This is one of a bunch of posts on science and the Web. Start here for an overview.
It's been fun to watch (and occasionally help drive) science moving online and taking advantage of the Web. Here are some of my favorite examples.
Simple, easy ways of sharing process abound. Github, bitbucket, and sourceforge are, ultimately, ways to share your research process with executable code. More generally, the open source ethos has sloooowly started to permeate academia. Huzzah.
IPython Notebook has enabled easy executable papers, and is changing the practice of data analysis. See diginorm and the QIIME/ipynb paper in particular. Open, easily reproducible pubs! In my lifetime!
BTW, is it just me, or is there extreme irony in Elsevier pushing executable papers?
Physicists have been using arXiv for decades to post their papers publicly, prior to peer review. It's starting to catch on in some parts of biology, too.
Haldane's Sieve is a blog started by Graham Coop and Joe Pickrell that posts paper titles and abstracts from the q-bio section of arXiv, with the goal of enabling comments and discussion.
This discussion on Haldane's Sieve, and the followup discussion and blog post by Rohan, and then the follow-on arXiv post by the original authors, is a stunning example that exemplifies what we should be doing on every paper.
Making the scientific process more visible, one depressing story at a time.
Experiments in crowd funding.
Wouldn't it be nice if some science, at least, could be funded directly by people who thought it was cool? Ethan Perlstein did that.
The general increase in science blogging and tweeting by scientists.
'nuff said... right?
The rise of Open Access has been nothing short of astonishing. Covered adequately elsewhere, though :)
I love being able to point scientists at an AMI and say, sure, re-run my analysis from scratch, it'll cost ya 8 bucks. Super enabling.
Mechanical turk and other cheap labor.
It's hard to know where this is going, but I bet it'll be cool.
Data archiving sites.
Increasingly sophisticated front ends to massive amounts of scientific data.
I'm sure there are whiz-bang-ier examples, but these are pretty cool 'cause they work and they're used.