What question did this study set out to answer?

Investigate how data scientists track exploratory variants in literate programming environments and determine user needs for future notebook version control systems.

April 19, 2018

The Story in the Notebook

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Authors

MKMary Beth KeryTaoyuan Chang Gung Memorial Hospital MRMarissa RadenskyUniversity of Washington MAMahima AryaIndian Institute of Technology Roorkee

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Implication

Mixed-methods study reveals versioning struggles and narrative curation patterns in data scientists, highlighting the need for context-based notebook history tools.

Key Points

Investigate how data scientists track exploratory variants in literate programming environments and determine user needs for future notebook version control systems.
Conducted semi-structured interviews with 21 data scientists to observe coding habits, narrative creation, and history tracking.
Surveyed 45 data scientists on how they envision utilizing past code and experiment histories in future version control systems.
Both informal and formal versioning attempts aimed at maintaining experimentation history reduced notebook readability and complicated iteration.
Participants curated notebooks into narratives primarily by manipulating cell structures rather than authoring markdown explanations.
Data scientists expressed a preference for history retrieval mechanisms driven by contextual anchors, such as output images and parameter configurations.

Cite This Study

Kery et al. (2018) studied this question.

synapsesocial.com/papers/6a12a3ab45487b7639a6e5f2 https://doi.org/10.1145/3173574.3173748

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Implication

Mixed-methods study reveals versioning struggles and narrative curation patterns in data scientists, highlighting the need for context-based notebook history tools.

The Story in the Notebook

Discussion

Member takes

Implication

Key Points

Cite This Study

The Story in the Notebook

Discussion

Member takes

Implication

Key Points

Cite This Study

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