Code Code Evolution: Understanding How People Change Data Science Notebooks Over Time
Code Code Evolution: Understanding How People Change Data Science Notebooks Over Time
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代码代码演变：了解人们如何随着时间的推移改变数据科学笔记本
DOI：
10.1145/3544548.3580997
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
L. Battle
中科院分区：
文献类型：
--
作者：
Deepthi Raghunandan;Aayushi Roy;Shenzhi Shi;N. Elmqvist;L. Battle
语义构建是识别、提取和解释数据见解的迭代过程，其中每次迭代都被称为“语义构建循环”。然而，在这个过程中，我们对语义行为是如何从探索和解释演变而来的知之甚少。这种差距限制了我们理解语义构建的全部范围的能力，这反过来又抑制了支持该过程的工具的设计。我们贡献了第一个混合方法来描述在计算笔记本中如何演变的语义。我们通过识别经历了重要迭代的数据科学笔记本，研究了从GitHub挖掘的2,574个Jupyter笔记本，提出了一个自动表征语义活动的回归模型，并使用该回归模型来计算和分析GitHub版本之间活动的变化。我们的结果表明，随着时间的推移，笔记本作者参与了各种意义生成任务，例如注释、分支分析和文档。我们用我们的见解为当前的笔记本环境推荐扩展。
Sensemaking is the iterative process of identifying, extracting, and explaining insights from data, where each iteration is referred to as the “sensemaking loop.” However, little is known about how sensemaking behavior evolves from exploration and explanation during this process. This gap limits our ability to understand the full scope of sensemaking, which in turn inhibits the design of tools that support the process. We contribute the first mixed-method to characterize how sensemaking evolves within computational notebooks. We study 2,574 Jupyter notebooks mined from GitHub by identifying data science notebooks that have undergone significant iterations, presenting a regression model that automatically characterizes sensemaking activity, and using this regression model to calculate and analyze shifts in activity across GitHub versions. Our results show that notebook authors participate in various sensemaking tasks over time, such as annotation, branching analysis, and documentation. We use our insights to recommend extensions to current notebook environments.
探索的路径、省略的路径、模糊的路径：决策点
DOI：
10.1145/3313831.3376533
发表时间：
2020
期刊：
Human factors in computing systems
影响因子：
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作者：
Liu, Tang;Althoff, Tim;Heer, Jeffrey
通讯作者：
Heer, Jeffrey
数据科学家如何使用计算笔记本进行实时协作
影响因子：
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作者：
Wang, April Yi;Mittal, Anant;Brooks, Christopher;Oney, Steve
通讯作者：
Oney, Steve