The Uptake of Open Science: Mapping the Results of a Systematic Literature Review

Abstract

This paper contributes to “Open Science” theory, with a specific focus on Open Science data generated by scholars. To this end, a mixed- method systematic literature review, including science mapping techniques, was conducted. Our preliminary results reveal the potential of Open Science as a domain for interdisciplinary research. A keyword co-occurrence network analysis using the VOSviewer visualisation tool identified five clusters of interrelated sub-concepts within Open Science research. The key distinctive characteristics and the various categories of Open Science data have been identified. The relevant data platforms have been provided to exemplify each category of Open Science data. Finally, a distinction between Open Science data and Open Government data was explored and the convergence point between them was presented.

A Bibliometric Analysis on How Organic Chemistry Education Research Has Evolved Collaboratively Over Time

“…To answer RQ2, we had analyzed the citation networks of 1056 articles according to (a) the publishing of a document by subject area, and (b) the top keywords and co-occurrence analysis. Keyword co-occurrence analysis is an effective content analysis method to map the strength of association between keywords in the literature (Shmagun et al, 2020). The released materials were then categorised according to their topic areas, as shown in Table 4.…”

“…The first cluster (red colour) is centred around 'laboratory instruction' as the largest node size whereas the size reflected the publications number in which the term was found. Besides, the number of clusters to which the terms have been assigned represented the total number of links with other nodes so-called "total link strength" metric (Van Eck & Waltman, 2017;Shmagun et al, 2020). The 'Hands-On Learning/Manipulatives' node was the nearest to the 'laboratory instruction' node and the close distance between both keywords suggested the strong relation as well as the important connection between these two (Nadzar et al, 2017;Van Eck & Waltman, 2017).…”

Examining the trend of research on active engagement in science education: Bibliometric analysis

“…In response to RQ2, we used top keyword and co-occurrence analysis to examine the citation networks of 1174 articles. Keyword co-occurrence analysis is a powerful content analysis technique for determining the degree of association among keywords in the literature (Shmagun et al, 2020).…”