This hands-on, 90-minute tutorial explores the capabilities provided by Globus for assembling, describing, publishing, identifying, searching, and discovering datasets. Attendees will learn how to integrate new Globus data publication platform services into their institutional repository and data publication workflows. The tutorial will teach users to create flexible, end-to-end publication workflows in Python. We will provide a hosted Jupyter environment in which users can develop and execute publication workflows without deploying any code locally. - Recommended Skill Level: The tutorial is intended for developers of Web applications or science gateways but it is appropriate for all experience levels. All code necessary to complete the exercises is provided in Jupyter notebooks and we will provide detailed documentation and Python Software Development Kit (SDK) to support use of the platform. Instructions for the exercises are explicit and detailed. - Prerequisites: The tutorial will be conducted using Jupyter notebooks in Python. Participants are expected to be familiar with Python. No prior knowledge of Jupyter notebooks is required as we have found them to be intuitive for a wide range of tutorial participants. Familiarity logging into a Linux shell via SSH and using a Linux text editor (e.g., vi/vim, emacs, nano) may be helpful but is not required for success in the tutorial. - Requirements: Participants must bring their own WiFi-enabled device with Web browser and SSH client installed. (Linux and Macintosh systems do not require any additional software. Windows and ChromeOS systems must have an SSH client application installed.) We will provide a hosted JupyterHub environment via which participants can follow the tutorial. Participants who wish to follow the tutorial on their own device should install Python and Jupyter locally prior to attending the tutorial.
