If a company fails to adapt to change, its competitors put it out of business. In extreme cases, an entire industry sector fails to keep up with the times and is eliminated or radically transformed. For academic research on the other hand, such external pressure is minimal since evaluation is mostly based on peer review. Therefore a culture of soul searching, meta-discussion about research practices and norms, and adaptation to technological change is essential for the health of academic communities.
I can’t speak for other disciplines, but within computer science, I’ve always felt that these meta discussions were inadequate — in terms of volume, vigor, and format. They happened mostly at conferences were largely limited to more senior/well-connected researchers, and lagged behind some of the serious problems that have accumulated such as restrictive publisher copyrights and very low acceptance rates at journals and conferences. In particular, in spite of the occasional blog post and ensuing commentary, I’ve felt that computer scientists have pretty much failed to utilize the Internet for these meta-discussions.
Until now. Google+ has changed all that.
Even though the number of Google+ users is still fairly small, there is a robust discussion going on whose volume already seems to have exceeded that of blogs. Here are some topics being discussed by fellow computer scientists that I saw on my stream in a two-week period (roughly the first two weeks of December, before things went dead for the holidays):
prepublication and distributing papers on arXiv, benefits vs drawbacks of anonymous submissions, the old journals vs. conferences debate, asshole reviewers and bad reviews, reviewers asking you to cite their unrelated paper, acceptance rates at top conferences, submission rates and reviewer load, conference spam and junk conferences, science journalism and blogging, citation managers, LaTeX showing its age, the grant proposal writing process, faculty salary, tips on giving talks, and discussions about which topics are hot and worth investigating.
The obvious question is, why Google+? I think there is a multitude of reasons. Privacy is certainly one. No community likes “airing dirty laundry in public,” and the ability to make limited posts is a huge benefit of Google+ over blogs. But this can’t be the only reason because at least half of the discussions I mentioned are public (but then again, posters might perceive them as 'less public' than blogs). Another problem with blog discussions is that the anonymity frequently led to incivility on the more contentious topics.
A third reason could be the way in which information and ideas percolate through communities on Google+ via the 'share' feature. Finally, part of it could simply be good timing. It’s fairly obvious to anyone who’s used Facebook or Twitter that the design of those sites isn’t suitable for the use-case I'm talking about; on the other hand, if Google had waited a couple of years it’s possible that a dedicated site like academia.edu might have gained traction as a discussion forum.
In my experience, the Internet isn’t anywhere close to replacing face-to-face communication for actual research collaboration, but as for meta-discussion, there is no reason to be dependent on physical gatherings. I will go out on a limb and predict that Google+ will take over as the default medium for these things. While I’m still speaking mainly about computer science, I suspect this is true more broadly. If you’re a researcher who’s not using the site yet, now would be a good time to give it a try.
 Proponents of pseudonymity often refuse to acknowledge this and other drawbacks of pseudonymous discussion, which I find disingenuous.
You can hold a few things in your head (register). Not more than a dozen or two in your active memory, but you can recall any of them pretty much instantly. Information that's important to you you'll often keep close by, either on sheets of loose-leaf paper on your working desk (L1 cache) a couple seconds away, or in a one of a handfull of books in your place (L2 and up cache) which is so well organized that no individual piece of information is more than a dozen or so seconds away.
If you can't find what you're looking for there, you'll have to make a quick stop at the library down the street (RAM, i.e. main memory). Fortunately, it's close enough that you can go down and grab a book and get back to work in only ~8 and a half minutes, and it's enormous, some are thousands of times the size of a typical strip-mall book store. A little inconvenient, until you remember that this library has a free delivery service, so it's really no bother at all so long as you can still find things to work on while you wait.
But the local library mostly just stocks things on demand (which is fair, your bookcases, worksheets, and even the dozen or two facts you hold in your head are mostly the same way). The problem is that when you need something that's not there, it can take a while to get it. How long? Think Amazon.com in the age of exploration. They send out an old wooden boat and it could be a week, could a month, and it's not unusual to wait 3 years before you hear a response.
Welcome to the world of hard disk storage, where your information is retrieved by making plates of metal spin really fast. Many metric tons of sweat have been spent making this as fast as possible, but it's hard to keep up with electrons flowing through wires.
So when someone says that Solid State Disks are awesome, it's because they're able to turn that slow, unpredictable old sailing ship into a streamlined steam-powered vessel. A good SSD can often make the voyage in less than a week, sometimes in little more than a day. It can also make many thousands more quests for information per year.
(If you're looking for an SSD, I recommend the OCZ Vertex 3, just upgraded my laptop with one, and the difference is striking!)
[credit inspiration for this post: http://www.phy.duke.edu/~rgb/Beowulf/beowulf_book/beowulf_book/node24.html and http://antirobotrobot.tumblr.com/post/17138289530/the-software-stack-and-latency ]
Peng Dai is currently a PhD student in Department of Computer Science and Engineering, University of Washington. He is working with Dr. Daniel S. Weld and Dr. Mausam. Peng got his Master of Science degrees from University of Kentucky and Singapore-MIT Alliance, and his Bachelor of Science degree from Department of Computer Science, Nanjing University.
- University of Washingtonpresent
- University of Washington
- University of Massachusetts
- University of Kentucky
- National University of Singapore
- Nanjing University
- Nanjing Foreign Languages School
- Langya Primary School