Tidynote: Always-Clear Notebook Authoring

2026-02-26

AI Summary

This work addresses the persistent lack of clarity support in current computational notebooks during exploratory programming, which often leads to disorganized code and ambiguous execution states. To tackle this issue, the authors propose a novel “always-clear” notebook interaction paradigm that introduces a dedicated side drafting area, bidirectionally movable cells, and a linear execution model supporting state forking. This design preserves the flexibility of exploratory workflows while ensuring overall structural clarity. Implemented on top of Jupyter, the system integrates a movable-cell architecture with program-state forking mechanisms. A user study with 13 participants demonstrates that the approach significantly enhances notebook clarity throughout its entire lifecycle, effectively supports real-world data analysis tasks, and fosters new strategies for maintaining clarity.

Technology Category

• Natural Language Processing: Interpretability, Analysis, and Evaluation of NLP Models
• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Humans and AI: Intelligent User Interfaces

Application Category

• Security and Privacy: Data transparency and provenance
• Responsible Web: Algorithmic accountability and transparency on the web
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Recent work identified clarity as one of the top quality attributes that notebook users value, but notebooks lack support for maintaining clarity throughout the exploratory phases of the notebook authoring workflow. We propose always-clear notebook authoring that supports both clarity and exploration, and present a Jupyter implementation called Tidynote. The key to Tidynote is three-fold: (1) a scratchpad sidebar to facilitate exploration, (2) cells movable between the notebook and the scratchpad to maintain organization, and (3) linear execution with state forks to clarify program state. An exploratory study (N=13) of open-ended data analysis tasks shows that Tidynote features holistically promote clarity throughout a notebook's lifecycle, support realistic notebook tasks, and enable novel strategies for notebook clarity. These results suggest that Tidynote supports maintaining clarity throughout the entirety of notebook authoring.

Problem

• notebook clarity
• exploratory workflow
• Jupyter notebooks
• code organization
• program state

Innovation

• always-clear notebook authoring
• scratchpad sidebar
• state forks
• notebook clarity
• exploratory programming