I run a lot of numerical simulations, and we run into the same issues, as a few people have noted above. Many of my colleagues still write code in fortran 77 and manually give descriptive filenames to their data. It's a mess. There's a guy at the University of Toronto, Greg Wilson, whose work centers on getting computational scientists--largely people who run simulations--to become more sophisticated. He runs a one-week course teaching software engineering principles to computational scientists. It's available online for self-study at http://www.sofware-carpentry.org./ One section is a lesson on using databases (he demonstrates SQL) to handle numerical data, which I imagine looks a lot like experimental data. He's currently rewriting the course, but I have learned a lot from it.

That may be. But whether he goes to publicize the work, he first needs to talk to an expert in the field and find out which conference or journal would even be appropriate. There are thousands out there, of varying quality and editorial policies. It will be difficult to publish if he is outside academia or research labs. They do get crackpot submissions all the time--I'm not saying the Alex is a crackpot, merely that it's possible he could be mistaken for one. Writing your first paper is not easy, especially without an academic advisor to help explain what the conventions are, what to leave out, etc. Most academics are interested in the work, not where you come from, and if Alex has done what appears to be good research, people would be happy to talk to him. He needs to find someone sufficiently expert in his topic to help him, and he needs to communicate what he has done in a clear and efficient way, because experts are busy and don't want to spend time on something that's explained poorly. He may be concerned about someone stealing his work, in which case, he could submit a very early preprint somewhere like arxiv.org in order that there is a public record of his findings.