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A taxonomy for reproducible and replicable research in environmental modelling
Environmental Modelling & Software ( IF 4.8 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.envsoft.2020.104753
Bakinam T. Essawy , Jonathan L. Goodall , Daniel Voce , Mohamed M. Morsy , Jeffrey M. Sadler , Young Don Choi , David G. Tarboton , Tanu Malik

Despite the growing acknowledgment of reproducibility crisis in computational science, there is still a lack of clarity around what exactly constitutes a reproducible or replicable study in many computational fields, including environmental modelling. To this end, we put forth a taxonomy that defines an environmental modelling study as being either 1) repeatable, 2) runnable, 3) reproducible, or 4) replicable. We introduce these terms with illustrative examples from hydrology using a hydrologic modelling framework along with cyberinfrastructure aimed at fostering reproducibility. Using this taxonomy as a guide, we argue that containerization is an important but lacking component needed to achieve the goal of computational reproducibility in hydrology and environmental modelling. Examples from hydrology are provided to demonstrate how new tools, including a user-friendly tool for containerization of computational analyses called Sciunit, can lower the barrier to reproducibility and replicability in the environmental modelling community.



中文翻译:

用于环境建模中可再现和可复制研究的分类法

尽管越来越多地认识到计算科学中的可再现性危机,但是在包括环境建模在内的许多计算领域中,究竟是什么构成可再现性或可复制性研究仍缺乏明确性。为此,我们提出了一个分类法,将环境建模研究定义为1)可重复,2)可运行,3)可复制或4)可复制。我们使用水文建模框架以及旨在促进可重复性的网络基础设施,从水文学的说明性示例中引入这些术语。以此分类法为指导,我们认为容器化是实现水文学和环境建模中计算可重复性目标所需的重要但缺少的组件。提供了水文学方面的示例,以演示如何使用新工具,

更新日期:2020-06-01
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