Addressing global scientific challenges requires the widespread sharing of consistent and trustworthy research data. Identifying the factors that influence widespread data sharing will help us understand the limitations and potential leverage points. We used two well-known theoretical frameworks, the Theory of Planned Behavior and the Technology Acceptance Model, to analyze three DataONE surveys published in 2011, 2015, and 2020. These surveys aimed to identify individual, social, and organizational influences on data-sharing behavior. In this paper, we report on the application of multiple factor analysis (MFA) on this combined, longitudinal, survey data to determine how these attitudes may have changed over time. The first two dimensions of the MFA were named willingness to share and satisfaction with resources based on the contributing questions and answers. Our results indicated that both dimensions are strongly influenced by individual factors such as perceived benefit, risk, and effort. Satisfaction with resources was significantly influenced by social and organizational factors such as the availability of training and data repositories. Researchers that improved in willingness to share are shown to be operating in domains with a high reliance on shared resources, are reliant on funding from national or federal sources, work in sectors where internal practices are mandated, and live in regions with highly effective communication networks. Significantly, satisfaction with resources was inversely correlated with willingness to share across all regions. We posit that this relationship results from researchers learning what resources they actually need only after engaging with the tools and procedures extensively.
https://doi.org/10.1057/s41599-023-01831-7
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