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A Course in Reproducible Research Some content is generic, some is domain specific Generic content must be illustrated by domain specific examples Meta.

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Presentation on theme: "A Course in Reproducible Research Some content is generic, some is domain specific Generic content must be illustrated by domain specific examples Meta."— Presentation transcript:

1 A Course in Reproducible Research Some content is generic, some is domain specific Generic content must be illustrated by domain specific examples Meta issues –Where should these topics be taught? Single generic course is unlikely to gain traction (at least in established institutions), so piecemeal inclusion into other computationally oriented courses is more likely to work –How can we share course material that is developed? Creative commons (but be careful about NC restrictions) –Examples: Software Carpentry bootcamps, reproducible science winter school in Geilo Norway, HPC course at U Washington, computational science course at KAUST, others? Dec 20121

2 Hands-on Topics (1) Software Carpentry –version control –scripting –databases –build systems –unit testing Testing –system / regression –V&V / UQ –continuous integration Provenance Reproducibility in statistical and probabilistic computations Dec 20122

3 Hands-on Topics (2) Research documentation –lab notebook –research compendium –literate programming Programming (not in SWC) –debuggers –how to write good code –floating point / nondeterminism –documentation Big challenges –high performance computing –big data –cloud computing –complicated SW stacks / toolchains (solution is VMs) Dec 20123

4 Lecture Topics IP / licensing Citation / attribution examples of RR (both good & bad; ideally domain specific) publishing / repositories / archives generic scientific software requirements Dec 20124

5 Participants Juliana Freire Andrew Davison David Ketcheson Aron Ahmadia Randall LeVeque Ian Mitchell Yihui Xie Andre Brodtkorb Dec 20125


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