On the Wired Science blog - The Internet Is Changing the Scientific Method:
If all other fields can go 2.0, incorporating collaboration and social networking, it's about time that science does too. In the bellwether journal Science this week, a computer scientist argues that many modern problems are resistant to traditional scientific inquiry.
The title of the post is a big misnomer as the paper does not say anything about the change in the Scientific Method, but about the change scientists go about their work (perhaps "methodology"?). Read the rambunctious comment thread.
The paper is here but you cannot read it because it is in Science so you have to pay, which you are not crazy to do. But I got the paper and read it. I cannot copy and paste the entire text without breaking some maddening copyright law or something, but it is within Fair Use to give you a few key quotes so you can start the discussion (under the fold).
Successful scientific collaboratories among genomic researchers, engineering innovations through open-source software, and community-based participation in cultural heritage projects are all early indicators of the transformative nature of collaboration (5). eBay, Amazon, and Netflix have already reshaped consumer markets, while political participation and citizen journalism are beginning to change civil society. Patientcentered medical information and secure electronic health records are improving health care while creating opportunities for clinical research. MySpace and Facebook encourage casual social networks, but they may soon play more serious roles in facilitating emergency/disaster response (6). Social media platforms such as Wikipedia, flickr, and YouTube are also stunning success stories of Web-based contributions.
Science 1.0 will continue to be important, but new kinds of science, which I call Science 2.0, are needed to study the integrated interdisciplinary problems at the heart of sociotechnical systems. Science 2.0 will be especially important to meet the design challenges in secure voting, global environmental protection, energy sustainability, and international development among many others.
Science 1.0 heroes such as Galileo, Newton, and Einstein produced key equations that describe the relationships among gravity, electricity, magnetism, and light. By contrast, Science 2.0 leaders are studying trust, empathy, responsibility, and privacy. The great adventure for the next 400 years will be to define, measure, and predict the interaction among these variables so as to accelerate scientific discovery, engineering innovation, ecommerce, and education
Advancing Science 2.0 will require a shift in priorities to promote integrative thinking that combines computer science know-how with social science sensitivity. Science 2.0 researchers who develop innovative theories, hypothesis testing based on case study research methods, and new predictive models are likely to lead the way. The quest for empirical validity will drive research beyond what laboratory-based controlled studies can provide, while replicability and generalizability will be achieved with greater effort through multiple case studies.
Science 1.0 remains vital, but this ambitious vision of Science 2.0 will affect research funding, educational practices, and evaluation of research outcomes. Science funding agencies will face resistance as they promote a transformation that seeks to make a safe space for Science 2.0. Scientific journal editorial boards and conference program committees are already shifting their attention to new topics and opening their doors to new scientific research methods. Pioneering educators have begun changing their curricula, focusing on collaboration strategies and teaching new research methods. The innovators are courageously taking on new challenges, but they should be ready for the resistance to novel ideas that has always been part of science. In that way, Science 2.0 is part of a great tradition.
Education & Careers
Technology
Comments
To a first order, Science 2.0 = the Science of Complex Systems, applied to nonlinear biological, social, and other networks.
An interesting analogy between social and cellular networks came up on Charles Stross' blog [you know that his degree was in Pharmacy, and he did significant software development, before he became a full-time award-winning science fiction author]. Selected comments relevant to this analogy, peaking at "metazoans" and "multicellularity" in #72:
http://www.antipope.org/charlie/blog-static/2008/02/recent_headlines.html#comments
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37:
atatl@26: quite a lot of science doesn't fit strict Poplerian criteria. Anything involving a complex system isn't reproducible in an "if a, then b" kind of fashion. Weather is a classic example, as is anything involving life. There are several branches of science devoted to analysing those kinds of systems correctly, chaos theory being one of them.
Posted by: Chris | February 11, 2008 3:28 AM
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I agree with Chris, PhD, of Sydney, Australia in his #37 rebuttal of #26.
I suggest that those interested (Charles Stross knows about these already, I'm pretty sure) start at (google these for URLs, rather than have me get this comment stuck in a queue for having URLs in it):
New England Complex Systems Institute
[it's almost a self-serving conflict of interest for me to list officers and faculty there whose work I recommend, because of my years of involvement with this amazing entity, and duties performed in chairing sessions, chairing the plenary session, and being Con Chair once before and once forthcoming -- May 2009 -- for the A-list mini Science Fiction Con embedded in the international interdisciplinary science conference). But do check out their web site and wiki.
NECSI Complex Systems Wiki
New England Complex Systems Institute - as described on Wikipedia
Santa Fe Institute
Santa Fe Institute - as described on Wikipedia
"The Santa Fe Institute was founded in 1984 by George Cowan, David Pines, Stirling Colgate, Murray Gell-Mann, Nick Metropolis, Herb Anderson, Peter A. Carruthers, and Richard Slansky. All but Pines and Gell-Mann were scientists with Los Alamos National Laboratory."
"SFI's original mission was to disseminate the notion of a separate interdisciplinary research area, complexity theory referred to at SFI as 'complexity science'. Recently it has announced that its original mission to develop and disseminate a general theory of complexity has been realized. It noted that numerous complexity institutes and departments have sprung up around the world..." [truncated]
Also google and read about faculty at Santa Fe Inst with whom I have have personal face-to-face time to better appreciate their amazing research [I'm not name-dropping, just extending the Network of Trust]:
J. Doyne Farmer, Murray Gell-Mann, John H. Holland, Stuart Kauffman, Christopher Langton, Brian Goodwin (hey, I'd like to, but have not actually met their faculty member Cormac McCarthy).
Posted by: Jonathan Vos Post | February 11, 2008 6:00 AM
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67:
-isms?
"I can't understand why people are afraid of new ideas. I'm afraid of old ideas."
-- John Cage
Posted by: Jonathan Vos Post | February 14, 2008 1:56 AM
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69:
Communism works fine. As long as you're dealing with less than five hundred people. And the people involved can chose to leave at any time. See: Kibbutz.
Posted by: Andrew Crystall | February 14, 2008 2:55 PM
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71:
Andrew: an interesting question is whether it can be made to work at larger scales by using appropriate communication technology to make an end-run around the scaling problem. (I'll note that communism is, the prevalent organizational form when you reduce the scale to the very small, that is, to a family -- parents don't charge their kids bed and board (at least, not unless they're old enough to hold down a job) and frequently share bank accounts, mortgages, and other financial arranges on a basis that has no limits to mutual liability. It seems to work progressively worse every time you increase the scale by an order of magnitude; which makes me wonder, why? I don't buy "human nature" explanations. I suspect it's more likely something to do with scale factors and information transfer within the group of
participants, but I'm not sure. Hmm ...)
Posted by: Charlie Stross | February 15, 2008 12:13 AM
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72:
I'd suggest it's both. Communications overheads obviously make it hard to come up with a communications method whereby millions or billions of entities could communally share, but biology has done it: metazoans (e.g. us) are a pretty good example of a huge number of cells doing just that. In fact the sharing is much more extreme than most
communist systems, in that cells uncomplainingly die on demand.
(This was difficult to come up with, and is expensive; multicellularity is still the exception, rather than the rule, and many organisms can switch from one to the other as conditions demand.)
However, we have *not* been selected for similar communications on a large scale: we handle larger groups by analogizing them to smaller ones of the scale we evolved to handle. I suspect two causes: we've only been communicating on that scale for the blink of an eye in
evolutionary time, and secondly, the world is too small for a large number of differing experiments on the general theme of communications to coexist without interfering horribly. (It's easy to try out a thousand variations on bacterial communication in a thousand stromatolites, but it's rather harder to try out a thousand variations on many-million-person-scale communications, especially when severe failures could lead to e.g. nuclear war.)
Posted by: Nix | February 15, 2008 2:28 PM
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Posted by: Jonathan Vos Post | March 9, 2008 9:34 PM
It seems to me that a better name for what Shneiderman is talking about would be Sociology 2.0, and even with that modification I'm not convinced that he's really talking about something new. The study of the sociology of literature, for example, is not that different from approaches appropriate to the situations he names.
Posted by: Kathryn Cramer | March 13, 2008 7:46 AM