalogues.
The project looks to put in place a modern data science driven cataloguing practice that would facilitate Winckelmann’s methodology.
The project is a resource for exhibition curators to catalogue exhibition content using open scholarship methods: Linked Open Data, FAIR Data Principles, open licencing, and AI-assisted research.
The resource would contain instructions for use as well as ready-to-go open licenced templates
The project has three options for curators:
- Cataloguing an exhibition being worked on
- Cataloguing a past exhibition for which a catalogue exists using OCR-processed catalogue data
- Retrieving past exhibition catalogue records from the Deutsche Nationalbibliothek (DNB) and structuring them using an open data model
- Course: BIM-126-02 Data Science, SoSe 2026
- Leads: Simon Worthington (TIB — Leibniz Information Centre for Science and Technology); Prof. Ina Blümel (Hochschule Hannover)
- Repository: https://github.com/NFDI4Culture/linked-open-exhibition
- Wikiversity: https://en.wikiversity.org/wiki/BIM-126-02-Data-Science-Linked-Open-Exhibition
Licences
Project content
All original content in this repository (code, documentation, notebooks, website) is released under:
CC BY-SA 4.0 — Creative Commons Attribution-ShareAlike 4.0 International
DNB metadata
All bibliographic metadata retrieved from the Deutsche Nationalbibliothek (DNB) SRU interface is released under:
CC0 1.0 Universal (Public Domain Dedication)
Source: dnb.de — Metadatendienste
The SRU interface is freely accessible without registration.
Cover images
Cover images retrieved via the DNB catalogue enrichment API are supplied by publishers and are not covered by the CC0 licence. They are used within this project solely for educational, non-commercial identification purposes and are not redistributed in this repository. Always verify image rights before reuse.
AI Attribution
This project was developed with the assistance of GitHub Copilot using the Claude Sonnet 4.6 model (April 2026).
AI assistance was used for: - Code generation (Python notebooks, SPARQL queries) - Documentation drafting - Data model design and planning - Glossary creation
All AI-generated outputs were reviewed and edited by the project team before use.
Credits
| Role | Name | Affiliation |
|---|---|---|
| Project lead | Simon Worthington | TIB — Leibniz Information Centre for Science and Technology |
| Course supervisor | Prof. Ina Blümel | Hochschule Hannover |
| Data model reference | Lozana Rossenova, Lucia Sohmen, Paul Duchesne | NFDI4Culture / WB4R |
| Funder | NFDI4Culture | — |
Technical stack
| Tool | Purpose |
|---|---|
| Quarto | Website rendering |
| wikibaseintegrator | Wikibase API client |
| mwclient | MediaWiki API client |
| python-dotenv | Credential management |
| DNB SRU API | Bibliographic data source |
| Wikibase | Knowledge base platform |
| GitHub Pages | Website hosting |