4.6 Article

R programming environment in wildlife: Are Veterinary Sciences at the same level than other research areas?

期刊

RESEARCH IN VETERINARY SCIENCE
卷 166, 期 -, 页码 -

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ELSEVIER SCI LTD
DOI: 10.1016/j.rvsc.2023.105079

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Analysis; R software; R-packages; Methodology; Statistics; Wildlife

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The study evaluated the use of R software in research articles addressing the study of wildlife, showing an increasing trend in the number of publications over time and a wide geographical distribution globally.
The computing environment has revolutionized the management and analysis of data in sciences during the last decades. This study aimed to evaluate the use of R software in research articles addressing the study of wildlife worldwide, particularly focusing on the research area Veterinary Sciences. For this purpose, a systematic review mainly performed in the Web of Science database was conducted. Out of a total of 509 articles reviewed, our results show an increasing trend of the number of publications using the R software over time, as well as a wide geographical distribution at a global scale, particularly in North America, Europe, Australia and China. Most publications were categorized in research areas related to Biological Sciences, while a minority of them was included in Veterinary Sciences (5.9%; 30/509). About the species groups assessed, many articles evaluated a single species group (96.5%), being mammals (50.7%) and birds (14.8%) the most studied ones. The present study showed a high variety of R-packages used in the publications reviewed, all of them related to data analysis, the study of genetic/phylogenetic information and graphical representation. Interestingly, the common use of packages between different research areas is indicative of the high interest of using R software in scientific articles. Our study points the R software as an open-source programming language that allows to support research addressing the study of wildlife, becoming a key software for many research areas, including Veterinary Sciences. However, an in-depth methodological description about the use of R software in publications to improve the tracking, reproducibility and transparency is encouraged.

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