TY - JOUR
T1 - Perceived benefits of open data are improving but scientists still lack resources, skills, and rewards
AU - Borycz, Joshua
AU - Olendorf, Robert
AU - Specht, Alison
AU - Grant, Bruce
AU - Crowston, Kevin
AU - Tenopir, Carol
AU - Allard, Suzie
AU - Rice, Natalie M.
AU - Hu, Rachael
AU - Sandusky, Robert J.
N1 - Funding Information:
Data management organizations and institutions must make assumptions about which of these factors can be used to influence researchers’ open data practices. DataONE (the Data Observation Network for Earth) was created in 2009 with the idea that attitudes and behaviors could be changed by (a) providing easy-to-use data-sharing infrastructure and training, and (b) helping influential researchers within the natural sciences adopt open data practices (Michener et al., ). Its initial focus was on the biological and environmental sciences. DataONE was funded by a large federal grant to create cyberinfrastructure that would address barriers preventing more open, global, and reproducible research (Michener et al., ). Part of the charter of DataONE was to determine what these barriers are by surveying researchers in different fields and developing personas to help address their needs.
Funding Information:
We have shown that a trustworthy and open research climate and a perception of individual benefit increase data-sharing behaviors. The fact that willingness to share has increased since the 2010s in government and academic circles suggests that mandates and societal norms work. This is emphasized by the increase in willingness to share by researchers that receive federal or national funding. Such funding sources are dominated by research funding agencies such as the National Science Foundation and the Australian Research Council, all of whom have increasingly set an expectation of open data and open science for their grantees in alignment with recommendations from the International Science Council and the World Data System.
Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - 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.
AB - 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.
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U2 - 10.1057/s41599-023-01831-7
DO - 10.1057/s41599-023-01831-7
M3 - Article
AN - SCOPUS:85162191288
SN - 2662-9992
VL - 10
JO - Humanities and Social Sciences Communications
JF - Humanities and Social Sciences Communications
IS - 1
M1 - 339
ER -