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The official Jupyter Conference
Aug 21-22, 2018: Training
Aug 22-24, 2018: Tutorials & Conference
New York, NY

"If the data will not come to the astronomer. . .": JupyterLab and a sea change in astronomical analysis

Adam Thornton (LSST)
11:55am–12:35pm Thursday, August 23, 2018

Who is this presentation for?

  • Those engaged in scientific disciplines

Prerequisite knowledge

  • No knowledge of JupyterHub, JupyterLab, or Kubernetes required

What you'll learn

  • See how the combination of JupyterLab, JupyterHub, and Kubernetes can provide a foundation for enabling analysis of very large datasets
  • Explore the LSST project to map the sky


LSST is an ambitious project to map the sky in the fastest, widest, and deepest survey ever made. The project’s petabyte-scale, 7 trillion-row database disrupts traditional astronomical workflows, and its science platform requires a paradigm shift in how astronomy is done. Adam Thornton discusses the challenges of providing production services on a notebook-based architecture and the compelling advantages of JupyterLab.

Topics include:

  • A brief overview of the mission of the Large Synoptic Survey Telescope (LSST) and the scale and scope of the data it will collect
  • How data analysis has typically been done in the astronomical community and why traditional methods can’t enable researchers to efficiently analyze the enormous quantities of data that will be produced
  • How adopting a new model, based on the combination of JupyterLab, JupyterHub, and Kubernetes, allows a path forward for rapid exploration of the data and publication-quality science analysis
  • A description of the project’s architectural choices, including the critical role of JupyterLab in enabling the necessary features of this platform
  • LSST team members’ very positive experiences as early JupyterLab adopters and occasional contributors
Photo of Adam Thornton

Adam Thornton


Adam Thornton is a software developer for the Large Synoptic Survey Telescope, where he focuses on data management, science quality, and reliability engineering and is working on the JupyterLab-based interactive component of the LSST science platform. He has nearly 30 years of development, IT consulting, and system administration experience in a wide variety of settings, from academic computing to Fortune 20 enterprises.