Packaging code for reproducible research in the public sector
Packaging code for reproducible research in the public sector
复制标题
公共部门可重复研究的包装规范
DOI：
10.48550/arxiv.2305.16205
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
A. Turrell
中科院分区：
文献类型：
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作者：
Federico Botta;R. Lovelace;Laura Gilbert;A. Turrell
有效和合乎道德地使用数据为决策提供信息，为公共部门提供了巨大的价值，特别是在通过透明、可重复和强大的数据处理工作流程提供数据时。政府释放这种价值的一种方式是公开他们的数据，让更多的人和组织获得洞察力。然而，开放数据在许多情况下是不够的：公开可用的数据集需要以可供分析的形式从流行的数据科学工具(如R和Python)中访问，才能实现其全部潜力。本文通过一个包装代码的案例研究，探索如何最大限度地发挥开放数据的影响，以促进可重复性分析。我们介绍了由英国交通部发布的jtstats项目，该项目由R和Python包组成，用于导入、处理和可视化表示旅行时间的大型复杂数据集，用于多种模式和多个地理级别的目的。Jtstats展示了特定领域的包如何能够在公共部门内外实现可重复的研究，从而节省重复的工作并降低重复分析的错误风险。我们希望jtstats项目鼓励其他人，特别是公共部门的人，通过使他们的数据集更容易获得来增加他们的数据集的价值。
The effective and ethical use of data to inform decision-making offers huge value to the public sector, especially when delivered by transparent, reproducible, and robust data processing workflows. One way that governments are unlocking this value is through making their data publicly available, allowing more people and organisations to derive insights. However, open data is not enough in many cases: publicly available datasets need to be accessible in an analysis-ready form from popular data science tools, such as R and Python, for them to realise their full potential. This paper explores ways to maximise the impact of open data with reference to a case study of packaging code to facilitate reproducible analysis. We present the jtstats project, which consists of R and Python packages for importing, processing, and visualising large and complex datasets representing journey times, for many modes and purposes at multiple geographic levels, released by the UK Department of Transport. jtstats shows how domain specific packages can enable reproducible research within the public sector and beyond, saving duplicated effort and reducing the risks of errors from repeated analyses. We hope that the jtstats project inspires others, particularly those in the public sector, to add value to their data sets by making them more accessible.