EVENTS
Scalable and Computationally Reproducible Approaches to Arctic Research
Dates: September 19 - 23, 2022
Location: NCEAS
Venue: Santa Barbara, CA
This 5-day in-person workshop will provide researchers with an introduction to advanced topics in computationally reproducible research in python, including software and techniques for working with very large datasets. This includes working in cloud computing environments, docker containers, and parallel processing using tools like parsl and dask. The workshop will also cover concrete methods for documenting and uploading data to the Arctic Data Center, advanced approaches to tracking data provenance, responsible research and data management practices including data sovereignty and the CARE principles, and ethical concerns with data-intensive modeling and analysis.
Materials
Instructors
| Name | |
|---|---|
| Matt Jones | jones@nceas.ucsb.edu |
| Jeanette Clark | jclark@nceas.ucsb.edu |
| Sam Csik | scisk@ucsb.edu |
| Carmen Galaz-Garcia | galaz-garcia@nceas.ucsb.edu |
| Daphne Virlar-Knight | virlar-knight@nceas.ucsb.edu |
| Natasha Haycock-Chavez | haycock-chavez@nceas.ucsb.edu |
| Ingmar Nitze | Ingmar.Nitze@awi.de |
| Chandi Witharana | chandi.witharana@uconn.edu |
Acknowledgements
Work was supported by:
- NSF award #1546024 to M. B. Jones, S. Baker-Yeboah, A. Budden, J. Dozier, and M. Schildhauer
Additional support was provided for working group collaboration by the National Center for Ecological Analysis and Synthesis, a Center funded by the University of California, Santa Barbara, and the State of California.