Commercial applications, public funding

I wanted to write this earier, but I couldn’t: I’m now in a hotel in Maastricht, Netherlands, and waiting to get back tomorrow. I’ve been attending the 4th NuGO hands-on advanced microarray data analysis course and I even wanted to blog about it… but the hotel’s connection did not resolve any non-European web page until late today.

Recently it came to my mind that certain organizations, laboratory groups, etc. use commercial software when doing publicly funded research. I’m speaking about microarray experiments, since that is my field of work, while other fields may be different. Personally I see the use of commercial software in microarray data analysis feasible only for groups that can’t afford a dedicated person for data analysis. As for the rest, I don’t think it’s quite a good idea for a number of reasons:

  • Commercial software may be polished and shiny, but for obvious reasons it always lags behind the academic developed software;

  • Most of the time the same results can be obtained with free alternatives, for example normalization, differential expression and hierarchical clustering;

  • Most importantly, there is the issue of lock in. What happens if you get a cut in your funds and you can’t pay your annual license anymore? You get a bunch of unusable data. And again, what if the company goes belly up? Again, you are screwed. This is even more true for web-based applications, where the data resides on a server that is away from you.

Of course the latter point also applies to academic software that is not either free or open source. .

It is also worthy to note that sometimes the results of algorithm designing, data workflows and the like end up in commercial applications. That may be perhaps healthy for business, but if those people got public funding, they should not be allowed to profit on the citizen’s tax money. If they got their funding by other means, they can do whatever they want in my view. I’m only concerned that goverment-funded research would then be used to restrict knowledge (only to paying customers) instead of spreading it.

Of course, , but if it is open sourced, at least someone can pick it up and improve it even if the original author is no longer around.

open source Science software

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