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arXiv · 2212.03907

A Novel JupyterLab User Experience for Interactive Data Visualization

Abstract

In the Jupyter ecosystem, data visualization is usually done with "widgets" created as notebook cell outputs. While this mechanism works well in some circumstances, it is not well-suited to presenting interfaces that are long-lived, interactive, and visually rich. Unlike the traditional Jupyter notebook system, the newer JupyterLab application provides a sophisticated extension infrastructure that raises new design possibilities. Here we present a novel user experience (UX) for interactive data visualization in JupyterLab that is based on an "app" that runs alongside the user's notebooks, rather than widgets that are bound inside them. We have implemented this UX for the AAS WorldWide Telescope (WWT) visualization tool. JupyterLab's messaging APIs allow the app to smoothly exchange data with multiple computational kernels, allowing users to accomplish tasks that are not possible using the widget framework. A new Jupyter server extension allows the frontend to request data from kernels asynchronously over HTTP, enabling interactive exploration of gigapixel-scale imagery in WWT. While we have developed this UX for WWT, the overall design and the server extension are portable to other applications and have the potential to unlock a variety of new user activities that aren't currently possible in "science platform" interfaces.

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Peter K. G. Williams, Jonathan Carifio, Henrik Norman, A. David Weigel. 2022-12-07. A Novel JupyterLab User Experience for Interactive Data Visualization. https://arxiv.org/abs/2212.03907

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