NoteFlow: Recommending Charts as Sight Glasses for Tracing Data Flow in Computational Notebooks
Yuan Tian, Dazhen Deng, Sen Yang, Huawei Zheng, Bowen Shi, Kai Xiong,, Xinjing Yi, Yingcai Wu

TL;DR
NoteFlow is a notebook library that recommends adaptive charts as visual aids to help data analysts trace data flow and understand data transformations during exploratory data analysis, reducing cognitive load.
Contribution
It introduces a novel chart recommendation system that adapts to data transformations, enhancing data traceability in computational notebooks.
Findings
User studies show improved understanding of data flow.
Charts effectively convey data transformations.
Enhanced overview of EDA process.
Abstract
Exploratory Data Analysis (EDA) is a routine task for data analysts, often conducted using flexible computational notebooks. During EDA, data workers process, visualize, and interpret data tables, making decisions about subsequent analysis. However, the cell-by-cell programming approach, while flexible, can lead to disorganized code, making it difficult to trace the state of data tables across cells and increasing the cognitive load on data workers. This paper introduces NoteFlow, a notebook library that recommends charts as ``sight glasses'' for data tables, allowing users to monitor their dynamic updates throughout the EDA process. To ensure visual consistency and effectiveness, NoteFlow adapts chart encodings in response to data transformations, maintaining a coherent and insightful representation of the data. The proposed method was evaluated through user studies, demonstrating its…
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Taxonomy
TopicsAdvanced Database Systems and Queries · Data Management and Algorithms · Data Mining Algorithms and Applications
