JupyterCon 2018

August 21 – 24, 2018 (All Day)
  • TBA


At this year's JupyterCon, Globus Co-Founder and Argonne Data Science and Learning Division Director Ian Foster presented on Globus and Jupyter. View the slides here, or read details from the talk below:

  • TitleScaling Collaborative Data Science with Globus + Jupyter
  • Date: Thursday, August 23
  • Time: 11:05-11:45 a.m.
  • Abstract: Jupyter is rapidly becoming the platform of choice for interactive data science in academic and commercial labs alike. While existing data interfaces are sufficient for modest datasets, users often struggle when they need to deal with the large and increasingly distributed data generated by modern science. The Globus team at the University of Chicago develops and operates software as a service for data management that is used by over 75,000 researchers worldwide. The Globus platform provides high-speed, reliable file transfer, sharing, and data publication as well as a federated identity infrastructure that facilitates collaboration across diverse security domains and organizational boundaries, with all services accessible via browser, command line, and REST APIs. In this talk, Ian Foster explains how to use Globus and Jupyter to seamlessly access notebooks using existing institutional credentials, connect notebooks with data residing on disparate storage systems (including GPFS, Lustre, Amazon S3, and Google Drive), and make data securely available to business partners and research collaborators. Ian demonstrates the existing integration and shares plans for expanding the joint solution to utilize JupyterLab and other Globus capabilities that further advance data-driven collaboration at scale.

JupyterCon brings together data scientists, business analysts, researchers, educators, developers, and core Project contributors and tool creators for in-depth training, keynotes, networking events, and practical talks exploring the Project Jupyter platform. In just four days you’ll discover the best practices for collaborative and reproducible data science; new use cases, and the expertise you need to transform your workflow with Jupyter. For more information, visit the JupyterCon site.