The Impact of Research Data Infrastructures: The Case of the AlphaFold Database
Other authors
Publication date
2025-05-26ISSN
2413-9505
Abstract
While the scientific output of research infrastructures is well documented, the broader effects of their secondary outputs, such as computational resources and datasets, remain poorly understood. To better understand the benefits of these public resources, this study explores the AlphaFold (AFDB) database, a collaboration between DeepMind and the European Molecular Biology Laboratory (EMBL) that democratizes access to protein structure data. Employing a quantitative case study strategy using bibliometric analysis, this study compares publications indexed in the Web of Science Core Collection citing the original AF paper (Jumper et al., 2021) with those citing the AlphaFold database (Varadi et al., 2022), covering publications up to August 2024. We examine the impact of the EMBL AlphaFold database on research themes, collaboration patterns, and scientific impact. Our exploratory analysis identifies several impacts: studies leveraging the AF database investigate application-focused themes and require collaboration between fewer institutions. This research highlights the wide-ranging impacts of research infrastructures, emphasizing the need for comprehensive impact assessments to inform future research policy and funding decisions.
Document Type
Article
Document version
Published version
Language
English
Pages
7 p.
Publisher
CERN Publishing
Is part of
CERN IdeaSquare Journal of Experimental Innovation, Vol. 9(1)
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Rights
© L'autor/a
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/


