Closed rougier closed 7 years ago
Proposal (extracted from the ReScience website):
If computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and replicating results, computational science still lags behind. In the best case, authors may provide the sources of their research as a compressed archive and feel confident their research is replicable. But this is not exactly true. Buckheit & Donoho explained almost 20 years ago that, an article about computational result is advertising, not scholarship. The actual scholarship is the full software environment, code and data that produced the result. The computational part in computational sciences implies the use of computers, operating systems, tools, frameworks, libraries and data. This leads to such a large number of combinations (taking into account the version for each component) that the chances to have the exact same configuration as one of your colleagues are nearly zero. This draws consequences in our respective computational approaches in order to make sure that computational research can be actually and faithfully replicated. 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 is reproducible. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. ReScience lives on GitHub where each new implementation of a computational study is made available together with comments, explanations and tests. Each submission takes the form of a pull request that is publicly reviewed and tested in order to guarantee that any researcher can re-use it. ReScience is open and collaborative by design: everything can be modified.
Some suggestions:
@benureau Thanks. The abstract is mostly an excerpt of the website and coul probably benefit from a full rewrite. Note also that the paper version is a bit different now (some corrections were added)
New version (13/07/2017):
Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and replicating 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 2 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, 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.
We forgot the abstract ! Any taker ?