Abstract
This study presents a comprehensive bibliometric analysis of the paper published by John Aitchison in the Journal of the Royal Statistical Society. Series B (Methodological) in 1982. Having recently reached the milestone of 35 years since its publication, this pioneering paper was the first to illustrate the use of the methodology "Compositional Data Analysis" or "CoDA". By October 2019, this paper had received over 780 citations, making it the most widely cited and influential article among those using said methodology. The bibliometric approach used in this study encompasses a wide range of techniques, including a specific analysis of the main authors and institutions to have cited Aitchison' paper. The VOSviewer software was also used for the purpose of developing network maps for said publication. Specifically, the techniques used were co-citations and bibliographic coupling. The results clearly show the significant impact the paper has had on scientific research, having been cited by authors and institutions that publish all around the world.
Highlights
Nowadays compositional data are defined as arrays of strictly positive numbers for which ratios between them are considered to be relevant (Egozcue and Pawlowsky-Glahn (2019))
The third event that seems to have facilitated the expansion of CoDA consists in the development of multiple libraries with R (Van den Boogaart and Tolosana-Delgado (2013), Palarea-Albaladejo and Martın-Fernandez (2015) and Filzmoser et al (2018)) and the creation of various softwares, such as the CoDaPack (Thio-Henestrosa and Martın-Fernandez (2005) and Comas-Cufı, Thio-Henestrosa, Egozcue, Tolosana-Delgado, and Ortego (2011)), which allows operations to be performed without any previous knowledge of programming
To celebrate 35 years since publication of the seminal article on CoDa analysis “The Statistical Analysis of Compositional Data” (Aitchison (1982)), the main purpose of this paper is to carry out an exhaustive bibliometric analysis of all publications to have cited the paper based on data taken from the Web of Sciences (WoS)
Summary
Nowadays compositional data are defined as arrays of strictly positive numbers for which ratios between them are considered to be relevant (Egozcue and Pawlowsky-Glahn (2019)). The scientific production related to compositional data analysis has increased constantly over the years, and in the last ten years especially started to flourish in very different fields to the ones where it was initially employed (Kogovsek, Coenders, and Hlebec (2013), Ferrer-Rosell, Coenders, and Martınez-Garcia (2015), Batista-Foguet, Ferrer-Rosell, Serlavos, Coenders, and Boyatzis (2015), Belles-Sampera, Guillen, and Santolino (2016), Morais, Thomas-Agnan, and Simioni (2018), Blasco-Duatis, Coenders, Saez, Garcıa, and Cunha (2019), Creixans-Tenas, Coenders, and Arimany-Serrat (2019), Carreras Simo and Coenders (2020) and Coenders and Ferrer-Rosell (2020)) This growth and expansion to new fields can be related to four identifiable events. The information we expect to gather from the analysis should answer the following research questions (RQ):
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