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Uncovering Biases Through Faceted Image Retrieval: Wikidata as a Data Provider for Art-Historical Research Cover

Uncovering Biases Through Faceted Image Retrieval: Wikidata as a Data Provider for Art-Historical Research

Journal of Open Humanities Data
Volume 12 (2026): Issue 1
By: Stefanie Schneider,  Matthias Springstein,  Julian Stalter,  Daniel Ritter,  Ralph Ewerth and  Eric Müller-Budack  
Open Access
|Jan 2026

Authors

Stefanie Schneider

stefanie.schneider@unimarburg.de

Institute of Art History, Marburg University, Marburg

Matthias Springstein

Matthias.Springstein@tib.eu

TIB – Leibniz Information Centre for Science and Technology, Hannover

Julian Stalter

julian.stalter@uni-marburg.de

Marburg Center for Digital Culture and Infrastructure, Marburg

Daniel Ritter

Daniel.Ritter@tib.eu

L3S Research Center, Leibniz University Hannover, Hannover

Ralph Ewerth

ralph.ewerth@uni-marburg.de

TIB – Leibniz Information Centre for Science and Technology, Hannover; L3S Research Center, Leibniz University Hannover, Hannover; Marburg University and Hessian Center for Artificial Intelligence (hessian.AI), Marburg

Eric Müller-Budack

eric.mueller@tib.eu

TIB – Leibniz Information Centre for Science and Technology, Hannover
DOI: https://doi.org/10.5334/johd.436 | Journal eISSN: 2059-481X
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Language: English
Submitted on: Oct 27, 2025
|
Accepted on: Dec 16, 2025
|
Published on: Jan 16, 2026
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
vision–language models,
multimodal retrieval,
faceted search,
art history,
visual culture

© 2026 Stefanie Schneider, Matthias Springstein, Julian Stalter, Daniel Ritter, Ralph Ewerth, Eric Müller-Budack, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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