The Undercover Economist, Tim Harford, has a good article in today’s Financial Times about the stages in life when different professions are most productive. For example, I did a quick Google/calculation: the average median age of a Nobel Prize winner in physics or chemistry is 55; in the literature and peace prizes, it’s 64. (Sorry, not going to do the full test for statistical difference today). This distinction makes some sense, as the great discoveries in the two scientific subjects are marked by innovation (something that may become replaced by habit with age) and excellence in literature and statesmanship benefits from vast amounts of experience.

But, in keeping with our recent discussions about reform in academia, perhaps the bigger question is whether or not we should be actively targeting funding to match these periods of productivity? A quote from the FT article:

Two of my favourite writers, Malcolm Gladwell and Jonah Lehrer, are worried about this – but from different perspectives. Gladwell, a Galenson fan, worries that our obsession with youthful genius will cause us to reject future late bloomers.

Lehrer has the opposite concern: that funding goes to scientists past their prime. He says the US’s National Institutes of Health (NIH) has been funding ever-older scientists. Thirty years ago, researchers in their early thirties used to receive 10 per cent of NIH grants; by 2006 the figure had fallen to 1 per cent.

From my experience in the UK, I think both groups have good, but different, funding opportunities. Established researchers are well-versed in applying for traditional call-based research grants, whereas young researchers are catered for by a number of fellowship schemes. I haven’t seen much evidence of disciplinary-based bias and to be honest, I think anti-discrimination laws would make it difficult to explicitly exclude a group of talented researchers just because they’ve reached an arbitrary age barrier. Think of Andrew Wiles, who found a proof of Fermat’s Last Theorem but just over the Fields Medal’s age limit of 40.

Ultimately the top performers in these disciplines are so unique that it doesn’t make sense to design generalized development or funding programmes for the rest of us. However we can at least take comfort that our best days may be ahead of us!

Imagine a world where real-time search is the norm. You will get just the information you seek landing on your lap the exact minute it becomes available, without you having to explicitly search for it. Will this change the way you do science? SciSurfer thinks it will.

The release cycle of scientific knowledge is slow. It may take up to 2 years for a paper to get accepted in a journal. The publishing process in itself will add a buffer of a few months (arguably because of the time cost of having a paper edition, even though most people will never use it). So, for some of us, it doesn’t feel like we are missing much if we do not get the latest updates on our field the very same minute they are published. Just going to conferences yearly feels like more than enough. But there is a portion of the academia that needs constant updates on their field, as close to real-time as possible. If you are in the life sciences, getting the latest paper about a molecule or a gene you work on before your competitor does may make or break your career.

For those academics, sciSurfer may be a very valuable tool. The basic idea of sciSurfer is to integrate all journal feeds and search over them. Note that they do not archive RSS, so only the latest articles are available. This is a different way to think about search, closer to twitter’s than to Google’s.

In use

If you are used to RSS feed readers, the interface will look familiar. Left side there’s a list of journals and searches. Every time there’s a new unread item the containing ‘folder’ turns bold. On the right side there’s a list of articles (title, authors, and abstract). The journal it comes from is shown in green. The interface resembles Google reader (in fact, sciSurfer is built on app engine, so it may share code with reader).

What is the advantage of scisurfer over simply subscribing to the RSS feed of the journals? Search. Scisurfer does searches over all the journals they are indexing. This is pretty impressive, because I don’t know of any search engine that works on RSS feeds. Using an RSS reader, the equivalent to scisurfer would be to subscribe to the RSS of all journals, and apply searches over those. This is beyond the capabilities of most destop RSS readers. Implementing search by author, abstract, etc is also beyond the feature set of a normal RSS reader. In fact, it’s not that easy to deal with author names. We all have had the experience of getting papers by people with the same lastname and initials as our intended query term that are NOT the person we are looking for. Thomson Reuters has a solution: researcher ID. Researcher ID is based on the simple idea that each individual would get a unique identification (ID) number acting as a digital “calling card” that the researcher can place anywhere, such as a personal home page, a CV, or a university page. It has been out for more than two years now, so it’s still too early to say whether it has been adopted successfully.

Apart from the reader, there are two other tools, news and journals. Searching journals by name integrates the RSS feeds of otherwise disperse journals. Still, I haven’t found a good use for this tool.

Navigating trends

The main use I can think of for sciSurfer is monitoring Trending topics. We are getting used to explosions in popularity thanks to twitter and Facebook updates. Good twitter clients show you ‘what’s hot’ together with an explanation on why. Even Mendeley is getting status updates these days, making it look more and more like ‘facebook for scientists’.

There are several things to like about sciSurfer.  It integrates with your Google account, so it’s one less login to remember. The devs show that they are on top of things and the result is a fast turnaround when I requested changes. They are very open about feature requests. In my experience, when a journal was not in sciSurfer’s list, the devs added it within hours.

But by far the best result of using sciSurfer is that it makes you aware of what is going on in your field in a way that feels different and pleasant. The most similar feeling that I got online is when I found a neat Phd. student tagging articles in citeUlike that are relevant for me (it’s like finding a gold mine).

Mendeley uses a similar real-time approach in their statistics. For example, they show what are the most read papers per discipline at a given point in time.

I’m not sure one can do searches according to popularity just yet on any of these tools, implementing a real-time soft peer review.

How does sciSurfer plan to make money? The free tool is limited to ten saved searches. They will charge for extra functionality. There’s an iPhone version coming, which may well be another source of funds.

Conclusion

As the number of publications grows, it becomes more and more difficult to follow the latest scientific trends. The approach that sciSurfer takes is that if you know your keywords then it should be trivial to filter the fire hose of information, by doing a trivial keyword match. While keyword match could go a long way, I’m skeptical that the future of search lies in dumb matching. The way I currently filter information is very social, that is, I’m surrounded by people I respect and I ‘feel’ what they believe is good research. If I’m like most researchers, then social filtering would be a natural fit. However, I rarely get value from social networks online (science-wise; no matter how hard social networks try to capture my attention!). It may well be that to form a reputation, scientists need to do far more than posting interesting updates in their microblogging feeds. And for us to follow their recommendations…

It was a matter of time before someone wrote a robot that grabbed latex  and returned an image after latex processing. LaTeXy does exactly that and has just increased tenfold the usefulness of wave for academics.

About two years ago we talked about filehamster. It was  free, unobtrusive, and simpler than doing version control ‘by hand’ (adding numbers to filenames) or ‘by machine’ (using a proper versioning tool such as subversion or mercurial).

Well, since then filehamster has moved on to be a pain in the ass. Now the free version nags you a lot, and the paid versions are not really giving us any outstanding features. Plus as a .NET application, it eats up RAM.

Enter AutoVer. Completely freeware, no nags, and a much better interface to boot. The GUI and options make more sense too. I even use it for coding when I’m doing something small and a mercurial repo would be overkill.

Eventually, all writing applications should enable smooth versioning and real-time collaboration (Office 2010 beta does! Wave and etherpad are not alone anymore). The slider that controls versioning as in a time machine is fantastic. AutoVer would not give you that. The AutoVer model also breaks when you send the manuscript to a collaborator, and he edits it on his machine (often changing the file name). Still, it’s much better than not doing versioning at all or doing it by hand.

By the way, does anyone know an alternative that is cross-platform?

Sometimes I wonder why many humans (me included) have trouble understanding probability. In cognitive science, probabilistic models are taking over most areas. Still, most people struggle with them. Could it be that the notation is just hard to swallow? What’s Wrong with Probability Notation? is a magnificent post that gives some basic reasons:

The first two issues arise in the usual expression of the first step of Bayes’s rule,

,

where each of the four uses of corresponds to a different probability function! In computer science, we’re used to using names to distinguish functions. So and are the same function applied to different arguments. In probability notation, and are different probability functions, picked out by their arguments.

This is one clear communication problem. Ideally we want more people to follow probabilistic reasoning. Doctors, judges, etc all show significant struggles when given probabilities (see e.g., Helping Doctors and Patients Make Sense of Health Statistics).

But how do we tackle this problem? Changing notation is easier said than done. In fact, anyone departing from traditional notation will have to convince reviewers that his notation is better… and add to the risk of cause a less-than-ideal impression.

Any ideas?

AcaWiki is a new wiki aimed at academics. They are asking for summaries of academic research. This could be an excellent exercise for students (i.e., don’t hand me your paper: post it to acaWiki, and let me know when I can look at it).

From reading the FAQ, It’s not clear to me that they are selling it right to the academic community:

What does AcaWiki offer to academic researchers?

AcaWiki offers a web 2.0 way of interacting with the public to increase impact. Research often languishes in academic journals, perhaps read only a few times by infrequent visitors. AcaWiki allows scholars to increase the impact of their research by enabling them to share summaries, long abstracts and literature reviews of their peer-reviewed work online. AcaWiki also encourages discussion by providing a talk page for each research paper.

Hmm, meh. While these are interesting reasons, I doubt academics will rush to fill in summaries. Discussion is covered by reference management sites such as citeUlike. And, of course, to make this work for academics, contributions to acaWiki must be well-evaluated by hiring committees… which is not going to happen any time soon. When faced when the decision of adding one more line to their CV or dedicating a similar stretch of time doing summaries of their articles for acaWiki, what would most academics do?

I still think this could fill a nice niche for student homework. Instead of leaving their work hidden in the HD of their T.A., posting it to acaWiki could be of use to the community. I often have to reread a paper because I’ve forgot most about it, and a good, crowd-refined summary would definitely help.

Just a quick one to highlight The False Prophet. S/he presents a list of reasons why things don’t get done, together with Preventive measures and solutions.

This is quite a finding. Example:

4. Distraction (…)

Preventive measures
When you commit to a project, set a daily/weekly schedule. Consistent time-structure is what gets projects done that last longer than the excitement of inspiration. Working on the project first thing in the morning is one way to head off distraction.
Set up your own status meetings, just as with “dependency”, since, in a way, you are depending on yourself to deliver. Having a regular status meeting with a friend (say, in a phone call) can keep you on track.
See “attention overload”, below.
Solutions (to be used after you’ve gotten distracted)
The 5M method. Note the time. Think of a tiny task that you think you can complete in five minutes. Give yourself an hour to do it. You can do the task right now, and then slack off. You can wait until five minutes are left in the hour and then rush. Odds are, once you do this tiny task, you’ll feel different. You’ll have some momentum. Your brain will now be returning to the work you want to do instead of the distraction. Or perhaps not. You can still slack off the rest of the hour if you prefer. A deal’s a deal.

He also has an interesting post on ‘how to fix grad school’. I like the way he presents arguments, and then tries to shut them down.

False Epiphany» Blog Archive » Incompletion: 15 Causes and Solutions

Looks like Elsevier experiments on how to present scientific papers are starting to get coverage  (on RWW no less).

The basic novelty here is real time search, but everything is peppered with other webby things like comments and AJAX.

The key features of the concept are here, and one can play with working prototypes. They are asking for feedback. I must say this is head and shoulders over reading a pdf on the screen. As highlights: (1) A figure that contains clickable areas so that it can be used as a navigation mechanism to directly access specific sub-sections of the results and figures, (2) references are clustered by sections of the paper they appeared in, and hot-linked.

However, it’s not clear if this kind of effort is just cosmetic or actually an important change. From the RWW article:

Some parts of the available prototypes are interesting but opinion in the scientific community seems split. Is this ground-breaking stuff or yesterday’s news repackaged by another industry threatened by the web? That depends on who you ask.

Let’s see. A publisher is, by definition, someone that helps your ideas reach more people and influence them (or was that a marketer? ). How good are current academic publishers achieving this? Not very well I would say, although it’s not the publisher’s fault only: most academics write in a way that repels readers. The fact is even that a blogger living in the long tail handles audiences orders of magnitudes larger than most academics get with their scholar papers. So one interesting question for academic publishers is how to get our stuff in front of the eyes of the general public, with their ever-decreasing attention span.

In this sense, I think this ‘new way of presenting an article makes it a lot easier to read. So, kudos to Elsevier.

On the other hand, if we want to compete for the attention of the general public, this is woefully inadequate. The Author Interview is a nice touch, but would people care enough to listen to it? Would this interview be helpful towards understanding the article without reading it in detail? Only server stats can answer these questions.

And there are many new ways of gather opinions and solve questions out there. Apart from wikis and forums, there is a new contender: stackOverflow. The basic idea is that the best solutions to a question get voted up. This saves one the effort to go through a thread of  partial answers. It has taken the programming community by storm. Partly because it actually works better than previous solutions (do you remember question answering sites?) and partly because Joel Spolsky and Jeff Altwood backed it and pimped it to their huge audiences. Of course, it wasn’t long before someone (mendicantbug.com) proposed The Stack Overflow of Academia  solution. This is by no means perfect:

The benefits of peer review by the herd are great, but not without pitfalls. First of all, you can be herd-reviewed by morons. Moron 1 might think everything Researcher A publishes is GOLD and gives the thumbs-up no matter how badly the research was done. Ditto on the flipside, with Moron 2 hating everything Researcher A does.

In any case, it’s clearly different to the ‘snail mail’ model of peer review that we still use. The post at stackOveflow is a declaration of principles.

As a commenter notes, the (bigger) problem that remains is that publishers want to be closed and charge for content:

This would be great if it was Google or some other company that doesn’t already charge exorbitant fees. Elsevier is well known to charge some of the highest prices—$300-400 for technical books! If electronic journals with multimedia etc are to take off, it will be because they democratize access to cutting edge science by removing the fees currently charged by academic journals, not b/c Elsevier hires some AJAX programmers. I can only imagine that this will be used as an excuse to charge more for access to Elsevier journals.

Very interesting times. I sense a huge opportunity here somewhere. Michael Nielsen also agrees that Scientific publishing is about to be disrupted. It just not clear to me whether facelifts like what Elsevier proposes are enough, or we need a more radical change.

Maybe I’m getting out of touch, but it’s only now that I found sciencewatch. It’s a service of Thomson Reuters (the makers of Web of Science) that collects and displays statistics on recent trends in science. Example:

Aug 2008 – SCHOLARLY USE OF THE WORLD WIDE WEB – Research Front Map – ScienceWatch.com

This is a citation network that shows highly cited papers on WWW. Diameter relates to citation: the two bigger circles are the paper that proposed the Hirsch index, and King’s paper on the scientific impact of nations. Clicking on the circles provides details on the papers.

There are many other fronts:

• Fast Breaking papers. These papers comprise the top 1% of papers in each field and each year
• Top Topics selects the Research Fronts with the largest absolute increase in size in each of the 22 major fields covered by Essential Science Indicators

Worth keeping an eye on.

This post describes a very efficient way to digitize large amounts of books. Why is this important? If you are an academic you (1) have amassed a large collection of books and (2) are bounded to relocate more than a few times i n your life. Moving books is no fun. Plus being able to grep through your books, and read them even if you are away from home (conference, coffee shop, retreat) is really priceless.