At a meeting last night with some collaborators at the Vélobstacles project, I was excitedly told about the magic of IPython and it’s notebook functionality for reproducible research. This sounds familiar, I thought to myself. Using a literate programming approach to integrate computation with the communication of methodology and results has been at the core of the development of the RStudio IDE and associated tools such as knitr.
Here is Fernando Pérez speaking at PyCon Canada 2012 in Toronto about IPython for reproducible scientific computing.
This looks like convergent evolution in the R and Python communities, and I’m sure these projects can (and have already) learn a lot from each other.
Reproducible research was first coined by Pr. Jon Claerbout, professor of geophysics at Stanford University, to describe that the results from researches can be replicated by other scientists by making available data, procedures, materials and the computational environment on which these results were produced from.
This workshop intends to describe reproducible research, what it is and why you should care about it, and how to do it with the combination of R, LATEX, Sweave and makefile. Tips and tricks will also be provided.
To get introduce to the concept of reproducible research
To get started with the implementation of reproducible research with R and Sweave,
To produce a first Sweave document in LATEX
This is a meeting of the Montreal R Users Group. We’re open to everyone! Sign up to RSVP!