计算可重复性的成功和扎:从脆弱家庭挑战中吸取教训
David M Liu1, Matthew J Salganik1
1Princeton University, Princeton, NJ, USA.
概括
在研究中实现计算可重复性是具有挑战性的. 这项研究引入了软件容器和云计算来标准化研究环境,提高了使用原始数据和代码重建研究结果的能力.
科学领域:
- 计算社会科学 计算社会科学
- 研究方法研究方法论.
- 数据科学是数据科学.
背景情况:
- 可复制性对于科学完整性至关重要.
- 计算可重复性,即用原始数据和代码重建结果,仍然是研究人员面临的实际挑战.
- "脆弱家庭挑战"强调了需要强大的可复制性方法的需要.
研究的目的:
- 为提升学术研究中的计算可重复性提出一个实用的方法.
- 展示软件工程工具用于可重复的科学研究的应用.
- 为了便于复制"社会"杂志关于脆弱家庭挑战的12篇文章中的发现.
主要方法:
- 使用软件容器 (例如Docker) 来标准化计算环境.
- 利用云计算平台 (例如亚马逊网络服务) 来实现可扩展和一致的研究执行.
- 将这些工具应用于"脆弱家庭挑战"特别号的12篇研究文章中.
主要成果:
- 成功地为每个提交的文章标准化了计算环境.
- 为脆弱家庭挑战研究提供了更容易的计算可重现性.
- 在学术研究中展示了使用专业软件工程工具的可行性.
结论:
- 软件容器和云计算显著提高了计算可重现性.
- 为研究人员和期刊提供建议,以便在未来的研究中采用这些工具.
- 标准化环境确保了研究的完整性,并促进了未来的科学进步.
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