If you want reproducible science, the software needs to be open source

An increasing proportion of scientific research is data-intensive, and analysing torrents of data requires software, much (if not most) of which is custom-written by researchers to meet their needs. What that means is that computer code has become the equivalent of lab apparatus for some kinds of science. But scientific method requires that the relevant disciplinary community should be able to reproduce an experiment. That means that the custom-written software should also be made available in an accessible form. But often it isn’t — which is why it’s good new to learn of a Nature Editorial arguing that it should. ArsTechnica has a useful piece about this issue. Excerpt:

Modern scientific and engineering research relies heavily on computer programs, which analyze experimental data and run simulations. In fact, you would be hard-pressed to find a scientific paper (outside of pure theory) that didn’t involve code in some way. Unfortunately, most code written for research remains closed, even if the code itself is the subject of a published scientific paper. According to an editorial in Nature, this hinders reproducibility, a fundamental principle of the scientific method.

Reproducibility refers to the ability to repeat some work and obtain similar results. It is especially important when the results are unexpected or appear to defy accepted theories (for example, the recent faster-than-light neutrinos). Scientific papers include detailed descriptions of experimental methods—sometimes down to the specific equipment used—so that others can independently verify results and build upon the work.

Reproducibility becomes more difficult when results rely on software. The authors of the editorial argue that, unless research code is open sourced, reproducing results on different software/hardware configurations is impossible. The lack of access to the code also keeps independent researchers from checking minor portions of programs (such as sets of equations) against their own work.