mage: Fluid Moves Between Code and Graphical Work in Computational Notebooks
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Abstract (arXiv)
We aim to increase the flexibility at which a data worker can choose the right tool for the job, regardless of whether the tool is a code library or an interactive graphical user interface (GUI). To achieve this flexibility, we extend computational notebooks with a new API mage, which supports tools that can represent themselves as both code and GUI as needed. We discuss the design of mage as well as design opportunities in the space of flexible code/GUI tools for data work. To understand tooling needs, we conduct a study with nine professional practitioners and elicit their feedback on mage and potential areas for flexible code/GUI tooling. We then implement six client tools for mage that illustrate the main themes of our study findings. Finally, we discuss open challenges in providing flexible code/GUI interactions for data workers.
Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Sep 2020.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 5; 2024: 4.
13 papers.
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- 2024Cocoa: Co-Planning and Co-Execution with AI Agentscited by 38
- 2023Data Formulator: AI-powered Concept-driven Visualization Authoringcited by 31
- 2023Model Compression in Practice: Lessons Learned from Practitioners Creating On-device Machine Learning Experiencescited by 21
- 2024Data Formulator 2: Iterative Creation of Data Visualizations, with AI Transforming Data Along the Waycited by 19
- 2022Symphony: Composing Interactive Interfaces for Machine Learningcited by 18
- 2021Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labelscited by 17
- 2024BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebookscited by 12
- 2022StickyLand: Breaking the Linear Presentation of Computational Notebookscited by 6
- 2024Talaria: Interactively Optimizing Machine Learning Models for Efficient Inferencecited by 6
- 2023SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebookscited by 3
- 2023MEGAnno: Exploratory Labeling for NLP in Computational Notebookscited by 2
- 2022Trinary Tools for Continuously Valued Binary Classifierscited by 0
1 more
- 2023Towards Multifaceted Human-Centered AIcited by 0
- 2024Cocoa: Co-Planning and Co-Execution with AI Agents14 Dec 2024
- 2024Data Formulator 2: Iterative Creation of Data Visualizations, with AI Transforming Data Along the Way28 Aug 2024
- 2024BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebooks10 Apr 2024
- 2024Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference3 Apr 2024
- 2023Model Compression in Practice: Lessons Learned from Practitioners Creating On-device Machine Learning Experiences6 Oct 2023
- 2023Data Formulator: AI-powered Concept-driven Visualization Authoring18 Sep 2023
- 2023SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebooks4 May 2023
- 2023Towards Multifaceted Human-Centered AI9 Jan 2023
- 2023MEGAnno: Exploratory Labeling for NLP in Computational Notebooks8 Jan 2023
- 2022Trinary Tools for Continuously Valued Binary Classifiers18 Apr 2022
- 2022StickyLand: Breaking the Linear Presentation of Computational Notebooks22 Feb 2022
- 2022Symphony: Composing Interactive Interfaces for Machine Learning18 Feb 2022
- 2024Cocoa: Co-Planning and Co-Execution with AI Agentscited by 38
- 2023Data Formulator: AI-powered Concept-driven Visualization Authoringcited by 31
- 2023Model Compression in Practice: Lessons Learned from Practitioners Creating On-device Machine Learning Experiencescited by 21
- 2024Data Formulator 2: Iterative Creation of Data Visualizations, with AI Transforming Data Along the Waycited by 19
- 2022Symphony: Composing Interactive Interfaces for Machine Learningcited by 18
- 2021Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labelscited by 17
- 2024BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebookscited by 12
- 2022StickyLand: Breaking the Linear Presentation of Computational Notebookscited by 6
- 2024Talaria: Interactively Optimizing Machine Learning Models for Efficient Inferencecited by 6
- 2023SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebookscited by 3
- 2023MEGAnno: Exploratory Labeling for NLP in Computational Notebookscited by 2
- 2022Trinary Tools for Continuously Valued Binary Classifierscited by 0
12 most cited of 13 All 13 (JSON)
- 2024Cocoa: Co-Planning and Co-Execution with AI Agents14 Dec 2024
- 2024Data Formulator 2: Iterative Creation of Data Visualizations, with AI Transforming Data Along the Way28 Aug 2024
- 2024BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebooks10 Apr 2024
- 2024Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference3 Apr 2024
- 2023Model Compression in Practice: Lessons Learned from Practitioners Creating On-device Machine Learning Experiences6 Oct 2023
- 2023Data Formulator: AI-powered Concept-driven Visualization Authoring18 Sep 2023
- 2023SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebooks4 May 2023
- 2023Towards Multifaceted Human-Centered AI9 Jan 2023
- 2023MEGAnno: Exploratory Labeling for NLP in Computational Notebooks8 Jan 2023
- 2022Trinary Tools for Continuously Valued Binary Classifiers18 Apr 2022
- 2022StickyLand: Breaking the Linear Presentation of Computational Notebooks22 Feb 2022
- 2022Symphony: Composing Interactive Interfaces for Machine Learning18 Feb 2022
12 newest of 13 All 13 (JSON)