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A Software Carpentry Perspective of Bioinformatics Training - Scott Ritchie
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A Software Carpentry Perspective of Bioinformatics Training - Scott Ritchie

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Scott C Ritchie, Damien Irving, David Flanders …

Scott C Ritchie, Damien Irving, David Flanders

Programming is increasingly becoming an essential skill for researchers in the life sciences. However, most scientists doing bioinformatics receive no formal training in programming, inhibiting both research efficiency and reproducibility. Software Carpentry is a volunteer organisation whose goal is to make scientists more productive, and their work more reliable, by teaching them basic programming skills through intensive two-day workshops (bootcamps). In this session we will discuss the Software Carpentry philosophy and reflect on our experiences running bootcamps for bioinformaticians in the Melbourne region.

Presented at InCoB 2014 special session on Bioinformatics Education and Training: http://incob2014.org

Published in Science
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  • Scientists spend 40% of their time building or using software
    55% say this figure is rising
    96% are largely self taught
  • Beginning in the late 90s. Taught by volunteers
  • Beginning in the late 90s. Taught by volunteers
  • Beginning in the late 90s. Taught by volunteers
  • Based on the feedback received, Give an Obama-pause
  • Based on the feedback received, Give an Obama-pause
  • Also mention global sprint for anyone who wants to help out with teaching materials.
  • Slide to display while we take questions

Transcript

  • 1. Software Carpentry @ITS_Res: Empowering Communities of Researchers with ITS Services Scott Ritchie, Ph.D. Student, Medical Systems Biology, Research Community Coordinator, Software & Data Carpentry Instructor for R Teaching lab skills for scientific computing
  • 2. The state of scientific computing “Giving the average scientist access to a supercomputer is like giving the average 16 year old a Ferrari, and the crash rates are similar” — Greg Wilson, creator of Software Carpentry, PyCon 2014
  • 3. Software Carpentry • Teach the basic lab skills for scientific computing • Two day bootcamps • Taught by volunteer instructors (and helpers!)
  • 4. Software Carpentry • Unix/Shell • Python, Matlab, or R • Git + Github • SQL
  • 5. Software Carpentry: what we really teach • Unix/Shell • Python, Matlab, or R • Git + Github • SQL  Task Automation  Modularisation  Tracking and Sharing  Structured Data
  • 6. Software Carpentry: what we really teach • Unix/Shell • Python, Matlab, or R • Git + Github • SQL  Task Automation  Modularisation  Tracking and Sharing  Structured Data
  • 7. Feedback A two day workshop will save on average, a day a week, for the rest of your scientific career.
  • 8. Teaching Pedagogy and Instructional Design 1. Wilson, G. Software Carpentry: lessons learned. F1000Res. 3, 62 (2014). 2. Wilson G, Software Carpentry: Lessons Learned. PyCon 2014 https://www.youtube.com/watch?v=FtKO619O5g0 • Scientific computing != software development! • Intrinsic motivation • Instructional Scaffolding • Instructor training: how, not what to teach.
  • 9. … Carpentry? Skills Required to be a successful Bioinformatician: • Scientific Computing / Programming • Data Analysis / Statistics • Biology
  • 10. The Research Bazaar • Hosts and funds most of the bootcamps in Australia • Researcher training • How do we apply this paradigm to teach tools in other disciplines?
  • 11. Researcher Training Conference resbaz.tumblr.com/conference • 3 Days, February 16th–18th • Interactive training sessions • Tools for Open Science and Arts/Digital Humanities • February 11th–13th • Learn about the pedagogy of teaching “Kickstarting doctoral training in Australia” n e c t a r cloud > virtual labs > research tools “Train the Trainer” Conference
  • 12. Find out more Blog: resbaz.tumblr.com Twitter: @ITS_Res, #ResBaz David Flanders: dff.melb@gmail.com, @dfflanders Scott Ritchie: sritchie73@gmail.com, @sritchie73 Software Carpentry software-carpentry.org The Research Bazaar Acknowledgements David Flanders (Research Bazaar) Damien Irving (Research Bazaar) David Lovell (CSIRO)
  • 13. Extra Slides
  • 14. Some Statistics1-2 1. Hannay, J. E. et al. How Do Scientists Develop and Use Scientific Software? (IEEE Computer Society, 2009) 2. Prabhu, P. et al. A Survey of the Practice of Computational Science. in State of the Practice Reports 19:1–19:12 (ACM, 2011). • Scientists spend 40% of their time building or using software • 55% say this figure is rising • 96% are largely self taught