Visualization of Research Data Management: A Scientometric Analysis

Abstract

Research data management has a significant value in this current scenario for the rapid development of information society. This research presents current trends in global research data management, identification of the most relevant topics through the thematic map, mapping of authorship, co-occurrences, review of bibliometric laws, citation analysis, keyword growth analysis and some more related issues. The purpose of this paper is to analyze the scientometric and bibliometrics of research data management to highlight the importance of its use in the research field. This paper aims to know the current global situation of research data management advancement keeping abreast of latest data sources for upload and preservation of plenty of research data generated daily. A data search was conducted from the most comprehensive database- Scopus based on relevant keywords in research data management. Extracted data was filtered by year, document type, language, and publication level then final purified data were analyzed and visualized by BibliometrixR, VOSviewer, MS Excel, and Datawrapper. A total of 1720 publications were retrieved from Scopus after an initial keyword search, and 1273 publications were selected applying limited exclusion criteria. The data contained 780 articles, 05 books, 57 book chapters, 372 conference papers, and 59 reviews. Most publications in research data management are in 2022 (n=180), most papers from source “Data Science Journal” (n=57), and most papers published by author “Ribeiro, C” (n=15).