Abstract
This study explores ways of identifying learned societies within the Research Organization Registry (ROR), a type of organization that so far lacks its own category within the registry. Despite their significant role in the academic landscape, learned societies lack distinct recognition in global databases, which lowers their visibility and perceived impact. Using enhanced ISSN data and the existing ROR database, we present a methodology to identify learned societies based on their publishing activities and organizational names. Our approach is validated against national lists of societies from Austria, Finland, and the UK, demonstrating the feasibility and reliability of our method which, however, has several limitations discussed in the paper. Our findings show that 92% of 1471 societies identified in ROR are currently assigned to ‘Other’ and ‘Nonprofit’ categories. We also highlight the geographical distribution and field-specific categorization of learned societies, emphasizing the diversity and scope of their influence. This paper contributes to the science of science field by proposing a framework that enhances the visibility and recognition of learned societies globally. Our research argues that ROR should consider enhancing their data schema to accommodate for learned societies, or a separate directory should be established to identify learned societies with ROR identifiers. This way ROR can provide an open research information resource for identifying learned societies both for research and practical purposes.
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Data availability
The final dataset of identified learned societies and assigned research fields and geographical scopes can be accessed from this URL: https://researchportal.amu.edu.pl/info/researchdata/UAMd59b319de1a54c77b7d2b6e53863cf65/
Notes
The official list was provided by one of the authors of this study (JP).
https://vwgoe.at/members/, data access: March 15, 2024.
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Funding
This study is supported by the Federation of Finnish Learned Societies.
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Emanuel Kulczycki: Conceptualization, Data Curation, Formal Analysis, Methodology, Visualization, Software, Writing—Original Draft, Writing—Review & Editing. Janne Pölönen: Conceptualization, Data Curation, Methodology, Writing—Original Draft, Writing—Review & Editing. Mikael Laakso: Conceptualization, Data Curation, Methodology, Writing—Original Draft, Writing—Review & Editing. Zehra Taşkın: Data Curation, Writing—Original Draft, Writing—Review & Editing.
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Kulczycki, E., Pölönen, J., Laakso, M. et al. Learned societies in the academic landscape: challenges in identifying and categorizing organizations. Scientometrics 131, 825–844 (2026). https://doi.org/10.1007/s11192-025-05304-3
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DOI: https://doi.org/10.1007/s11192-025-05304-3