Maitner Brian, Santos Andrade Paul Efren, Lei Luna, Kass Jamie, Owens Hannah L, Barbosa George C G, Boyle Brad, Castorena Matiss, Enquist Brian J, Feng Xiao, Park Daniel S, Paz Andrea, Pinilla-Buitrago Gonzalo, Merow Cory, Wilson Adam
Department of Integrative Biology University of South Florida St. Petersburg Florida USA.
Department of Geography University at Buffalo Buffalo New York USA.
Ecol Evol. 2024 Aug 27;14(8):e70030. doi: 10.1002/ece3.70030. eCollection 2024 Aug.
Biologists increasingly rely on computer code to collect and analyze their data, reinforcing the importance of published code for transparency, reproducibility, training, and a basis for further work. Here, we conduct a literature review estimating temporal trends in code sharing in ecology and evolution publications since 2010, and test for an influence of code sharing on citation rate. We find that code is rarely published (only 6% of papers), with little improvement over time. We also found there may be incentives to publish code: Publications that share code have tended to be low-impact initially, but accumulate citations faster, compensating for this deficit. Studies that additionally meet other Open Science criteria, open-access publication, or data sharing, have still higher citation rates, with publications meeting all three criteria (code sharing, data sharing, and open access publication) tending to have the most citations and highest rate of citation accumulation.
生物学家越来越依赖计算机代码来收集和分析数据，这凸显了已发表代码对于透明度、可重复性、培训以及进一步研究基础的重要性。在此，我们进行了一项文献综述，估算自2010年以来生态与进化领域出版物中代码共享的时间趋势，并测试代码共享对引用率的影响。我们发现代码很少被发表（仅占论文的6%），且随着时间推移改善甚微。我们还发现可能存在发表代码的激励因素：共享代码的出版物起初影响力往往较低，但累积引用速度更快，弥补了这一不足。另外符合其他开放科学标准（开放获取出版或数据共享）的研究，其引用率更高，同时符合所有三项标准（代码共享、数据共享和开放获取出版）的出版物往往拥有最多的引用和最高的引用累积率。
