Platforms for reproducible research
This post was motivated by Ian Gent’s recomputation manifesto and his blog post about it. While I agree with pretty much everything said there, there is one point that I strongly disagree with, and here I’d like to explain the reasons in some detail. The point in question is “The only way to ensure recomputability is to provide virtual machines”. To be fair, the manifesto specifies that it’s the only way “at least for now”, so perhaps our disagreement is not as pronounced as it may seem.
I’ll start with a quote from the manifesto that shows that we have similar ideas of the time scales over which computational research should be reproducible:
“It may be true that code you make available today can be built with only minor pain by many people on current computers. That is unlikely to be true in 5 years, and hardly credible in 20.”
So the question is: how can we best ensure that the software used in our computational studies can still be run, with reasonable effort, 20 years from now. To answer that question, we have to look at the possible platforms for computational research.
If you plan to distribute some piece of digital information with the hope that it will make sense 20 years from now, you must either have confidence in the longevity of the platform, or be willing and able to ensure its long-term maintenance yourself. For the Flash platform, that means confidence in Adobe and its willingness to keep Flash alive (I wouldn’t bet on that). For the 2013 Web platform, you may hope that its sheer popularity will motivate someone to keep it alive, but I wouldn’t bet on it either. The Web platform is too complex and too ill-defined to be kept alive reliably when no one uses it in daily life any more.
Back to computational science. 20 years ago, most scientific software was written in Fortran 77, often with extensions specific to a machine or compiler. Much software from that era relied on libraries as well, but they were usually written in the same language, so as long as their source code remains available, the platform for all that is a Fortran compiler compatible with the one from back then. For standard Fortran 77, that’s not much of a problem, whereas most of the vendor-specific extensions have disappeared since. Much of that 20-year-old software can in fact still be used today. However, reproducing a computational study based on that software is a very different problem: it also requires all the input data and an executable description of the computational protocol. Even in the rare case that all that information is available, it is likely to depend on lots of other software pieces that may not be easy to get hold of any more. The total computational platform for a given research project is in fact as ill-defined as the 2013 Web platform.
Today’s situation is worse, because we use more diverse software written in more different languages, and also use more interactive software whose use is notoriously non-reproducible. The only aspect where we have gained in standardization is the underlying hardware and OS layer: pretty much all computational science is done today on x86 processors running Linux. Hence the idea of conserving the full operating environment in the form of a virtual machine. Just fire up VirtualBox (or one of the other virtual machine managers) and run an exact copy of the original study’s work environment.
But what is the platform required to run today’s virtual machines? It’s VirtualBox, or one of its peers. Note however that it’s not “any of today’s virtual machine managers” because compatibility between their virtual machine formats is not perfect. It may work, or it may not. For simplicity I will use VirtualBox in the following, but you can substitute another name and the basic arguments still hold.
VirtualBox is a highly non-trivial piece of software, and it has very stringent hardware requirements. Those hardware requirements are met by the vast majority of today’s computing equipment used in computational science, but the x86 platform is losing market share rapidly on the wider computing device market. VirtualBox doesn’t run on an iPad, for example, and probably it never will. Is VirtualBox likely to be around in 20 years? I won’t dare a prediction. If x86 survives for another 20 years AND if Oracle sees a continuing interest in this product, then it will. I won’t bet on it though.
What we really need for long-term recomputability is a simple platform. A platform that is simple enough that the scientific community alone can afford to keep it alive for its own needs, even if no one else in the world cares about it.
Unfortunately there is no suitable platform today, to the best of my knowledge. Which is why virtual machines are perhaps the best option right now, for lack of a satisfactory one. But if we care about recomputability, we should design and develop a good supporting platform, starting as soon as possible.
For a more detailed discussion of this issue, see this paper written by yours truly. It comes to the conclusion that the closest existing approximation to a good platform is the Java virtual machine. What we’d want ideally is something similar to the JVM, but designed and optimized for scientific applications. A basic JVM implementation is quite simple (the complex JIT stuff is not a requirement), a few orders of magnitude simpler than VirtualBox, and it has no specific hardware dependencies. It’s even simpler than many of today’s scientific software packages, so the scientific community can definitely afford to keep it alive, The tough part is… no, it’s not designing or writing the required software, it’s agreeing on a specification. Perhaps it will never happen. Perhaps virtual machines will remain the best choice for lack of a satisfactory one. Or perhaps we will end up compiling our software to asm.js and run in the browser, just because someone else will keep that platform alive for us, no matter how ill-adapted it is to our needs. But don’t say you haven’t been warned.Computational science, Reproducible research