From research proposal to project management. A guide from the Transkribus community on planning and executing workflows for researchers and GLAM-professionals

Abstract Transitioning from research proposal to project management in Automatic Text Recognition (ATR) for cultural heritage text collections demands meticulous planning, realistic budgeting, and efficient team coordination. Insights from the Transkribus User Conference 2024 offer a roadmap for success, emphasising clear objectives, ethical considerations, and practical outcomes. Effective budgeting should include digitization, software, staffing, and long-term storage, while a comprehensive Data Management Plan (DMP) ensures efficient data handling. Key project management tasks include team formation, workflow documentation, and document layout optimization. High-quality training and validation data in ATR require clear guidelines, iterative testing, and agreed licensing. Crowdsourcing can enhance ATR projects, and sharing models and datasets through platforms like Transkribus Sites promotes collaboration and visibility.

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Publication Details

Journal
International Journal of Digital Humanities
Published
2025-09-01
DOI
https://doi.org/10.1007/s42803-025-00107-7
Citations
1
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
3.25

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article

From research proposal to project management. A guide from the Transkribus community on planning and executing workflows for researchers and GLAM-professionals

R Griffiths, Salvatore Spina, Achim Rabus, Günter Mühlberger et al.
1 citations
International Journal of Digital Humanities
Research Data Management Practices
3.25
article

From research proposal to project management. A guide from the Transkribus community on planning and executing workflows for researchers and GLAM-professionals

R Griffiths, Salvatore Spina, Achim Rabus, Günter Mühlberger, Melissa Terras, Carlotta Capurro, Ash Charlton, Joseph Nockels, Christel Annemieke Romein, Adi Keinan-Schoonbaert, Christa Schneider, Heleen Wilbrink, Süphan Kırmızıaltın, Fatma Aladağ, Ronny Reshef, Seongjin Ahn, Erika Kuijpers, David Joseph Wrisley, Levi Damsma, Lorena De Vita, Laura Fahnenbruck, Gert Gielis, Mirjam El Attal, Juma Noah Omollo, Nour al Assali, Eugenio Torres Flawiá, Giorgia Agostini
article en
1 citations

Abstract

Abstract Transitioning from research proposal to project management in Automatic Text Recognition (ATR) for cultural heritage text collections demands meticulous planning, realistic budgeting, and efficient team coordination. Insights from the Transkribus User Conference 2024 offer a roadmap for success, emphasising clear objectives, ethical considerations, and practical outcomes. Effective budgeting should include digitization, software, staffing, and long-term storage, while a comprehensive Data Management Plan (DMP) ensures efficient data handling. Key project management tasks include team formation, workflow documentation, and document layout optimization. High-quality training and validation data in ATR require clear guidelines, iterative testing, and agreed licensing. Crowdsourcing can enhance ATR projects, and sharing models and datasets through platforms like Transkribus Sites promotes collaboration and visibility.

International Journal of Digital HumanitiesVol. 7(2)
University of Siena (IT), University of Bern (CH), New York University Abu Dhabi (AE), Radboud University Nijmegen (NL), École Pratique des Hautes Études (FR), University of Freiburg (DE), Universität Innsbruck (AT), Utrecht University (NL), British Library (GB), Huygens Institute for History and Culture of the Netherlands (NL), University of Catania (IT), University of San Andrés (AR), Max Planck Institute for Legal History and Legal Theory (DE), Bunge & Born Foundation (AR), State Archives of Belgium (BE), Marmara University (TR), Vrije Universiteit Amsterdam (NL), University of Amsterdam (NL), University of Sheffield (GB), Erasmus University Rotterdam (NL), University of Twente (NL), University of Edinburgh (GB)
Koninklijke Nederlandse Akademie van Wetenschappen, Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 7%
Research Data Management Practices
3.25
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