Open Source

A key challenge in the open source space is that projects are often independent and autonomous, with relatively few formal ways to collaborate and coordinate efforts. While this usually isn’t a big deal, it means that there is a missed opportunity to grow the impact of an ecosystem because it requires coordinated development among multiple stakeholders within it.

In this post, we’re sharing our Commitment to Open Technology. It is focused on software licenses for reasons we’ll describe below. We hope that it clarifies what kind of licenses we’ll use, and assures our communities that we will not change our stance towards open source technology in the future.

A non-exhaustive list of things 2i2c and Development Seed did with the NASA VEDA project last quarter! Automated backups and alerting with jupyterhub-home-nfs # Tracking Issue jupyterhub-home-nfs is a young project to provide flexible per-user home directory limits on JupyterHub - an important feature for controlling cloud costs.

2i2c is pleased to announce the frx-challenges project, a new open source tool to help communities host data challenges on shared infrastructure: 2i2c-org/frx-challenges This project aims to make it easier for administrators to provide a service that enables users to submit code and data that are evaluated on secure infrastructure with access to private data and resources.

On most research oriented JupyterHub installations, users would like to customize their server (the environment, resources available, etc) after logging in. In Kubernetes based JupyterHub environments, a profile list provides this functionality.

Cross-posted from the Jupyter Book blog. Note that some MyST functionality is not supported on the 2i2c website – please see the original post for previews. Over the last ten months, the Jupyter Book team have been hard at work; Jupyter Book has become a Jupyter subproject, and the team1 announced a plan to release Jupyter Book 2.

Our partner OpenScapes recently took a trip to the White House to advocate for Open Science and the Open Source ecosystem, check out their blog post about the experience.

The DeepLabCut Team # Animal pose estimation using deep neural networks. Courtesy of the DeepLabCut Jupyter Book The DeepLabCut team is a group of researchers and developers who are working on open source tools for analyzing animal pose estimation by training deep neural networks on videos.

Thank you to Sajjad Anwar and Sanjay Bhangar for contributing to this post. The VEDA dashboard The 2i2c team are proud to continue our strong working collaboration with Development Seed, following our previous work on launching the US GHG center (also see the Development Seed blog post).

The HHMI Spyglass tutorial Spyglass # Spyglass is a framework for reproducible and shareable neuroscience research produced by Loren Frank’s lab at the University of California, San Francisco. Check out our blog post about the release of their preprint to read more about the methods.