I’ll give a talk at the University of Reading about reproducibility and replicability and will introduce the ReScience journal.

If computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing 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 reproducible. But this is not exactly true. Buckheit and Donoho (1995) explained 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 components) that the chances to have the exact same configuration as one of your colleague are nearly zero.This draws consequences in our respective computational approaches in order to make sure research can be actually and faithfully shared and replicated. ReScience is a peer-reviewed journal that target computational research and encourage the explicit replication of already published research promoting new and open-source implementations. The goal is to ensure the original research is replicable, but more importantly, ReScience aims at the cross-fertilization of research by incitating researcher to replicate the work of others, hoping this might pave the way for future collaborations or give rise to new ideas as a result of the replication effort.