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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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Results of the poll in the study "Information Scientists' Motivations for Research Data Sharing and Reuse"

Authors: Shutsko, Aliaksandra;

Results of the poll in the study "Information Scientists' Motivations for Research Data Sharing and Reuse"

Abstract

This is a dataset with results of the poll conducted in the study “Information Scientists’ Motivations for Research Data Sharing and Reuse”. In terms of the Uses and Gratifications Theory (Questions 1 and 2), the most popular uses relate to the categories of research support and information. Researchers share, or would share, their research data in general for any reusability purposes and especially for combination of different datasets to produce new evidence. Also, the vast majority of study participants associate research data sharing with possibilities to accelerate scientific progress and to increase research efficiency. In case of research data reuse, all the researchers indicated that they use, or would use, others’ data first of all for inspiration. Interestingly, study participants put relatively high the category of recognition in case of sharing, but at the same time they do not associate increased recognition among colleagues and other researchers with research data reuse. The remaining categories belonging to the categories of self-esteem and social interaction, i.e. increased citation level and visibility of the research as well as enhanced scientific reputation, possible cooperations and co-authorship, were selected only by few respondents. Also remarkably, data reuse is more frequently linked to entertainment then data sharing. In terms of the Self-Determination Theory (Questions 3 and 4), all but one of the interviewees indicated that they have shared or would share their research data because it can accelerate scientific progress which they consider important and would like to contribute to it (i.e., identified regulation). The second most popular motivation turned out to be the obligation by employer, project funder and/or journals (i.e., external regulation). The third most popular option was social influence, i.e. because many other researchers participate in data sharing and they feel obligated to do the same (i.e., external regulation).This way, the participants demonstrate a mixture of identified motivation and external regulation, both material and social. In the case of data reuse, the participants demonstrate more homogeneous results with identification and intrinsic motivation having most of the votes. The role of external regulation seems to be much less important as in the case with data sharing. So, researchers reuse, or would reuse, research data because it can accelerate scientific progress which is important for them. Additionally, researchers enjoy exploring and using third party research data. Thus, interviewees participate or would participate in data sharing because they consider it important, but also feel or are obliged to do so. At the same time, study participants do not feel pressure from outside when deciding whether to reuse data or not. For more information about the study and its results, please read the article “Information Scientists’ Motivations for Research Data Sharing and Reuse” by Shutsko and Stock (2023).

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Keywords

motivations, poll results, data sharing, gratifications, data reuse, dataset, information science, research data

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
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21
1
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