The guiding strategies of Science 1.0 are still needed for Science 2.0: hypothesis testing, predictive models, and the need for validity, replicability, and generalizability. However, the Science 2.0 challenges cannot be studied adequately in laboratory conditions because controlled experiments do not capture the rich context of Web 2.0 collaboration, where the interaction among variables undermines the validity of reductionist methods (7). Moreover, in Science 2.0 the mix of people and technology means that data must be collected in real settings (see the figure). Amazon and Netflix became commercial successes in part because of their frequent evaluations of incremental changes to their Web site design as they monitored user activity and purchases.
Good evolutionary ecologist that I am, I read this and said to myself, “Science 2.0 sounds like what I already do.” Biologists have been using methods beyond controlled laboratory experiments and collecting data in “real settings” to test hypotheses since Darwin’s day and before (see Jared Diamond’s discussion of natural experiments found in “real settings” [subscription]).
As an example of Science 2.0 methods, Shniederman shows a chart mapping collaborations between U.S. Senators, a version of which is available here. It’s an informative picture – you can see immediately that “independents” Joe Lieberman and Bernie Sanders are a lot more connected to the Democrats than the Republicans, and that a relatively small number of senators act as “bridges” between the two parties. But it’s not clear to me why this represents a new method (apart from the visualization technology behind it) – couldn’t the same graphic have been compiled from paper voting records in 1920? It might be easier to produce now, but I don’t think the diagram represents a new scientific method. (An analogy: it might be really easy for me to do ANOVAs now, but these statistics pre-date my laptop and R.)
Shniederman also suggests that Science 2.0 will be interested in different kinds of things than hoary old Science 1.0:
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.
He cites a “fivefold growth of research on privacy and trust,” based on a literature search, but doesn’t elaborate on how these topics require truly new methods. Again, I’d suggest that Science 1.0 was interested in human interactions, too (just ask a Sociobiologist), but it didn’t have the data provided by the Internet until, well, about 10 years ago. I’d wager that none of the studies turned up by Shneiderman’s lit search do anything radically new, methods-wise.
It’s certainly true that the growth of social networking through the Internet allows scientists access to data that can answer questions we weren’t able to deal with before. For instance, we have real-time records of people interacting with their friends thanks to Facebook (momentarily pretend this doesn’t creep you out). But the actual methods we’ll use to analyze those data are nothing radically new. On that count, Science 2.0 looks a lot like a Microsoft product upgrade – a new interface “skin” on top of the same basic mechanism.
Shneiderman B. 2008. Science 2.0. Science 319:1349-50.
Diamond J. 2001. Dammed experiments! Science 294:1847-8.