Tian-Yuan Huang | Searcharxiv

arXiv2023

An empirical exploration of the diversified R ecosystem

Born in the late 20s, R is one of the most popular software for statistical computing and graphics. With the development of information technology and the advent of the big data era, great changes have taken place in the R ecosystem. Based on the meta information of the Comprehensive R Archive Network (CRAN) and the bibliometric data of literature citing R, we discovered that while R is initiated by statistics, its development is benefited greatly from computer science and the main user group in academics come from various disciplines such as agricultural science, biological science, environmental science and medical science. In addition, we displayed the collaboration patterns among R developers and analyze the possible effects of collaboration in the R community.

stat.OT↗

arXiv2022

Eddy Covariance: A Scientometric Review (1981-2018)

The history of eddy covariance (EC) measuring system could be dated back to 100 years ago, but it was not until the recent decades that EC gains popularity and being widely used in global change ecological studies, with explosion of related work published in papers from various journals. Investigating 8297 literature related with EC from 1981 to 2018, we make a comprehensive and critical review of scientific development of EC from a scientometric perspective. First, the paper outlines general bibliometric statistics, including publication number, country contribution, productive institutions, active authors, journal distribution, highly cited articles and fund support, to provide an informative picture of EC studies. Second, research trends are revealed by network visualization and modeling based on keyword analysis, from where we could discover the knowledge structure of EC and detect the research focus and hotspots transitions at different periods. Third, collaboration in EC research community has been explored. FLUXNET is the largest global network uniting EC researchers, here we have quantified and evaluated its performance by using bibliometric indicators of cooperation and citation. Specific discussions have been given to the historical development of EC, including technical maturation and application promotion. Considering the current barrier for collaboration, the review closes by analyzing the reasons hindering data sharing and makes a prospect of new models for data-intensive collaboration in the future.

cs.DL↗