By Deborah Paul, with contributions by Matthew Collins and Alex Thompson
In 2015, Data Carpentry participated in the Biodiversity Information Standards’ (TDWG) pre-conference training week in Nairobi, Kenya through the collaborative efforts and funding of the JRS Foundation, TDWG, the Gordon and Betty Moore Foundation, and iDigBio. For 2016, a Software Carpentry workshop was held two days prior to the December TDWG 2016 meeting in Santa Clara, Costa Rica. This was Software Carpentry’s first time to be offered in Central America and iDigBio got to lead the way. Local organizers from Centro de Transferencia Tecnológica y Educación Continua (CTEC) including Rogelio Quiros and Erick Mata, FSU’s Institute for Digital Information (iDigInfo), participant fees, and a grant from TDWG made this course possible.
Instructors from the Integrated Digitization of Biological Collections project (iDigBio) from Florida State University and the University of Florida joined participants from Israel, Estonia, Belgium, Costa Rica, the USA, and France. We enjoyed a cross-disciplinary environment with three professors, one an ecologist, the other two were computer scientists, as well as computer science students, ecology students, a graduate student, and data managers from OBIS, and GBIF. Course content included an introduction to the “shell”, introduction to SQL, introduction to R, and an introduction to version control using GitHub. You can check out the course web site at http://idigbio.github.io/2016-12-03-tdwg-costa-rica/
In our post-workshop survey, all respondents agreed or strongly agreed that skills they learned will be used in their research/work. Everyone strongly agreed the workshop was worth their time and agreed or strongly agreed they would recommend this workshop to a friend or colleague. CTEC faculty hope to do more of these types of capacity building exercises and join the Software Carpentry community. We hope to take Software Carpentry to TDWG 2017 - and see you there!
Background: Software Carpentry's mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. Participants are encouraged to help one another and to apply what they have learned to their own research and data problems. For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".