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DATA JOURNALS AND DATA PAPERS IN VARIOUS RESEARCH AREAS AND SCIENTIFIC DISCIPLINES – BIBLIOMETRIC ANALYSIS BASED ON INCITES

Abstract

The main aim of this work is to provide insight into a bibliometric analysis of Data Journals and Data Papers in terms of research areas, disciplines, publication year and country. In particular, we calculated many bibliometric indicators, especially: the number of publications and citations. Furthermore, this work also investigated the top 20 journals in which scientists published the largest number of Data Papers. It was found that the first Data Paper in Medical and Health Science was published in 2006. Our results indicate that about 64% of Data Papers are cited and about 30% of Data Papers are articles that have international co-authors. We also found that a significant number of Data Papers were published in top quartile (Q1) Open Access journals. Furthermore, most Data Papers were published in Multidisciplinary Sciences, followed by Biological Sciences, Earth and related Environmental Sciences as well as Computer and Information Sciences. Our analyses show that the largest number of Data Papers were published in journals with an Impact Factor ranging from 5 to 6. Additionally, the largest number of Data Papers were published in the USA, China, the United Kingdom, Italy and France. From the point of view of scientists, this work is needed because scientists can check information about journals in which they may publish research data. Moreover, they can find Data Journals with a high Impact Factor and MEiN points. This analysis is also interesting because scientists/publishers can compare the disciplines and countries in which researchers have published the greatest number of Data Papers. Finally, it is worth noting that this work gives insights into the various bibliometric indicators related to citations and the number of publications. This information can be useful for people associated with bibliometric analyses.

Keywords:

data journals, data papers, research areas, bibliometric analysis

Details

Issue
Vol. 25 No. 4 (2021)
Section
Research article
Published
2021-12-30
DOI:
https://doi.org/10.34808/tq2021/25.4/p
Licencja:
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors

BEATA ADAMCZAK

Gdańsk University of Technology, Library 11/12 Gabriela Narutowicza 80-233 Gdańsk, Poland

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