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
   

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2. Coding skills for
   researchers.
   Domain independent.
   Popular since 2012.
   

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3. Software Carpentry workshops since 2012
   

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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
   

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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.
   

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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/
   

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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.
   

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8. PyAOS Data Carpentry: Content
   ž Task: Python script that plots the
   rainfall climatology
   ž Focus: Programming best practice
   

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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.
   

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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?
    

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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/
    

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