Jupyter Meets the Earth: Community input
A virtual meeting to be held on Monday July 27 at 8am - 10am PDT Register Here
Project Jupyter is an open source platform for interactive computing and data analysis, widely used in research, education and industry. The Jupyter meets the Earth project is using research use cases in geosciences to drive technical developments within the Jupyter and Pangeo ecosystems. This project revolves around the following key goals: (1) Facilitate the discovery, integration, and effective use of the diverse sources of data in the geosciences. (2) Empower researchers to utilize modern, scalable compute resources. (3) Accelerate the process of discovery by enabling researchers to rapidly create and deploy custom interactive applications tailored to the research question at hand. (4) Make it possible to communicate scientific results in a manner that is tailored to the final consumers of research – be they other scientists, policy makers, students, or the general public.
Our technical targets include improvements in JupyterHub for interactive computing on High Performance Computing (HPC) and cloud infrastructure, the development of JupyterLab extensions for data discovery, and contributions to widgets and dashboarding solutions for researchers to easily create graphical user interfaces as well as interactive documents to share analyses with broad audiences. You can find more information about the project at https://bit.ly/jupytearth.
We would like to gather input for how to best serve your research needs, exploring questions such as:
- What are current bottlenecks in your interactive computing workflow?
- What integrations with geoscience-specific tools would be useful, or could be made better via closer ties with Jupyter infrastructure?
- How would you like to publish and share your computational research and where can improvements be made (e.g. Binder, JupyterBook, etc.)?
- Desktop vs local cluster vs HPC vs cloud: what is your workflow today? What do you envision it will be in 5 years?
- Where are the pain points in working with your data on shared infrastructure (cloud or HPC)? Data discovery? Sharing data with collaborators? …
Whether you are an active participant in the Pangeo community, you use Jupyter tools in your work, or are considering adopting some of these tools, we welcome your input and ideas.