CyVerse Discovery Environment GitHub (open source)
About this Webinar
Since its inception, CyVerse has focused on building our platform to enable data-driven discovery and give you the tools and services you need to do your collaborative research, manage your data at each step of the data lifecycle, and facilitate scientific reproducibility for more robust, open science.
And now, we are proud to preview in this webinar CyVerse's new User Interface (UI) for the Discovery Environment, which is so much more than just another pretty face! Without losing the same key operations available for Data, Apps and Analyses, we've completely redesigned the UI to make doing your online research tasks easier, including getting help when and where you need it and the ability to use CyVerse on your mobile devices. Find out all the cool new ways CyVerse is transforming science!
We are also seeking users who would like to beta-test the UI. If you're interested, please contact us at firstname.lastname@example.org.
What You'll Learn
- How to navigate the new User Interface of the Discovery Environment
- New features that make using CyVerse even easier
- What CyVerse features and functions you can access using a mobile device
- When the new UI will be operational
- When the current system will sunset
User Skill Level
About the Presenter
A graduate of The University of Arizona, Sriram Srinivasan joined CyVerse in 2009 after completing his degree and now leads CyVerse's Core Software team. Starting out as an application programmer, he worked closely with our early community members to understand scientists' needs for using research cyberinfrastructure, and helped translate those requirements into platform features and services that now support their ability to use CyVerse for the entire data-research lifecycle. Sriram and his team, along with CyVerse Designer-Developer Mariah Wall, have been working on the new User Interface for over a year and are eager to show off the Discovery Environment's new features and functionality that will make doing data-driven, reproducible science even more efficient.