波巴：创作和可视化多元宇宙分析
Boba: Authoring and Visualizing Multiverse Analyses
摘要：
多元宇宙分析是一种数据分析方法，其中所有“合理”的分析决策都被并行评估和集体解释，以促进稳健性和透明度。然而，指定一个多元宇宙是要求很高的，因为分析师必须管理来自分析决策的交叉产品的无数变体，并且结果需要细致入微的解释。我们贡献波巴：一个集成的领域特定语言（DSL）和可视化分析系统，用于创作和审查多元宇宙分析。使用Boba DSL，分析师只需编写一次分析代码的共享部分，以及定义替代决策的本地变体，编译器从中生成代表所有可能分析路径的脚本。Boba Visualizer提供了模型结果和多元宇宙决策空间的链接视图，以便快速、系统地评估相应的决策和鲁棒性，包括采样不确定性和模型拟合。我们通过两个数据分析案例研究展示了波巴的实用性，并反思了多重宇宙分析软件的挑战和设计机会。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
