Open Research Data in the Open Science Ecosystem and Business Environment

A. Boiko, Olha Kramarenko, T. Mayboroda
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引用次数: 2

Abstract

Abstract Today, one can observe shifts in the research landscape, which is formed by digitization and open science principles. The open science movement continues to gain momentum, attention and debate. In parallel with the principle of unity, open science gives rise to a taxonomy of several related ideas, guidelines and concepts, such as open access, open replicable research and open data. Over the past fifteen years, research institutions have focused on open access to publications. However, recently the focus of attention has shifted to research data as a “new currency” in research activities and their distribution in open access, and the guiding principles of data management are becoming crucial for the wide implementation of open science practices and the effective use of data in research, industry, business and other sectors of the economy. In this context, it is relevant to carry out a thorough study of primary scientific works on open science issues and to study the role of the concept of “open research data” in the paradigm of a holistic ecosystem of open science and business ecosystem. In this work, it is proposed to use the methods of quantitative and qualitative bibliometric analysis, which allows to identify the main trends and form the basis for further research. The information base for this work was the international scientometric database Scopus, which enables to analyze bibliographic data using built-in tools and import them for external use in the VOSviewer software. The study revealed an increasing trend in the number of publications on the subject under study, with the highest annual growth rate in 2017 (76%) and 2019 (66%). Qualitative bibliographic analysis made it possible to analyze the most cited and, therefore, trending works on the selected topic. In terms of the number of citations per year, the results show that the studies with such directions in open science as open program code (open source); data/research reproducibility, research data management; open access to publications (open access) are most popular. In addition, a cluster analysis of the co-prevalence of keywords was conducted. It formed clusters dedicated to both institutional and infrastructural problems of the development of open science and research data. Separately, the results of the analysis create a scientific basis for further research into the key determinants of the effectiveness of the implementation of a proper research data management system at the micro, meso, and macro levels. It will improve the effectiveness of the implementation of scientific developments from one field of knowledge to another, while achieving increased interdisciplinary research. In parallel with this, interested persons of the real sector of the economy get the opportunity to analyze scientific results, determining the possibility of their adoption in their own activities.
开放科学生态系统和商业环境中的开放研究数据
今天,人们可以观察到由数字化和开放科学原则形成的研究格局的变化。开放科学运动继续获得动力、关注和辩论。与统一性原则并行,开放科学产生了几个相关思想、指导方针和概念的分类,如开放获取、开放可复制研究和开放数据。在过去的15年里,研究机构一直专注于开放获取出版物。然而,最近关注的焦点已经转移到研究数据作为研究活动的“新货币”及其在开放获取中的分布,数据管理的指导原则对于开放科学实践的广泛实施和数据在研究、工业、商业和其他经济部门的有效利用变得至关重要。在此背景下,有必要对开放科学问题的初级科学著作进行深入研究,并在开放科学和商业生态系统的整体生态系统范式中研究“开放研究数据”概念的作用。在这项工作中,建议使用定量和定性文献计量学分析的方法,这可以确定主要趋势,并为进一步研究奠定基础。这项工作的信息库是国际科学计量数据库Scopus,它可以使用内置工具分析书目数据,并将它们导入VOSviewer软件中供外部使用。该研究显示,与所研究主题相关的出版物数量呈增加趋势,2017年(76%)和2019年(66%)的年增长率最高。定性书目分析使分析被引用最多的作品成为可能,因此,在选定的主题上,趋势作品。从年引用次数来看,结果表明,在开放科学领域,以开放程序代码(open source)为方向的研究;数据/研究可重复性,研究数据管理;对出版物的开放存取(Open access)是最受欢迎的。此外,对关键词的共患病率进行了聚类分析。它形成了致力于开放科学和研究数据发展的体制和基础设施问题的集群。另外,分析结果为进一步研究在微观、中观和宏观层面实施适当的研究数据管理系统的有效性的关键决定因素奠定了科学基础。它将提高从一个知识领域向另一个知识领域实施科学发展的效率,同时实现更多的跨学科研究。与此同时,实体经济部门的相关人员有机会分析科学结果,确定其在自己的活动中采用的可能性。
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