Data Carpentry for Atmosphere and Ocean Science

An overview of the work Data Carpentry is doing to teach foundational coding and data science skills to atmosphere and ocean scientists.

Transcript

1. @DrClimate damien.irving@unsw.edu.au Data Carpentry for Atmosphere and Ocean Science Damien Irving Climate Change Research Centre University of New South Wales
2. Coding skills for researchers. Domain independent. Popular since 2012.
3. Software Carpentry workshops since 2012
4. Workshop features ž Two-day intensive format ž Focus on programming best practices1,2 ž Volunteer instructors trained in pedagogy ž Peers (not experts) teaching peers ž Live coding ž High helper to learner ratio 1. Wilson et al (2014). Best practices for scientific computing. PLoS Biol 12(1): e1001745 2. Wilson et al (2017). Good enough practices in scientific computing. PLoS Comput Biol 13(6): e1005510 Reduced cognitive load for learners
5. Coding skills for researchers. Domain independent. Popular since 2012. Coding & data skills for researchers. Domain specific. Since 2015. For people working in library & information related roles. Since 2014.
6. Data Carpentry ž Flagship lessons: — Ecology, genomics, social sciences, geospatial [mature] — Digital humanities, image analysis, economics, astronomy [under development] ž Community contributed lessons: — Atmosphere and ocean science [mature] — https://github.com/carpentries-incubator https://datacarpentry.org/lessons/
7. PyAOS Data Carpentry: Timeline ž Software Carpentry @ AMOS 2013-17 ž Data Carpentry pilots @ AMOS 2018, WHOI, BoM ž Published with JOSE1 ž Data Carpentry @ AMOS 2019-2020 1. Irving D (2019). Python for atmosphere and ocean scientists. Journal of Open Source Education. 2(11), 37.
8. PyAOS Data Carpentry: Content ž Task: Python script that plots the rainfall climatology ž Focus: Programming best practice
9. https://carpentrieslab.github.io/python-aos-lesson/ Website has everything needed to run the workshop (or independent study). Participants must have some (very basic) experience with Python.
10. Next steps ž Grow the community of Carpentries instructors in the PyAOS space — You don’t need to be an expert programmer! — https://carpentries.org/become-instructor/ ž Further lesson development — Large arrays (chunking, dask, etc) — Regridding — Other additional topics?
11. damien.irving@unsw.edu.au @DrClimate Please get in touch if you’d like to get involved! Become an instructor? Host a workshop at your institution/conference? Lesson development ideas? https://carpentrieslab.github.io/python-aos-lesson/