ReScience C

Ten Years Reproducibility Challenge

Fri, 11 Oct 2019 00:00:00 +0200

Did you ever try to run an old code that you wrote for a scientific article you published years ago? Did you encounter any problems? Were you successful? We are curious to hear your story. This is the reason why we are editing a special issue of ReScience to collect these stories.

The ten years reproducibility challenge is an invitation for researchers to try to run the code they’ve created for a scientific publication that was published more than ten years ago. This code can be anything (statistical analysis, numerical simulation, data processing, etc.), can be written in any language and can address any scientific domain. The only mandatory condition to enter the challenge is to have published a scientific article before 2010, in a journal or a conference with proceedings, which contains results produced by code, irrespectively of whether this code was published in some form at the time or not.

Note that we do not ask you to write a new version of your old code. We ask you instead to try to make your old code to run on modern hardware/software (with minimal modifications) in order to check if you can obtain the exact same results that were published at least ten years ago.

Sounds easy? We have good reasons to think this might be more difficult than you think. And maybe the first problem you’ll have to solve is to find your own source code.

More information at: rescience.github.io/ten-years

ReScience (R)evolution

Thu, 23 May 2019 00:00:00 +0200

Four years ago, we launched ReScience, a new scientific journal aimed at publishing the replication of existing computational research. Since ReScience published its first article, things have been going steadily. We are still alive, independent and without a budget. In the meantime, we have published around 25 articles and the initial has grown from around 10 to roughly 100 members (editors and reviewers), we have advertised ReScience at several conferences worldwide, gave some interviews, and published an article introducing ReScience in PeerJ Computer Science. Based on our experience at managing the journal during these four years, we thought that time was ripe for some changes. Read our editorial if you want to know more.

Sustainable computational science: the ReScience initiative

Mon, 18 Dec 2017 00:00:00 +0100

We just published our white paper on ReScience in PeerJ

Abstract: Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results; however, computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. James Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested and are hardly ever actually executed to check that they produce the results advertised in the article. ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. ReScience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests.

References: N.P. Rougier et al., (2017) Sustainable computational science: the ReScience initiative. PeerJ Computer Science 3:e142. DOI doi.org/10.7717/peerj-cs.142

Call for replication

Wed, 19 Oct 2016 00:00:00 +0200

It is now possible to suggest an article for a replication. Just open a new issue in the call for replication repository and give the reference of the original article and possibly the reason you would like to see this article replicated (please refrain from suggesting your own work). Note that you’re also encouraged to register as a reviewer such that you can review the replication you’ve been proposing if someone actually takes up the challenge.

If you’re looking for some challenge, you can also look at the current list of suggestions.

You can help by becoming a reviewer

Sat, 02 Jul 2016 00:00:00 +0200

ReScience is slowly gaining momentum and we currently have 4 submissions to review. If you’re interested in helping ReScience and reproducibility, you can become a reviewer. What you need is a github account, a one line description of your expertise (see the Board for some examples) and to tell us you’re interested such that we can add you to the board. You can also follow the submission repository and propose your help whenever a submission falls into your expertise domain.

New year, new challenges ahead

Thu, 07 Jan 2016 00:00:00 +0100

Even though open and reproducible science is gaining fast ground, there still exists a large number of published computational researches that are just awaiting replication. Why not pick your favorite paper and try to replicate it ? If you’re interested in this specific paper, chances are that your replication will also be interesting for a lot of researchers.

ReScience: A Scientific Journal Living on Github

Sun, 06 Sep 2015 00:00:00 +0200

LabCritics kindly made a post introducing ReScience and explaining its goals: “Computational research is set to get new open source journal solely for publishing implementations of algorithms and codes already published. Termed ReScience (Replicated Science – I guess [note: yes]), the journal uses and exists solely on Github, a popular Web-based Git repository service, offering all of the distributed revision control and source code management functionality of Git.”

Official creation

Tue, 01 Sep 2015 00:00:00 +0200

It’s our great pleasure to announce the creation of ReScience which is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research is reproducible.

Review process test is over

Mon, 10 Aug 2015 00:00:00 +0200

We’ve been testing the review process with Tiziano Zito (editor), Benoît Girard (reviewer) and Mehdi Khamassi (reviewer). They helped smoothing the whole process and we’re ready for mass production! But let’s wait for a second review…