Data Carpentry for Atmosphere and Ocean Scientists

Python has emerged in recent years as the programming language of choice for data analysis in the atmosphere and ocean sciences. By consulting online tutorials and help pages, most researchers in this community are able to pick up the basic syntax and programming constructs. This self-taught knowledge is sufficient to get work done, but it often involves spending hours to do things that should take minutes, reinventing a lot of wheels, and a nagging uncertainty at the end of it all regarding the reliability and reproducibility of the results. To help address these issues, the author organised a Software Carpentry (Wilson, 2014) workshop alongside the 2013 Annual Conference of the Australian Meteorological and Oceanographic Society (AMOS). He then trained up as a Carpentries instructor and taught workshops alongside AMOS conferences from 2014-2017, as well as other ad hoc workshops in various meteorology and oceanography departments. While these workshops were very popular and well received, there was clearly demand for a workshop designed specifically for atmosphere and ocean scientists. Instead of teaching generic skills in the hope that people would figure out how to apply them in their own context (i.e., in the context of netCDF files, PyAOS libraries, etc), such a workshop would teach programming, data management and reproducible research skills in the atmosphere and ocean science context. This idea of discipline (or data-type) specific workshops was the driving force behind the establishment of the Data Carpentry initiative, so with their assistance the author developed and published “Python for Atmosphere and Ocean Scientists” (Irving, 2019), the official Data Carpentry offering for researchers in the field. Now that the workshop materials (i.e. lesson plans, data files and software installation instructions) have been released and tested in a number of different forums – including alongside the 2018 and 2019 AMOS conferences – the author is looking for people interested in teaching and/or hosting a workshop. Similar to the Data Carpentry communities in ecology, genomics and social sciences, it is hoped that a global network of instructors can be established to run regular workshops and contribute to ongoing collaborative development of the lessons. Come along to this presentation to hear more about the new Data Carpentry lessons for atmosphere and ocean scientists and how to get involved.

Irving, D (2019). Python for atmosphere and ocean scientists. Journal of Open Source Education. 2(11), 37. doi:10.21105/jose.00037

Wilson, G (2014). Software Carpentry: lessons learned. F1000Research, 3, 62. doi:10.12688/f1000research.3-62.v2