"Principles of Open Source software did not prove to be useful in open drug development. ... Crowdsourcing will not advance quantum physics," he writes. "Open Science in its fullest form is not an issue that scientists can truly solve by themselves."
Open Science's Greatest Need Is ... Non-Scientists? | The Daily Scan | GenomeWeb
Please read the great post examining models of 'open science by Pawel.
While I agree with much of the chewy content goodness, I'm not sure I can sign on to the bit about 'principles of open source software did not prove to be useful in open drug development' being entirely true.
The capability for open source to be useful in things like crowdsourcing new theories of genetics+anthropology (genoanth) in addition to drug development hasn't been proven, but it certainly hasn't been disproven.
Especially in health analytics/personal biometrics ("Me-trics" or the #quantifiedself) Joe the Plumber hasn't had access to the kind of data about ourselves (much less others) that we'd need to share and contribute to an open-source public health development initiative.
Cancer-survivor communities like ACOR (@gfry, @ePatientDave thanks again for the heads up here) COULD in theory be used to open-source new treatments. In fact, the community/listserv members ARE using the list this way, but the 'establishment' isn't paying much attention.
PatientsLikeMe.com, however, has made open-sourcing one's health data relatively easier, lowering barriers to entry by putting metric tracking/analytics tools in the hands of patients.
Despite my fan-girl-ism for PLM, there are issues with the service, which isn't 'pure' opensource (in my opinion) - I cannot opt out of having my data anonymized and sold, and I can't demarcate if it's used for corporate gain versus nonprofit research purposes. I also can't throw my data open for the world to use/view at will if I so choose.
If I was designing an open-science, open-source health development initiative (product or drug), I'd go after a software installlation like that offered by Palantir Tech. Then I'd recruit survivors and start sharing data nodes. Then I'd motivate the community to go to work analyzing the hell out of the data intersection points for sparks of potential relevance. Then each promising x+y would have to be examined for causation/correlation.
If I wanted to cure a disease like Parkinson's, or even come up with EBP support (and EBP here would really be E2BP, for Evidence-based practice+ Experiential-based practice) for a new clinical guideline to impregnate into real-world practice, this is how I'd go about it.
I digress. But Pawel Szczesny (Freelancing Science) is right about one very big issue here - open science (or open source, or open health) absolutely require participation outside traditional professional gradients to succeed.
Talent without a pedigree counts for something here. Let's make sure we don't continue to make the mistake of discounting the value of experiential knowledge, which is open science (and 'open health's) most underutilized asset.