R goes to StackExchange

“What’s the big deal? We already have the r-help mailing list.”

No, it’s a big deal. Really.

Have you forgotten the joys of being a first-year R user, either begging advice off of friends or using Google to search archives of the R-help list? (Firefox has a dedicated search add-on for the R-help archives.) Yes, it gets the job done, but it’s kludge. If you’re a self-taught R programmer you know what I’m talking about.

StackExchange for Statistical Analysis will let experienced users answer statistics questions, presented in a legible format, and good answers are promoted to the top of the list. Questions can be tagged by subject matter and by package. Proper formatting for code swatches, and for discussion. It’s modeled on StackOverflow.

What makes a science wiki tick?

Nature has a great article discussing various business strategies for making a collaborative scientific resource work. What makes some grow and others wither? What returns does a scientific organization get on its investment in public, collaborative technologies? Is there a way to see that contributors and the host organization all reap the rewards of their work?

From the article in Nature.

The science wikis face a tougher challenge in building critical mass, if only because they’re aiming at a much smaller audience. One obvious strategy is to avoid fragmenting that audience. As Evelo points out, “biologists aren’t going to work on a dozen wikis to see which will survive”. They are going to want the various wikis to be interoperable and mutually supporting, so that the data they enter in one can be easily ported to another — or will even flow to all the appropriate sites automatically.