Lost in digitalization? Using data as a source for quantitative art history

Panel that will be held at the DHBenelux 2026 conference. Abstract: The rapid advancements of data methods and technologies, coupled with the increasing availability of data from museums, researchers, and art-related institutions, open new avenues for applying data analysis to the field of art history. Nevertheless, art historical data are complex artifacts, whose selection reflects the interests of current and past art collectors and curators, and which often rely on uncertain, interpretative, and incomplete information. Furthermore, only a limited part of such data had been digitalized. In this context, the open question is how it is possible to conduct faithful and relevant quantitative analyses in the art history sector, given these limits and challenges. This panel aims to address this issue with speakers from an art historical, technical, or mixed background to discuss which adaptations are needed from statistics, biology, and data science to conduct quantitative analyses that are meaningful to advance art historical knowledge.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-14
DOI
https://doi.org/10.5281/zenodo.19571949
Primary Topic
Aesthetic Perception and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Lost in digitalization? Using data as a source for quantitative art history

Sofia Baroncini, Thorsten Wübbena, Angela Dreßen, Weixuan Li et al.
Zenodo (CERN European Organization for Nuclear Research)
Aesthetic Perception and Analysis
article

Lost in digitalization? Using data as a source for quantitative art history

Sofia Baroncini, Thorsten Wübbena, Angela Dreßen, Weixuan Li, Bárbara Romero Ferrón, Folgert Karsdorp
article en

Abstract

Panel that will be held at the DHBenelux 2026 conference. Abstract: The rapid advancements of data methods and technologies, coupled with the increasing availability of data from museums, researchers, and art-related institutions, open new avenues for applying data analysis to the field of art history. Nevertheless, art historical data are complex artifacts, whose selection reflects the interests of current and past art collectors and curators, and which often rely on uncertain, interpretative, and incomplete information. Furthermore, only a limited part of such data had been digitalized. In this context, the open question is how it is possible to conduct faithful and relevant quantitative analyses in the art history sector, given these limits and challenges. This panel aims to address this issue with speakers from an art historical, technical, or mixed background to discuss which adaptations are needed from statistics, biology, and data science to conduct quantitative analyses that are meaningful to advance art historical knowledge.

Zenodo (CERN European Organization for Nuclear Research)
Leuphana University of Lüneburg (DE), Leiden University (NL), Royal Netherlands Academy of Arts and Sciences (NL), Leibniz Institute of European History (DE), Universidad de Málaga (ES), University of Amsterdam (NL)
Openalex Percentile: Top 5%
Aesthetic Perception and Analysis
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Lost in digitalization? Using data as a source for quantitative art history — Sofia Baroncini, Thorsten Wübbena, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS