ArticlePloS one2017
Data sharing as social dilemma: Influence of the researcher's personality.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Commentary: Making Patient Data Count-Opportunities and Challenges for Open Science in Clinical Psychology.Journal of clinical psychology · 2026Article
- Acceptability of Active and Passive Data Collection Methods for Mobile Health Research: Cross-Sectional Survey of an Online Adult Sample in the United States.JMIR formative research · 2025Article
- Article
- Estimating social bias in data sharing behaviours: an open science experiment.Scientific data · 2023Article
- Care to share? Experimental evidence on code sharing behavior in the social sciences.PloS one · 2023Observational
- Sharing, reuse, and storage of biosamples among biomedical researchers in Jordan: Practice and concerns.PloS one · 2022Article
- Dynamics of cumulative advantage and threats to equity in open science: a scoping review.Royal Society open science · 2022Article
- How do researchers approach societal impact?PloS one · 2021Article
- How Can We Not Waste Legacy Genomic Research Data?Frontiers in genetics · 2020Article
- Article
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Authors and funding
4 authors.
Funding
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Abstract
It is widely acknowledged that data sharing has great potential for scientific progress. However, so far making data available has little impact on a researcher's reputation. Thus, data sharing can be conceptualized as a social dilemma. In the presented study we investigated the influence of the researcher's personality within the social dilemma of data sharing. The theoretical background was the appropriateness framework. We conducted a survey among 1564 researchers about data sharing, which also included standardized questions on selected personality factors, namely the so-called Big Five, Machiavellianism and social desirability. Using regression analysis, we investigated how these personality domains relate to four groups of dependent variables: attitudes towards data sharing, the importance of factors that might foster or hinder data sharing, the willingness to share data, and actual data sharing. Our analyses showed the predictive value of personality for all four groups of dependent variables. However, there was not a global consistent pattern of influence, but rather different compositions of effects. Our results indicate that the implications of data sharing are dependent on age, gender, and personality. In order to foster data sharing, it seems advantageous to provide more personal incentives and to address the researchers' individual responsibility.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.