[mechanical_fish]

You can share them. Many labs do. Indeed, most of these things are probably shared in one way or another.

And you're correct: The trick to encouraging open source science is not to focus on the social networking tech -- that will be ready when you need it -- but to first attack the problem of doing quality lab work on the cheap. That's where the bottleneck is.

The biggest problem with shared facilities is the tragedy of the commons. In engineering -- or machining or woodworking or cooking, for that matter -- you quickly learn the importance of having your own tools. It only takes seconds to ruin a good tool. It only takes seconds to contaminate your cell culture, or your neighbor's cell culture, or an entire room full of your department's laboratory mice.

And mailing your samples off to a distant "virtual" lab is fine if you're studying disposable samples, or inorganic samples, or samples that have been permanently fixed and preserved on a glass slide. But living cells ship poorly even when you're allowed to ship them at all, and animals ship even more poorly than that. So often you've got to live next door to the equipment you're trying to share, and that's still expensive.

[dougabug]

The cost of maintaining your own tools is quite high, as is the expertise required to maintain them in working order. It seems to be that the inexperience or lack of skill which leads to shared equipment getting ruined is due to the fact that extremely sensitive equipment is being handled by students and junior scientists with little engineering background. The same argument could be made for the value of having your own servers. The scientific equivalent of a datacenter, would necessarily entail staffing of highly qualified, experience personnel. Such expertise would undoubtedly be costly, but it would be amortized over a large amount of equipment.

[ylem]

Staffed by who? There are actually some user facilities for materials synthesis--the problem is that if someone is making someone else's material instead of working on something that they're interested in, then I don't think that you're going to get the same level of productivity out. Also, materials synthesis takes time and running through lots of dead ends. When I was a grad. student, a postdoc from a collaboration would drive in to our lab with powders she had made--try to grow a crystal for a week (sleeping for maybe an hour or two a night on a floor in our office) and then go back to her home institution and come back in a few weeks. That just doesn't work--you don't have the responsiveness to be able to figure out what dead ends you're wandering down...Imagine if you were writing code and could only run it once every few weeks. Now, imagine that it was thousands of lines of nontrivial code and you're trying to debug it that way...

[dougabug]

Staffed by scientists and engineers, I imagine. You can get some pretty sophisticated parts built by foundries. At one point, making a microchip was prohibitively expensive. Nowadays, when you create chips basically by coding them in high level synthesis languages. Spinning a chip does take weeks. Obviously when a process takes longer to carry out, with high iteration cost, careful methodology is called for. Simulation and error checking software becomes valuable. Heck, once upon a time computers themselves were massively expensive, among the most expensive machines built. Computing wasn't born cheap. Mass production and decades of technological advances made them so. Machines for combinatorial science may someday be more effective than graduate students.