Enabling Collaborative Data Science Development with the Ballet Framework
Micah J. Smith, Jürgen Cito, Kelvin Lu, Kalyan Veeramachaneni
Paper appears method- or tooling-adjacent to AI workflows with partial ecosystem coverage.
While the open-source software development model has led to successful large-scale collaborations in building software systems, data science projects are frequently developed by individuals or small teams. We describe challenges to scaling data science collaborations and present a conceptual framework and ML programming model to address them. We instantiate these ideas in Ballet, the first lightweight framework for c ...
ollaborative, open-source data science through a focus on feature engineering, and an accompanying cloud-based development environment. Using our framework, collaborators incrementally propose feature definitions to a repository which are each subjected to software and ML performance validation and can be automatically merged into an executable feature engineering pipeline. We leverage Ballet to conduct a case study analysis of an income prediction problem with 27 collaborators, and discuss implications for future designers of collaborative projects.
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While the open-source software development model has led to successful large-scale collaborations in building software systems, data science projects are frequently developed by individuals or small teams.
Implementation Evidence Summary
eugeneyan/applied-ml is the closest maintained adjacent implementation (Matches contextual method/domain keyword: data science). It is not paper-verified; validate algorithm and evaluation setup against the paper before trusting reported metrics. Community adoption signal: 29736 GitHub stars.
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Utility signals: depth 70/100, grounding 75/100, status medium.
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Matches contextual method/domain keyword: data science
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Research context
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Citations
109
References
Tasks
Computer science, Data science, Pipeline (software), Feature (linguistics), Executable, Software engineering, Software, Focus (optics)
Methods
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Domains
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