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Cited by 5Handwritten Text Recognition TechniquesDigital Humanities and ScholarshipResearch Data Management Practices

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Human-in-the-loop tabular data extraction methods for historical climate data rescue

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Vercruysse, Bas, Birkholz, Julie M., Chandrasekar, Krishna Kumar Thirukokaranam, Muheki, Derrick, Thiery, Wim, Verbeeck, Hans, Hufkens, Koen, Jacobsen, Kim, Verbruggen, Christophe·2026·International Journal on Document Analysis and Recognition (IJDAR)
DOI 10.1007/s10032-025-00524-y
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Abstract

Historical meteorological data is necessary for modeling climate scenarios, yet there remain significant challenges in archiving, extracting relevant data, organization and provision. Data rescue efforts play an important role in collecting relevant information, yet the real challenge remains in the implementation of accurate and efficient methods for extracting information from historical handwritten tabular records which are largely recorded in handwritten logbooks. The diverse tabular structures, layouts, and writing styles in these documents, along with the accessibility and varying quality of source preservation, make it impractical to rely on a single solution. In an effort to fill this gap, we propose a human-in-the-loop workflow with benchmarks of open- and closed-source methods for extracting and processing handwritten tabular data. We explain through the case of climatological data from the Congo region (1907–1960) how HIL workflows can be implemented and their trade-offs for implementing solely computationally steered models. In addition, we outline how generalized large Vision Language models have changed how HIL workflows can be implemented as to increase accuracy and precision not only with semi-automatic solutions for data provision but also prompt engineering and the necessary (historical) context to achieve optimal results.

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Authors
Vercruysse, B., Birkholz, J. M., Chandrasekar, K. K. T., Muheki, D., Thiery, W., Verbeeck, H., Hufkens, K., Jacobsen, K., & Verbruggen, C.
Affiliations
  • Ghent University (BE)
  • Royal Library of Belgium (BE)
  • Royal Museums of Art and History (BE)
  • Vrije Universiteit Brussel (BE)
  • BlueGreen Labs (bv) (Belgium) (BE)
  • Royal Museum for Central Africa (BE)
Corresponding author
Vercruysse, Bas
ORCID
Venue
International Journal on Document Analysis and Recognition (IJDAR)
Publisher
Springer Science and Business Media LLC
Published
2025-05-08
Volume
29
Issue
1
Pages
61-75
ISSN
  • 1433-2825 (ISSN-L)
  • 1433-2833
DOI
10.1007/s10032-025-00524-y
OpenAlex
W4410144136
Cited by
5
References
5
Citations by year
2026: 5
FWCI
1.76
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal on Document Analysis and Recognition (IJDAR) (publishedVersion, cc-by-nc-nd)
  • Ghent University Academic Bibliography (Ghent University) (publishedVersion)
  • Lirias (submittedVersion, cc-by-nc-nd)
  • VUBIR (Vrije Universiteit Brussel) (submittedVersion, cc-by-nc-nd)
  • Ghent University Academic Bibliography (Ghent University) (submittedVersion, other-oa)
Funders
  • Fonds Wetenschappelijk Onderzoek (I000921N, FWOTM1151)
  • Belgian Federal Science Policy Office (BR/175/A3/COBECORE)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Handwritten Text Recognition Techniques
  • Social Sciences › Arts and Humanities › Literature and Literary Theory › Digital Humanities and Scholarship
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
Keywords
human-in-the-loop, tabular data extraction, historical meteorological data, climate data rescue, vision-language models, prompt engineering

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