期刊
SAFETY SCIENCE
卷 134, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.ssci.2020.105093
关键词
Scientometrics; Bibliometrics; Safety science; Mapping knowledge domains; Science mapping
资金
- National Natural Science Foundation of China [51904185, 51874042]
- Canada Research Chairs Program
- Natural Sciences and Engineering Research Council (NSERC)
Scientometrics analysis is increasingly used in various scientific fields to obtain quantitative insights on specific research areas by visualizing data metrics. The method allows researchers to gain a deeper understanding of different aspects of a scientific domain. Various methods have been developed to answer specific research questions, such as collaboration networks, thematic research clusters, historic evolution patterns, and trends in research topics.
Scientometrics analysis is increasingly applied across scientific domains to gain quantitative insights in the development of research on particular (sub-)domains of scientific inquiry. By visualizing metrics containing quantitative information about such a domain, scientometric mapping allows researchers to gain insights in aspects thereof. Methods have been developed to answer specific research questions, focusing e.g. on collaboration networks, thematic research clusters, historic evolution patterns, and trends in topics addressed. Several articles applying scientometric mapping to safety-related topics have been published. In context of the Special Issue 'Mapping Safety Science - Reviewing Safety Research', this article first reviews these, and subsequently provides an overview of key concepts, methods, and tools for scientometric mapping. Data sources and freely available tools are introduced, focusing on which research questions these are suited to answer. A brief tutorial-style description of a scientometrics research process is provided, guiding researchers new to this method how to engage with it. Finally, a discussion on best practices in scientometric mapping research is made, focusing on how to obtain reliable and valid results, and how to use the scientometric maps to gain meaningful insights. It is hoped that this work can advance the application of scientometric research within the safety science community.
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