Welcome to the Jupyter at Research Facilities group!

There are a wide range of research facilities (such as X-ray light sources, astronomical observatories, genetics centers, etc.) that are users or potential users of the Jupyter ecosystem to support their research. Such facilities have some common needs in the Jupyter ecosystem:

1. Large data sets that are expensive to produce and prohibitive to transport need to be stored and analyzed for long periods of time. Often these data sets must be analyzed remotely.

2. Large computational resources (such as clusters or supercomputers) need to be scheduled and shared among facility users and accessed remotely.

3. Remote teams need to work in collaboration with facility personnel or on-site team members to collect and analyze data. This includes both interactive collaboration as the data is being collected and analysis long after the data has been collected.

4. Reproducible computational results, including narrative, data, code, and output, need to be stored and accessible remotely for potentially long periods of time.

5. Results need to be converted to formats suitable for publication and sharing with the broader community.

In this group, we welcome questions and discussions relating to the use of Jupyter at research facilities (also commonly called "user facilities") to address these and other needs.

Correct Citation for Jupyter[Lab]

Ivan Calitz Crockart