[this isn't very concrete, needs the JupyterLab beta example?] NERSC's annual survey feedback from users about Jupyter tends to be highly appreciative. By and large, the user base is forgiving about our experimental efforts and mis-steps with Jupyter because they understand the long-term benefit. Innovation in the data science stack is something that data scientists seem to be prepared for: Often users find solutions or give us advice about issues with Jupyter. Proactive communication with users about Jupyter plans, status, and feedback actually seem to help cultivate user tolerance for experimentation with new features the need arises.
Probably the most important lesson learned that we can share, especially to other HPC centers, is that building support for Jupyter within an institution that provides supercomputing power takes data, persuasion, and management that sees the benefits of expanded access through rich user interfaces like Jupyter. We have been able to expand support for Jupyter from just one shared node on Cori to four plus batch nodes (requiring consensus from many internal stakeholders) through plots like Figure \ref{952831} that management can digest and project forward. Users with a direct line to federal research agency stakeholders like program managers are a potential source of external motivation and support.
HPC community building and collaboration. HPC community building and collaboration.