论文标题
Boba：创作和可视化多元宇宙分析
Boba: Authoring and Visualizing Multiverse Analyses
论文作者
论文摘要
多元宇宙分析是一种数据分析的方法，在该方法中，所有“合理”的分析决策并行评估，并集体解释，以增强鲁棒性和透明度。但是，指定多元宇宙的要求是要求的，因为分析师必须从分析决策的交叉产品中管理众多变体，并且结果需要细微的解释。我们贡献Boba：一种集成域特异性的语言（DSL）和用于创作和审查多元宇宙分析的视觉分析系统。借助Boba DSL，分析师仅将分析代码的共享部分编写一次，以及定义替代决策的本地变化，编译器从中生成代表所有可能的分析路径的脚本的多重脚本。 Boba可视化器提供了模型结果和多元宇宙决策空间的链接视图，以实现对结果决策和鲁棒性的快速，系统的评估，包括对不确定性和模型拟合进行采样。我们通过两个数据分析案例研究证明了Boba的实用性，并反思了多元宇宙分析软件的挑战和设计机会。
Multiverse analysis is an approach to data analysis in which all "reasonable" analytic decisions are evaluated in parallel and interpreted collectively, in order to foster robustness and transparency. However, specifying a multiverse is demanding because analysts must manage myriad variants from a cross-product of analytic decisions, and the results require nuanced interpretation. We contribute Boba: an integrated domain-specific language (DSL) and visual analysis system for authoring and reviewing multiverse analyses. With the Boba DSL, analysts write the shared portion of analysis code only once, alongside local variations defining alternative decisions, from which the compiler generates a multiplex of scripts representing all possible analysis paths. The Boba Visualizer provides linked views of model results and the multiverse decision space to enable rapid, systematic assessment of consequential decisions and robustness, including sampling uncertainty and model fit. We demonstrate Boba's utility through two data analysis case studies, and reflect on challenges and design opportunities for multiverse analysis software.
