Main Page

From Reproducible Research

Welcome

Welcome on this site about reproducible research. This site is intended to gather a lot of information and useful links about reproducible research. As the authors (Patrick Vandewalle, Jelena Kovacevic and Martin Vetterli) are all doing research in signal/image processing, that will also be the main focus of this site. Follow the links in the text or in the navigation bar on the left to navigate through this site.

A description of how we make our research reproducible can be found on the How To page. The links page contains a large set of links about RR, tools, etc. And on the RR Material page, you can find a set of links to code and data for papers in signal processing.

News

This site has now been merged with its .org counterpart, which was maintained by John Cook. Both URLs point now to the same site, and a blog has been added. (Sep 09)

The forum has now also been transferred from the LCAV site to this page, so feel free to start discussing. (Feb 09)

This site is launched, with now also meaningful content. Quite an achievement already, I would say. (Jan 09)

Motivation

After a colleague asked something about a paper you wrote, you spend a considerable amount of time finding back the right program files you used in that paper. Not to talk about the time to get back to the set of parameters used to produce that nice result.

Because this type of situations sounded all too familiar to many people of the lab, we are now trying to make our research reproducible. Most of the ideas about reproducible research come from Jon Claerbout and his research group at Stanford University. We believe reproducible can be helpful in many ways:

• It will help us in the first place, to reproduce figures in the revisions of a paper, to create earlier results again in a later stage of our research, etc.
• Other people who want to do research in the field can really start from the current state of the art, instead of spending months trying to figure out what was exactly done in a certain paper. It is much easier to take up someone else's work if documented code is also available.
• It highly simplifies the task of comparing a new method to existing methods. Results can be compared more easily, and one is also sure that the implementation is the correct one.

This may all sound very trivial, and in discussions with colleagues, there was a general agreement that this is how research should be performed. However, in practice, only few examples are available today. Making articles reproducible indeed requires a certain investment in time. However, we think that it is worth the investment. The interest is hard to quantify, but from download statistics and Google rankings, we can see that it really pays off!