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Re: [O] A manuscript on "reproducible research" introducing org-mode

From: Christophe Pouzat
Subject: Re: [O] A manuscript on "reproducible research" introducing org-mode
Date: Thu, 16 Feb 2012 10:21:39 +0100
User-agent: Gnus/5.13 (Gnus v5.13) Emacs/23.3 (gnu/linux)

Hello Jambunathan,

The ODT version was prepared "by hand" using LibreOffice. This was
written (last May) before your org-odt functions became part of org-mode
(if I'm right). I would now also do it with org-mode.


Jambunathan K <address@hidden> writes:

> Christophe
> I see an ODT file in there - LFPdetection_in.odt
> http://hal.archives-ouvertes.fr/hal-00591455/
> May I ask how the document was produced. 
> Do you have any insights on how the Org's ODT exporter performs wrt your
> input Org file. Just curious.
>> @article{Delescluse2011,
>> title = "Making neurophysiological data analysis reproducible: Why and how?",
>> journal = "Journal of Physiology-Paris",
>> volume = "",
>> number = "0",
>> pages = " - ",
>> year = "2011",
>> note = "",
>> issn = "0928-4257",
>> doi = "10.1016/j.jphysparis.2011.09.011",
>> url = "http://www.sciencedirect.com/science/article/pii/S0928425711000374";,
>> author = "Matthieu Delescluse and Romain Franconville and Sébastien Joucla 
>> and Tiffany Lieury and Christophe Pouzat",
>> keywords = "Software",
>> keywords = "R",
>> keywords = "Emacs",
>> keywords = "Matlab",
>> keywords = "Octave",
>> keywords = "LATEX",
>> keywords = "Org-mode",
>> keywords = "Python",
>> abstract = "Reproducible data analysis is an approach aiming at 
>> complementing classical printed scientific articles with everything required 
>> to independently reproduce the results they present. “Everything” covers 
>> here: the data, the computer codes and a precise description of how the code 
>> was applied to the data. A brief history of this approach is presented 
>> first, starting with what economists have been calling replication since the 
>> early eighties to end with what is now called reproducible research in 
>> computational data analysis oriented fields like statistics and signal 
>> processing. Since efficient tools are instrumental for a routine 
>> implementation of these approaches, a description of some of the available 
>> ones is presented next. A toy example demonstrates then the use of two open 
>> source software programs for reproducible data analysis: the “Sweave family” 
>> and the org-mode of emacs. The former is bound to R while the latter can be 
>> used with R, Matlab, Python and many more “generalist” data processing 
>> software. Both solutions can be used with Unix-like, Windows and Mac 
>> families of operating systems. It is argued that neuroscientists could 
>> communicate much more efficiently their results by adopting the reproducible 
>> research paradigm from their lab books all the way to their articles, thesis 
>> and books."
>> }


Most people are not natural-born statisticians. Left to our own
devices we are not very good at picking out patterns from a sea of
noisy data. To put it another way, we are all too good at picking out
non-existent patterns that happen to suit our purposes.
Bradley Efron & Robert Tibshirani (1993) An Introduction to the Bootstrap


Christophe Pouzat
MAP5 - Mathématiques Appliquées à Paris 5
45, rue des Saints-Pères
75006 PARIS

tel: +33142863828
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