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.
Highlights
The aim of this study is to propose some initial conceptual foundations of “Open Science” (OS) field of scholarship, with a particular focus on OS data
The relatively new phenomenon called “Open Science” has emerged due to the fundamental, revolutionary changes in government and science policies triggered by the development of Information and Communication Technologies (ICT)
Online collaboration tools, including those that are designed to engage with general public, contribute to the networked science, which in turn speeds up scientific discoveries and knowledge creation
Summary
The aim of this study is to propose some initial conceptual foundations of “Open Science” (OS) field of scholarship, with a particular focus on OS data. The relatively new phenomenon called “Open Science” has emerged due to the fundamental, revolutionary changes in government and science policies triggered by the development of Information and Communication Technologies (ICT). ICT advancements along with authorities’ commitment allow both government and science to become transparent, participatory, and collaborative. Data sharing technologies are expanding the boundary of scientific knowledge dissemination to the public, far beyond academic communities. Online collaboration tools, including those that are designed to engage with general public, contribute to the networked science, which in turn speeds up scientific discoveries and knowledge creation. In the era of Big Data and Linked Open Data, data-driven intelligence enhances our ability to extract new knowledge and create value under condition that the access to the world’s scientific data sources is widely available and the data are linked
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