Web 2.0 for Biologists–Are any of the current tools worth using?

This is a presentation I gave last weekend at the Southwest Regional Society for Developmental Biology Meeting. It’s an updated version of an earlier talk posted here. It’s kind of a 180 degrees turn from the previous talk, in that the first one was delivered to publishers, and this one was delivered to scientists. Here I’ve tried to include the thoughtful comments and helpful suggestions that readers made on the first talk, and have also tried to point out currently useful tools and interesting future directions. I don’t come at this subject from the point of view of a programmer, that’s not my background. I’m approaching it as 1) a publisher, who wants to build these tools into our journals and online products to make them more useful, and 2) as a former research scientist, with a thought toward what tools would have made my life easier when I was at the bench. The same caveat applies as last time–I work for a biology publisher, and am a former biologist. My comments and analysis of the culture here refer to that culture specifically (and I’ll try to avoid using the generic word “scientist” where it’s inappropriate). Different cultures have different needs. Certain fields of science collect types of data that more obviously fit in with Web 2.0 approaches. These approaches may not apply directly to the world of wet-bench biology, but they do serve as valuable pointers and directions worth watching. I want to be clear that I’m not writing Web 2.0 off as useless. What I’m interested in doing is separating the wheat from the chaff. Much of what is currently being done under this umbrella is useless and doomed. But there are some gems already available and despite many likely failures, aspects of those failures are worth recognizing and incorporating into future efforts.

If you read the first talk, sorry for the redundancies, and sorry for re-using some of the same jokes. I’ll work on new ones for the next presentation.

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A quick aside–I know this is a really long article, and I apologize if it’s tough to read that much. It’s basically a transcript of a 30 minute talk. I’m still looking for a better way to present such a talk as an online document, so suggestions are welcome. I’ve taken a look at Slideshare, and I don’t see how that would make things any faster to read or easier to parse. Having the slides in a slideshow format is not all that meaningful without the text (no one likes a talk where the speaker just reads off of their slides). Also, Slideshare spent all of yesterday telling me that my 20 MB PowerPoint file is bigger than their 30 MB size limit. Today, it’s suddenly an acceptable size, but my slideshow has now been “processing” for over 18 hours. I’ll embed it here if it ever gets completed, but so far I’m giving Slideshare a big thumbs down.

As previously, I started the talk with a quick intro to Cold Spring Harbor Laboratory, CSHL Press, and CSH Protocols. I’ll skip that here.

Web 2.0 is a big buzzword these days. Some people find the term too vague, and some consider it already outdated. What does it mean? In general, it refers to projects with at least some of the following principles:

1) web as platform—applications are built to run online, rather than on the computer or on one particular operating system.
2) connecting people through social networks, taking advantage of the power of that connectivity
3) user generates the content, often the user generates the design. Blogs, wikis, etc.
4) Repurposing of content. In web 2.0 content is meant to be open for anyone to grab, and re-use or reformat into a new context.

(image comes from here)

What’s happening in this world for biologists? Here’s a rough list, far from complete, that I put together in about 20 minutes on Google. Many of these properties are owned by big publishing houses, some are from individual entrepreneurs, some come from science communities. The list includes “social networking sites” which host blogs, connect collaborators, discussion boards, etc., “referral sites” which let you tag and promote interesting papers or store all of your references online, and a few others endeavors, some incorporating wikipedia-type information, others looking to take advantage of the growth in online video. So, the question is, how are these sites doing, are they being used by mainstream biologists?

I’ve been conducting an informal poll for the last six months, asking every biologist I encounter in my editorial work what science blogs they read regularly, what social networking science websites they use, where they’ve left comments on published papers. I’ve spoken with undergraduates, graduate students, postdocs, PI’s and department chairs and have yet to see any significant positive response. Granted this isn’t a random sample, but several hundred biologists later, I’m definitely willing to call it a trend. (I’ve cleverly illustrated this concept using the parlance of the internet. We all know the internet was invented for selling pornography, but happily, our society has evolved to a point where the internet is now used as a medium for displaying cute pictures of cats). This response has been really disappointing. If you read the science news, or if you spend much time in the science blogosphere, everyone seems to be talking about these great tools and the changes they’re making in research science. But when you step away from the enthusiasts/early adopters and speak with the majority of biologists, you find out that they’re not aware of these tools, nor do they have much interest in using them.

I’ll try to talk about why we’re seeing this reaction from the community, why things haven’t caught on, then I’ll talk about about the most interesting directions and tools I’ve found. I’m not sure that there are very many tools I can recommend wholeheartedly, but there are a few, and there are some directions that show great promise. One thing to remember is that all of these tools are “works in progress” and this is very early in their evolution. Many are pointless and doomed, others have some good reasoning behind them but need a lot of polishing to be really useful. It has been suggested to me that it’s way too early in the development of Web 2.0 to expect mainstream use, and that certainly may be the case. However, if these tools are ever going to catch on, they need to address the issues I’ll discuss here.

There’s been a real rush to have a Science Web 2.0 presence, but not a lot of time seems to have been spent on really addressing the needs of the cultures involved. For online businesses, there’s the concept of the “first mover advantage”. You see a lot of efforts being made both by large corporations and individuals hoping to catch this advantage. They’re trying to establish a presence, get users signed on, and then they’ll figure out a business model, or a strategy for doing something useful later on. The idea seems to be throwing a bunch of stuff up against the wall and seeing what sticks. Most of what’s been done has been to look at what has worked for other cultures and to just copy it and dress it up as being “for scientists”. However, scientists, biologists in particular, have a very different culture than say, Battlestar Galactica fans, and very different needs.

(Image from here)

So what are they missing? Time is the key component here. Much of Web 2.0 is based on the idea of user-created content. You put up a site, the users create the content. It requires a hefty time investment from the users. The problem is, you’re dealing with a base of users who are overscheduled and overworked. The quote used here from a Postdoc is important:

“I can barely keep up with the literature in my field and with what my labmates are doing. Who has time to spend reading some grad student’s blog?”

Information overload is a bigger problem than a lack of ability to find information. Dumping more and more user-created content into the mix just exacerbates things. We need efficiencies, ways to organize information and take it in faster rather than being given a second mountain of material to wade through. More on this later, including some tools that are built to address the very common plea, “help me keep up!”

You also have the paradox that those whose input would matter most to these sites are the least likely to contribute. I’m more interested in reading comments from a prominent researcher, or seeing her tags on papers that she finds interesting, rather than the less-informative opinions of a beginning graduate student. And yet those early graduate students are much more likely to be active on these sites because they’re more likely to have the time to spend there. Later in their careers, as they become more successful, their schedules get more crowded, and participation will wane just as it is becoming most valuable.

(Image from here)

Expediency is another important factor. If you need an answer to your question, are you better off doing a directed search for someone who knows the answer, or just throwing the question out into the community in hopes that someone will rescue you? On CSH Protocols, we have discussion forums on every protocol. It seemed like a really good idea when we launched—if you’re having a problem with a given protocol, you could ask a question and someone else using the protocol would hopefully answer you. We’ve seen something like 4 or 5 total comments left on the site in the year and 3/4 of our existence (that’s on over 1100 articles!). The only answers that have been posted to questions asked are from our editorial staff, not from other readers. If I need help with running my experiment, I can’t wait months for an answer. Graduate school is already long enough!

Also factor in that you’re quite likely using reagents that are either expensive or hard to come by (or often both). You have to decide if you’re willing to trust the advice of a random stranger here, rather than being really sure you’ve found an expert.

Nearly every biology journal that I’ve seen create a commenting system has followed up that creation with an editorial, a few months later, wondering why no one is using these commenting system. Expediency is one reason. Another big reason is a complete lack of incentive. Again, you’ve got a limited amount of time, so why spend it on something for which you receive no credit? Where’s the upside in leaving a comment on someone’s paper? Are you really likely to spend your spare time wandering through our published protocols looking for poor souls in need of advice? Why would you waste your valuable time looking to play the good samaritan when youve got work to do?

It’s interesting, because the same doesn’t seem to hold true for other cultures in science. Medical doctors seem to love to participate in online commentaries and chats. Computer scientists seem to do little else! I’ll talk a little more about some of these cultural factors later, although there’s no clear cut cultural difference that separates us from other scientists.

This lack of incentive extends beyond commenting on papers. Wikis are defined as collaborative websites where the users create, edit, link and organize the content. Most wikis are based on the idea of anonymous contributions. Community and resource building are both important things, but how do they balance with career building?

Why write a wikipedia entry when instead you could be writing a review article for publication? There is currently no system of recognition available for such contributions. At least there’s no system readily recognized by thesis, job search or tenure committees. Wikis have other problems as well, the few times I’ve tried to contribute to articles I’ve found things incredibly frustrating, but that’s a matter for a different blog post.

Another big reason for the lack of adoption of new technologies is inertia. By “inertia”, I mean a couple of related things.

First, most Web 2.0 sites aren’t useful until they’ve got a high level of participation. If the users are creating content, no users = no content. If there’s no content, no users are going to bother participating, rinse, lather, repeat, the circle goes around and around. A social network without a lot of members is not very useful. And remember the caveat from earlier. Most content is being created by those with the most time on their hands who are the least likeliest to be creating the content you want.

This becomes even further burdened by the proliferation of “me too” sites. Here you see nine different sites that all serve similar purposes. If I have limited time and each site requires a substantial time investment, how am I going to choose which one I’ll use when they all offer essentially the same thing? What happens instead is that most people choose not to choose and sit things out until a clear winner emerges. For those who do pick a site, the site they’ve chosen is only one of many, so it sees 1/9th the traffic than if it were the only one, which means less content, which means it’s less useful. There’s an argument to be made that it’s worth waiting for quality to filter out before investing your time and effort.

A real key to remember when choosing between these new tools is to look for open-ness. You want a tool that uses standard file formats, that lets you import data from elsewhere, and export data to take elsewhere. The smart designers of the better tools are confident enough in their sites that they build in this functionality. You make an effort on site A, you can take it over to site B and plug it in and check it out. It helps you avoid lock-in, it lets you get more out of the same amount of effort, and it lets you try more than one tool to find what works best for you.

The second thing I mean by “inertia” comes from the idea of “if it ain’t broke, don’t fix it”. If I’ve already got a way to do something, and it works okay, it’s going to take a lot to make me change to a new way. Doing something new takes effort and (again) time. People are afraid of change, and retraining can be annoying and time consuming. If you want me to switch, you have to not just be better, you have to be way better for me to make that effort.

So far, a lot of these new tools aren’t well designed, they’re hard to use, hard to figure out and many don’t offer anything that much better than what you’re already doing. The added value received from using a site must outweigh the effort you’re required to put in.

(Image from here)

There are also cultural reasons why the current tools are failing to catch on. I keep seeing the phrase “Myspace for scientists” used to describe new online efforts and it drives me crazy (examples here, here, here, here, here, here,…….).. Myspace is targeted at a particular culture, and while it works well for that culture, the idea of shoehorning other groups into its functionality is flawed. Biologists interact in very different ways than teenagers and their peers, or rock bands and their fans. Biologists don’t find collaborators by chatting online with strangers. Most of us aren’t interested in sharing scandalous pictures of our drunken revelries.

Getting back to the idea of having online discussion groups on published papers, here’s another point where the concept fails to fit the culture. Think about meetings you’ve been to, and the behavior of the participants, and you’ll some consistent patterns. The big shots and the networkers currently on the job market sit in the front rows and ask the majority of the questions of the speaker. The graduate students sit quietly at the back and if they have a question, they approach the speaker after the talk in private. I’m not saying this is a good thing, but there does seem to be a certain etiquette involved, or at least a wariness to expose oneself in public. Online behavioral patterns tend to follow offline patterns. There is a great hesitancy to publicly go on the record criticizing a colleague. Sure, in private, at the bar, scientists are great critics. But are you willing to publicly leave a critical comment on a paper where everyone can see it for all time? Are you willing to criticize work by someone who may one day be deciding on your grants, peer reviewing your own papers or chairing a job search committee? Unlike teenagers chatting, professionals making public statements have responsibilities and there are consequences to their words.

And one other point that should be obvious if you know your community —the vast majority of papers are downloaded as pdf files, which are then printed out and read. There’s no way to leave a comment on a printout of a pdf. You’d have to be mighty motivated to go back to the journal site, track down the individual paper in question and leave a comment for the author.

Enough generalities and social analysis. Let’s talk about specific tools and directions. Probably the ones most familiar to you are blogs. This is a visual representation of the blogosphere made last year. There are a lot of blogs out there. I think this only compounds the issues of information overload that we’re currently facing. Adding more blogs means adding more noise to filter. It’s unclear to me how many blogs the system is going to be able to support. The best-read science blogs are also the best-written science blogs, often by professional writers or well-established leaders of their fields. Again, if information overload is a problem, then if every graduate student out there starts blogging, who’s going to read those blogs? How will they find the time?

Should you be blogging? The answer varies, depending on who you ask. Like the other tools I’ll mention today, blogging (at least blogging well) takes a lot of time and effort. If you’re going to commit that time and effort, you should be clear on what you’re getting out of it, and who your audience really is.

The first thing to think about is the world of science blogging. Who really reads science blogs?

1) Other science bloggers
I read a lot of biology blogs. One of the first things you notice when doing so is that the world of biology blogging is kind of insular and circular. Bloggers write blog entries about other bloggers and their blogs. Go read any biology blog and take a look at the comments people leave. Nearly every single one contains a link to the commenter’s own blog. There’s a relatively small circular group here, of scientists who are interested in blogging, who write blogs and who read blogs and who leave comments on other peoples’ blogs. These are the enthusiasts, not the mainstream. While they may be harbingers of future developments, right now they tend to reinforce one another’s ideas about the importance of what they’re doing. I should note that my own blog posts about blogging and Web 2.0 get far more interest and far more response than posts about science or experimental methods.

2) Non-scientists / Non-specialists
Many of the readers of science blogs fall into this category. They are people who are interested in science but that don’t get their information from research papers. These can be non-scientists, or scientists who are not specialists in your given field. The quote used on the slide is from the blogging physicist (not the evolutionary biologist) Sean Carroll. As he notes, scientists already have very efficient methods of communicating their work with one another (publishing papers, giving talks, e-mail). Blogs, for him, are a great way to reach people outside of your field, and, as he puts it, “We don’t have a lot of goals other than us having fun.” There is obviously great value in outreach, in education, in sharing your science with those outside of your own area.

The next two sets of readers are probably less important to you, but can have their uses (particularly for us publishers)

3) Journalists
Science journalists are clearly reading blogs and using them as fodder for story ideas. Blogs serve as a great place for a scientist to translate an important finding into clear language so journalists can pick up on the significance of the discovery. Blogs can be more effective than press releases, as they can cover a subject in much more detail and over a longer period of time.

4) Search Engines
If you want people to find out more about your lab, about the work you’re doing, odds are they’re going to find you through Google. Blogs help you out here, as they create more opportunities for your information to come up in a web search. By blogging about your research, you create new search strings, new ways for searchers to find your articles. By adding links to your published papers and your lab’s website, you help increase the position of your material in search engine listings. That’s one of the main reasons we started the Bench Marks blog, really thinking of it more as a marketing endeavor than anything else. It helps raise awareness about the material we’re publishing, drives traffic to our journal site and helps our search rankings.

21) What does blogging do for your career? On the positive side, talk to any science blogger, and they’ll rave about what it’s done for them. It connects you to a network of like-minded individuals. It may lead to relationships, collaborations, jobs, etc. It’s a way of getting your name out there, of getting recognition. It lets you network without leaving home. It also, over time, should improve your writing skills.

22) But, there are dangers involved as well. There are professors who blog who feel like their blogs were detrimental in their drives to attain tenure. It gets your name out there, but not for your actual work—it’s unclear how much that’s going to help you get a job. The internet has a tendency towards arguments, flamewars and exaggerations. If you do choose to be a science blogger, my advice is to be as professional as possible. Remember that this is a permanent, public record. Personally, I’m very glad blogs didn’t exist when I was in grad school. Who knows what I would have written about that I’d be embarrassed by today.

Social networks—You know these as things like Myspace, or Facebook. Recent numbers are showing that participation in these sorts of sites is beginning to wane (UK numbers here). Users are spending less and less time obsessively checking their Myspace page for messages from their friends. The trendiness may be fading, but there are some useful ways of interacting and consolidating information that these sites provide. The consensus view is that these social types of programs will become ubiquitous, and get built into lots of other programs and sites. Social networking behavior will continue, but social networking sites will disappear. You’ll stop having to go to particular sites to do these things, they’ll instead be built in everywhere.

In the meantime, as I said earlier, scientists don’t need social networks for chatting with online friends, or posting pictures of last weekend’s drunken bash. For scientists, social networks are all about jobs, finding openings or finding candidates for openings. SciLink is a site that understands this, and they’ve taken the LinkedIn model and tried to make a similar site for scientists (the problem here is that most scientists seem to be cutting out the middleman and just going directly to LinkedIn). Unlike Myspace, it’s not a place you would visit every day to check in on things. You’d set up a page, and really only spend much time there during the rare periods of your career when you’re actively seeking a job, or actively trying to hire someone.

I mentioned wikis earlier, collaborative websites where the users create, edit, link and organize the content.

GoPubMed is a tool that I can heartily recommend. GoPubMed ties into PubMed and searches the database, just like you normally would. But, it extends things from there, creating a much more useful search tool. First, they do automated text-mining of each paper, bringing out key words and contexts, and they’ve built a subject taxonomy based on this. But, since this automated semantic text mining is imperfect, they put their users to work to create what’s called a “folksonomy”, a collaborative indexing of the content. The “curators” as they’re called here, correct the usage of terms and improve the taxonomy created by the automated text mining. It’s a great tool for narrowing down your PubMed searches. Let’s say you’re looking for a paper on signal transduction by someone with the last name “Smith”. Search for “Smith” and PubMed currently gives you approx 150,000 results. GoPubMed let’s you very quickly pare this down to 537 papers on “biological processes” and even better, 73 papers on “signal transduction. It’s a real timesaver, and can help others find your papers to read them and cite them, which is always a good thing.

Some of the more prominent Web 2.0 offerings are sites where you can keep your reference lists online. The idea is that you upload your list of references, you go through them and add subject tags to each one and now you’ve got an organizational system. You can now get at your reference list from any computer connected to the internet. You can very easily add new papers to your reference list with a few clicks. You can share the links to papers with colleagues very easily. You can import and export this list in a variety of formats, for things like EndNote. You can add resources to your lists that aren’t papers, really, anything that has a link can go in. The sites also serve as discovery tools—you can go and see what papers other users have tagged with a particular term, potentially finding material you would not have encountered on your own.

Here’s Connotea, Nature’s offering in this area. As you can see, I’ve got a set of papers tagged here, along with blog entries. You can see the various tags I’ve used, and the links take you out to the journal article (or anything) in question.

But all is not perfect. I don’t see the great benefit of keeping this information online. How often do you have access to a computer, but not your computer, and you need to get to a particular reference that you couldn’t find through a PubMed/Google search? Remember, you can only access your reference list if you can get online—tough to do if you’re writing a manuscript on an airplane. You can only access the actual papers if you’re online somewhere that has a subscription to that particular journal. Adding tags is incredibly tedious, particularly if you’ve amassed a reference list that’s thousands of articles long. I did around 60 papers and nearly died. You can’t really do anything with content that’s not online, like a book chapter. You can’t search within the actual papers themselves through this system. And quite frankly, the discovery tools are at this point fairly useless, too much noise and not enough signal. Not enough people are using the systems to really help much, and as I’ve said before, they may not be the authoritative voices you’re looking for. Ask any editor about author-supplied keywords on papers and you’ll be amazed at the variety of keywords different authors will use to describe similar work. Which makes discovery harder. Also note that if you do want to use these discovery tools, there’s no requirement that you contribute your own list of papers with tags.

These sites are probably worth giving a look. It’s free to set up an account, and if you’re already using EndNote, uploading your reference list is trivial. Play around a little, and see if it’s going to be useful before spending much time tagging your lists. If your list is short, or you’re just starting out, then this is a great opportunity. You can get ahead of the game here, and set yourself up to be organized for the rest of your career. If you’ve already got 1500 papers on your reference list, you’re going to need to think about whether you want to put forth the effort needed to organize in this manner. Try more than one site, as you should be able to import and export back and forth between the various sites to see which one suits you best.

A caveat—I started on Connotea, put up a list of papers and added tags. Then I exported that data and brought it into several other sites. Sometimes this doesn’t work as well as you’d like it to. Here’s my CiteULike page. When I imported from Connotea, it kept one or two of my tags on imported papers, but seems to have lost some of them as well.

Here’s my page on 2collab, Elsevier’s offering. Here, it kept all of my tags, but seems to have lost all of the article titles, listing them all as “dx.doi.org”, which is not all that helpful to browse through. So the systems are far from perfect. They’re still evolving, which makes me hesitant to enthusiastically recommend them at this point, as none of them really work as well as you would like. I think we really need tools that can semantically parse papers and do the tagging for you before these types of sites really fulfill their potential.

As an alternative, think instead about programs that allow you do similar things, but offline, with the information stored on your own computer. I tend to have a bias toward things I can control, I want to buy and own CD’s or song downloads, I don’t want to subscribe to a music system that could disappear at any moment, taking all my playlists with it. If it’s on my computer, I control it, the terms of service can’t be secretly changed, my data can’t disappear if the company pulls the plug. It’s not very Web 2.0, but it is worth investigating.

These organizational programs deal with pdf files, which you’ve probably already downloaded hundreds if not thousands, all of which have obscure file names that you can’t be bothered to rename and organize. What’s really great here compared to the online programs is that you can search the full text of these pdf’s. A good search ability obviates the need for tagging and folders and time-consuming organizational schemes. These things are still nice, but a good text search will take you to the paper you want much more efficiently than wading through a group of articles with a shared tag. With these local reference managers, you don’t have to spend hours tediously adding tags if you don’t want to.

Papers is probably the best of this breed (it’s Mac only, sorry Windows users). Papers lets you import pdf’s you’ve already downloaded, and you match them using PubMed/Google Scholar to get all the metadata on the papers and links to the journal. You can search for new papers and download the pdf’s for those as well, add notes, send copies out to colleagues, etc. You organize here by creating folders (or letting the program create “Smart” folders for you), rather than tagging.

There are some drawbacks here as well. You can only access your lists and references on your own computer. You lose all of the Web 2.0 potential for discovery and community, since it’s basically a private list. Although they promise you can import and find your paper in PubMed with a few clicks, it’s not that easy all of the time. Sometimes it works great, other times it takes some digging to identify the paper. The exporting/importing is, like the online programs, pretty flaky. The Papers program works best with PDF files, so again you have some issues with non-pdf sources of information.

Overall though, I find programs like this (other options for the Mac include Yep and Yojimbo) to be highly useful. They help you get organized and help you find the information you’re seeking with minimal effort required.

Zotero is an interesting open source hybrid between the two types of programs I’ve mentioned. It’s an extension of the Firefox web browser, so you can use it on Windows, Mac and Linux. It’s free and can import/export your data to and from the online resource managers. It integrates well with EndNote, Microsoft Word, OpenOffice and a wide variety of websites and databases. Zotero uses the same folders/collections method of organizing as Papers and also uses tags like online resources. You can attach downloaded pdf’s to specific linked items. You can archive web pages in your browser and take notes directly on web pages. It’s very versatile for both online and offline. On the downside, again, it’s a private list so you lose the discovery and community aspects. You’re also losing the very valuable ability to search the text of papers. Also, like the other offerings mentioned here, it takes a significant time commitment to set up and organize.

On to a few other interesting directions that Web 2.0 is heading for biologists—Gadgets and Widgets. Get ready for these, you’re going to be seeing a lot of them in the very near future. These are basically small, self-contained programs that can be added to any website. You can also use similar things in Microsoft Vista, in the Sidebar, and in Mac OSX in the Dashboard. Google is offering quite a few very useful widgets for research biologists. Here’s a great article from the Bitesize Bio blog with links to their “Top 10 Gadgets for Molecular and Cell Biologists“. These include quick apps for searching PubMed, doing BLAST searches, seeing protein structures, etc. There’s even a lab timer, which is always handy to have.

You can do as I’ve done in this slide, and set up an iGoogle home page with all of the gadgets you want to use, or you can take individual gadgets and put them on your own web page. Ideally you’d set up a page for your lab with these useful tools readily available (or each person in the lab can have their own version). Highwire Press, the Stanford-based company that hosts our journals along with Science, JBC, PNAS and others is launching a new platform later this year that supports and encourages publishers to use gadgets, so expect to see a lot of them coming out from the various journals.

Gadgets are ways to increase your efficiency, to group frequently-used tools together in one easily found location.

Mashups are defined as “a website or application that combines content from more than one source into an integrated experience.”

The idea here is that a new resource is created by taking several other resources and combining them. The classic example is a website that takes real estate listings from Craigslist and combines them with Google Maps, creating a visual interface for apartment hunting. Epispider is an example of a site that combines data from a wide range of medical and public health sources and presents it in a new way. Here you see recent reports of avian influenza presented over time and geographically. Sites like this, as far as I’m concerned, show the real value of Web 2.0 and we need more of them. Mashups can collate vast amounts of data from a wide variety of sources and present it to you in a manner that’s both more meaningful, and quicker to analyze than having to do all that collating yourself.

There are some interesting efforts being made with Mashups in the world of Bioinformatics, here’s one called the Genome Projector.

One last interesting direction, the idea of “workflows”. These are probably more relevant to computational biology and bioinformatics than what most here do. The idea is that it’s often difficult to replicate someone’s results because you can’t recreate step-by-step the process they followed to get them. Sites like MyExperiment and one from the Broad Institute at MIT called Gene Pattern are creating ways of sharing these workflows in a downloadable format, so you can either recreate what someone else did to verify it, or plug your own data into the same process and generate new results. It will be interesting to see if these become standard requirements for publication of work, part of the “Materials and Methods” section of a paper. It will also be interesting to see if this concept is applicable to wet-bench work.

In summary, we’re still in the early days of adapting Web 2.0 for use in science. Not a lot of what’s currently being offered is going to succeed or be around for very long. Even the successful offerings are “works in progress” which will hopefully improve over time. Even so, there are some very useful tools now available, and even more on the horizon that should make your life as a research scientist easier and open new avenues for communication and learning.

(Image from here)

Some final thoughts on what to look for in a Web 2.0 tool:

Look for things that save time, things that help you organize better, and assimilate information faster.

A good tool will fit your needs. Don’t waste your time on tools that don’t offer you something substantial in return. Value added must outweigh effort required.

Always look for open-ness. Look for sites that use standard file formats, that allow you to easily import and export your data and efforts. You don’t want to be locked-in.

Be aware of network effects. The site you choose may not catch on. Is it still going to be of value to you?

And since I like to leave on a positive note, I’ll offer you this drawing from the great Adam Koford. As the internet has taught us, there’s nothing happier than a unicorn, except perhaps for a unicorn eating a bowl of glitter.