Measuring academic research impact based on open data: A case of engineering faculties

Tsolakidis, Anastasios; Triperina, Evangelia; Sgouropoulou, Cleo; Christidis, Nikos

doi:10.1109/educon.2017.7943064

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…Besides performance incentives, open data offers diverse personal advantages, for example increased citation rates, recognition, and reputation [14,19]. These aspects affect not only researchers' impact factors [55], but also the relevance of their own publications, leading to increased peer recognition [56], new collaboration possibilities [57], and overall career benefits [16]. Thus, we generated the following hypotheses:…”

Section: Perceived Advantages (Hypotheses 1a-c)mentioning

confidence: 99%

When are researchers willing to share their data? – Impacts of values and uncertainty on open data in academia

et al. 2020

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Background E-science technologies have significantly increased the availability of data. Research grant providers such as the European Union increasingly require open access publishing of research results and data. However, despite its significance to research, the adoption rate of open data technology remains low across all disciplines, especially in Europe where research has primarily focused on technical solutions (such as Zenodo or the Open Science Framework) or considered only parts of the issue. Methods and findings In this study, we emphasized the non-technical factors perceived value and uncertainty factors in the context of academia, which impact researchers' acceptance of open data-the idea that researchers should not only publish their findings in the form of articles or reports, but also share the corresponding raw data sets. We present the results of a broad quantitative analysis including N = 995 researchers from 13 large to medium-sized universities in Germany. In order to test 11 hypotheses regarding researchers' intentions to share their data, as well as detect any hierarchical or disciplinary differences, we employed a structured equation model (SEM) following the partial least squares (PLS) modeling approach. Conclusions Grounded in the value-based theory, this article proclaims that most individuals in academia embrace open data when the perceived advantages outweigh the disadvantages. Furthermore, uncertainty factors impact the perceived value (consisting of the perceived advantages and disadvantages) of sharing research data. We found that researchers' assumptions about effort required during the data preparation process were diminished by awareness of e-science technologies (such as Zenodo or the Open Science Framework), which also increased their tendency to perceive personal benefits via data exchange.

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