Series A Workshops (Hybrid, In-Person)
Series A Workshop(s) Purpose
NASA is studying best practices and capabilities for future architecture and computational requirements to meet its Open-Source Science policies. Identified best practices and capabilities will inform plans for transitioning to a Data and Compute Infrastructure that supports Open-Source Science policies.
The main study interest is how a coordinated cloud and High-End Computing (HEC) infrastructure could meet the data and computing needs of the Science Mission Directorate (SMD), including scientific workloads in data processing, analytics, modeling and simulation, and AI/ML, while ensuring that the infrastructure enables Open Science practices.
Key Areas of Interest
We will identify User Needs and Business Needs that should drive the SMD Data and Computing Architecture study (Workshop A.1). We will then identify elements of candidate Alternative Architectures responsive to those Needs (Workshop A.2). Our final step will be to compare and refine Alternative Architectures (Workshop A.3).
Target Workshop(s) Audience
All Series A workshops are open meetings, but of specific interest to researchers, big data teams, and archivists at the Science Mission Directorate (SMD) Data Repositories along with missions and community members in relevant topic areas.
Individuals from Division Headquarters, Data centers, User Working Groups, or individuals who specialize in computing are recommended to attend in-person.
Workshop Agenda(s) (2 Full Days, hybrid)
- A.1) Understanding SMD Needs for Data and Computing (October 12 – 13, 2022)
- A.2) Definition of Alternative Architectures (New Date To Be Announced)
- A.3) Analysis & Evaluation of Architectures (New Date To Be Announced)
Code of Conduct
All Series A workshops are conducted following the Transform to Open Science Code of Conduct.
Point of Contact
If you wish to register for an A Series Workshop or receive additional information about upcoming Data and Computing Architecture Study Workshops, please contact Hannah Cubberley.
If you have any questions about Data and Computing Architecture Study, please contact Elena Steponaitis.