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Re: [O] A manuscript on "reproducible research" introducing org-mode
From: |
Jambunathan K |
Subject: |
Re: [O] A manuscript on "reproducible research" introducing org-mode |
Date: |
Thu, 16 Feb 2012 14:28:31 +0530 |
User-agent: |
Gnus/5.13 (Gnus v5.13) Emacs/24.0.93 (windows-nt) |
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."
> }
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