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Vas Vasiliadis, University of Chicago, Argonne National Laboratory
Lee Liming, University of Chicago , Argonne National Laboratory
April 5, 2022 - 10:00 to 1:40 CDT


Globus will be presenting a two-part tutorial in this year's conference.

Advanced Computing Meets Data FAIRness

Building Science Gateways with the Django Globus Portal Framework

The broad scope of a typical science gateway—to simplify access to shared data, computing and other resources—makes building such a gateway from scratch a daunting task. Investigators must be able to stage data from instruments (or other sources), submit compute jobs to analyze data, move data to more persistent storage, describe data products, and provide a means for collaborators to search, discover, reuse and augment these data products. Myriad tools are available to enable all these tasks but integrating them in a way that hides the complexity from users, is a challenge.

In this tutorial we will describe an approach that bootstraps science gateway development based on the Modern Research Data Portal[1] design pattern. The solution uses a set of open source tools that build on the established Django web framework, the ubiquitous OAuth2/OpenID connect standards for authentication/authorization, the widely deployed Globus service for research data management, and the nascent funcX functions-as-a-service platform. Attendees will learn how to rapidly deploy a science gateway that enables both automated computation at scale and data enhanced discovery of resulting data products. The emphasis will be on automating many of the required tasks so that gateway developers can focus on building differentiated, discipline-specific functionality rather than low-value—yet critical—supporting infrastructure.

We will use the ALCF Community Data Co-Op as an exemplar to illustrate how these tools have been used to support large-scale collaborative research. We will describe the overall solution architecture and introduce attendees to the individual tools. Attendees will then use these tools to deploy and configure their own science gateway to support image analysis, description, indexing and search. 
The tutorial will comprise a mix of lectures, demonstration and hands-on exercises. Virtual machines will be provided for computation and for hosting the science gateway. The objective is for attendees to develop a high-level understanding of the various components and leave with working code that can serve as the starting point for their own science gateway implementation.

Recommended skill level: intermediate/advanced; Prerequisites: familiarity with Python, ability to SSH into remote virtual machines, and a modern web browser.