Science 2.0 : what is and what needs to be
Chris Patil , of Ouroboros , and Vivian Siegel have an interesting and thought-provoking op-ed in DMM, on the issue of the promise and the not-so-promising actuality of science 2.0.
They are right when they say that they doubt if science 2.0 wold attract more scientists than the currently active science bloggers and the likes; and I share their skepticism. However, while they believe that all the tools for online collaboration are already in place, I on the other hand think we need a more formalized one-stop system for scientists, where all their sharing, networking and collaborating needs are met. It doesn’t really attract me that much if I have to collaborate using FrinedFeed, share using twitter , learn using google reader, disseminate using blogger, or network using acaedmia.org etc. I am sure a scientific virtual water-cooler will soon emerge , but till that time I am skeptical of actual practicing scientists using science 2.0 in their day-to-day life; of course how the current breed of science bloggers use these tools and the kind of successful collaborations they can demonstrate would easily and likely define the way science 2.0 shapes up. Needless to say I am excited to be part of the early adopters and while twitter/ FF have not lived to their promise, the relatively older sibling of blogging , has managed to land me virtual collaborations, where I am discussing research ideas with persons who actually perform experiments (I am by circumstances an armchair scientist). For an example see comments by Kim on my last post on action selection, which has also led to some offline discussion and a possible future collaboration. For me science 2.0 works perfectly because I am not in the competitive business of being the first to publish a paper or to secure tenure etc and thus can put my ‘ideas to the world’ as freely as they come. At the same time, I am more than aware that the apprehensions scientists have over being stolen from are genuine and need more thought and care while designing the science 2.0 tools.
I will now like to quote some passages from the op-ed that I liked the most.
Suppose that your unique combination of training and expertise leads you to ask a novel question that you are not currently able to address. You advertise your idea to the world, seeking others who might be able to help. You find that Miranda has an idle machine, built for another purpose, that could be modified just so to help answer your question, if only she had a few samples from an appropriate patient. Hugo, busy with clinical responsibilities, has no time, but has a freezer full of biopsy tissues from such patients. Steve has the time and inclination to modify Miranda’s machine and to write the scripts to drive the analysis. Polly watches the whole process to make sure that the study has sufficient statistical power. Correspondence among the interested parties could be recorded in a publicly available forum, along with data and analysis as they emerge – allowing the entire scientific world to look on and to offer advice on the framing of the question, the design of the machine, the processing of the samples and the interpretation of the results.
In other words, what if you could think a thought at the world and have the world think back? What if everyone in the world were in your lab – a ‘hive mind’ of sorts, but composed of countless creative intellects rather than mindless worker ants, and one in which resources, reagents and effort could be shared, along with ideas, in a manner not dictated by institutional and geographical constraints?
What if, in the process, you could do actual scientific research? Granted, it would be research for which no one person (or group) could take credit, but research all the same. Progress might even occur more rapidly than it does in our world, where new knowledge is shared in the form of highly refined distillates of years of work.
I fit perfectly the person who can ask novel questions, experimental suggestions, but lacks expertise / time/ resources/ sanctity to run them. to me this hive mind would be god-send. If only, it could take off!! But then they provide a reality check:
Beyond raising concerns about the philosophy of communication, our utopian fantasy ignores important aspects of human nature. In any real world, finding collaborators would require a great deal more than shooting questions into the void and cocking an ear for the echo. In particular, in order to find a colleague with exactly the right complement of skills, interest and dependability, we need not only openness but trust. Within a laboratory group (at least, in a functional one), trust is part and parcel of lab citizenship; we and our colleagues voluntarily suspend our competitive urges in order to create a cooperative (and mutually beneficial) environment. In the wider world, however, the presumption is reversed: we tend to be cagey and suspicious in our interactions with other scientists. When we step outside the laboratory door, we transform from Musketeers (‘All for one…!’) to Mulder and Scully (‘Trust no one.’).
Oh , how I hate them to have burst my fantasy bubble by providing this reality check!! But thankfully not being bound to any laboratory I am at least immune form this cooperate or compete dilemma. I just hope there are more people like me (or enuff foolish scientists not really bothered about plagiarism) to reach a critical mass and snowball science 2.0. and then they touch on some subtle aspects of the above:
Another clash between utopia and human nature occurs at the level of publicly sharing preliminary data. In particular, during the period of transition between the status quo and the glorious future, openness may be provably irrational from a game-theoretical standpoint. If I share my data but my competitors do not, I’ve laid all of my cards out on the table, whereas others play theirs close to the vest – a bad bet under any circumstances. At best, my openness allows my adversaries to strategize; at worst, it allows them to steal my ideas. Perhaps the term ‘stealing’ is too harsh: in the words of our estimable thesis advisor, Peter Walter, ‘you can’t unthink a thought.’ Once an idea is in the field, can anyone be blamed for reacting to it in a way that is personally optimal? We already live with this moral conundrum every time we agree to review papers and need to balance the expectation of confidentiality with our own desire to shape our own future plans on the basis of the best and most current information. Radical sharing will require ways for individuals to protect themselves from the occasionally deleterious consequences of rational self-interest.
Perhaps most importantly from a practical perspective: information doesn’t share itself. From establishing an open record of preliminary discussions to freely disseminating experimental results, each step in the process requires an infrastructure. A framework, composed of software and web tools, is necessary in order to empower individual scientists to share information without each of them having to write the enabling code from scratch.
The weakest part of the article in my opinion, is when they argue that the tools are already available. I beleive we are still in the early stages of experimenting; new concepts and sites like biomedexperts need to be experimented with and I am sure we will soon be there. The authors suggest several sites where scientists in science 2.0 purportedly hang and then they point to reasons why that model has not succeeded yet:
Social networking tools also suffer from a variant of the ‘no one will go there until everyone goes there’ problem – the ‘me too’ dilution factor. Just as in the social/job space (Facebook, LinkedIn, MySpace, Bebo), there are myriad networks to choose from and many are too similar to distinguish. To a new user with limited time, it’s not obvious whether to try and join multiple networks, arbitrarily choose one, or wait for a clear winner to emerge.
Here’s praying that a clear victor emerges soon!
Patil, C., & Siegel, V. (2009). This revolution will be digitized: online tools for radical collaboration Disease Models and Mechanisms, 2 (5-6), 201-205 DOI: 10.1242/dmm.003285
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