Links to Other Reproducible Research

Here are some links to related work about reproducible research, reproducible research papers, etc.

Other people and labs doing RR efforts

Reproducible electronic documents: Jon Claerbout and his colleagues at the Stanford Exploration Project initiated (to our knowledge) the discussions about reproducible research.
Wavelab: David Donoho and his colleagues at the Stanford Statistics Department developed Matlab code to reproduce their results on wavelets.
Reproducible Neurophysiological Data Analysis: a page by Christophe Pouzat on reproducible research in neurophysiology using R and Sweave.
Sensorscope: the wireless environmental sensing network developed at EPFL. Detailed descriptions of the sensor platform are available for those interested to reproduce the setup. Documented datasets are also available for people interested to reuse the data.
Xin Li's source code collection for reproducible research, with links to code for various image processing algorithms.
Al Hero's lab applies reproducible research for their publications.
Andrew Davison at CNRS works on facilitating reproducible simulations using Python.

Journals with RR initiatives

Annals of Internal Medicine: When a paper is accepted, the authors are asked explicitly whether their paper is reproducible. If yes, links are provided to the study protocol, data, and/or statistical code.
IEEE Transactions on Signal Processing: in the acceptance e-mail from the editor-in-chief, the authors are encouraged to make their code and data available online.
The Insight Journal: An online, open access journal in medical imaging that requires code as an integral part of the publication. They also allow for online post-publication reviews.

Articles about RR (chronologically)

D. E. Knuth, Literate Programming, The Computer Journal, vol. 27, no. 2, pp. 97–111, May 1984.
J. Claerbout, Electronic documents give reproducible research a new meaning, in Proc. 62nd Ann. Int. Meeting of the Soc. of Exploration Geophysics, 1992, pp. 601–604.
J. B. Buckheit and D. L. Donoho, WaveLab and Reproducible Research, Dept. of Statistics, Stanford University, Tech. Rep. 474, 1995.
R. Koenker, Reproducible Econometric Research, Department of Econometrics, University of Illinois, Urbana-Champaign, IL, Tech. Rep., 1996.
M. Schwab, M. Karrenbach, and J. Claerbout, Making scientific computations reproducible, Computing in Science & Engineering, vol. 2, no. 6, pp. 61–67, Nov. 2000.
H. D. Vinod, Care and feeding of reproducible econometrics, Journal of Econometrics, vol. 100, no. 1, pp. 87–88, Jan. 2001.
F. Leisch, Sweave: Dynamic generation of statistical reports using literate data analysis, in Compstat 2002 — Proceedings in Computational Statistics, W. Härdle and B. Rönz, Eds. Physica Verlag, Heidelberg, 2002, pp. 575–580, ISBN 3-7908-1517-9.
M. Barni and F. Perez-Gonzalez, Pushing Science into Signal Processing, IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 119–120, July 2005.
R. D. Peng, F. Dominici, and S. L. Zeger, Reproducible Epidemiologic Research, American Journal of Epidemiology, 2006.
H. A. Piwowar, R. S. Day, and D. B. Fridsma, Sharing detailed research data is associated with increased citation rate, PLoS ONE, vol. 2, no. 3, p. e308, March 2007.
M. Barni, F. Perez-Gonzalez, P. Comesaña, and G. Bartoli, Putting reproducible signal processing into practice: A case study in watermarking, in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 4, April 2007, pp. 1261–1264.
S. Fomel and G. Hennenfent, Reproducible computational experiments using scons, in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 4, pp. 1257–1260, April 2007.
J. Kovacevic, How to encourage and publish reproducible research, in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 4, April 2007, pp. 1273–1276.
P. Marziliano, Reproducible research: A case study of sampling signals with finite rate of innovation, in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 4, April 2007, pp. 1265–1268.
J. Vandewalle, J. Suykens, B. De Moor, and A. Lendasse, State of the art and evolutions in public data sets and competitions for system identification, time series prediction and pattern recognition, in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 4, April 2007, pp. 1269–1272.
P. Vandewalle, G. Barrenetxea, I. Jovanovic, A. Ridolfi, and M. Vetterli, Experiences with reproducible research in various facets of signal processing research, in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 4, April 2007, pp. 1253–1256.

Tools

Open Source

RRepository: a repository setup for making reproducible research publications available online, based on EPrints.
ThePub: an alternative setup for making reproducible research publications available online, using Java.
Sweave: a demo of Sweave, a package to do literate programming and good documentation using the statistical software R, by Charlie Geyer.

Commercial

Inference for Office: a tool for performing reproducible research from within Word or Excel documents, with links to scripts in Matlab, R, etc.

Blogs

Reproducible Research

Reproducible Ideas: John D. Cook's blog about reproducible research.
Pixeltje Blog: Patrick Vandewalle's blog about reproducible research, image processing, and research in general.