|November 7, 2019|
|09:00—09:15||Welcome and opening remarks from the Dean|
What is Globus? How does Globus work? How is it used in the life sciences? We will explore these topics in more in this introduction to enabling large scale biomedical research with secure and reliable data movement and sharing with Globus.
We will demonstrate Globus capabilities from the perspectives of an end-user researcher with a focus on bio-science. This is an introduction to the many features of the Globus web application. You will learn how to move 'omics data, to and from your laptop, your lab, your computing center and the cloud. You will learn how to use Globus to share data with your research team and your collaborators, and move data to other labs and processing centers.
The Standard Globus subscription provides a secure, unified interface to your research data. Use Globus to 'fire and forget' high-performance data transfers directly between systems within and across organizations. No “traversing the cloud” necessary. Need to manage HIPAA-regulated data? Working with PII or CUI? No problem. Globus supports higher assurance levels for managing restricted data, researchers can easily work with this data and share it securely and appropriately with collaborators, while meeting compliance requirements.
We will provide a detailed walkthrough of installing and configuring a Globus endpoint. We will also review deployment configurations such as multi-server data transfer nodes, using the management console with pause/resume rules, and integrating identity systems for streamlined user authentication. We will discuss connectors to storage systems such as S3, Ceph, HPSS, and Google Drive. You will get to experiment with server endpoint installation using a virtual machine.
We will demonstrate how you can incorporate Globus capabilities into your own data portals, science gateways, Jupyter notebooks and other web applications that support data-intensive research.
We will review common use cases and demonstrate how the Globus command line interface (CLI) may be used to automate repetitive data management tasks. We will also provide specific examples to instruct users how to automate scripted transfers to/from endpoints, and how to have a script return an inventory of data stored on an endpoint.