Category Archives: Science

Social media sites for scientists

myScience: “social software” for scientists:
[Via O’Really? at Duncan.Hull.name]

myExperimentWith apologies to Jonathan Swift:

“Great sites have little sites upon their back to bite ‘em
And little sites have lesser sites, and so ad infinitum…”

So what happened was, Carole Goble asked on the myExperiment mailing list, “is there a list of scientist social networking sites”? Here is first attempt at such a list (not comprehensive), you’ll have to decide for yourself which are the great, greater, little and lesser sites.

For simplicity, I’ll break social software down into social networking, data sharing, blogging, ranking and video. These categories aren’t exclusive, as some sites do more than one of these tasks, but they help to classify the wild wild web of social software.
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The sites listed here are some very useful ones to get started with scientific Web 2.0 sites. Although ‘out in the wild’, they are where the cutting edge of Open Science is taking place. Thus, they are useful touchstones for the latest innovations.

Not all really solve an urgent problem but that is the nature of Web 2.0. Start with something simple and move towards perfection. Along the way, urgent problems may get solved.

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Square One: The Knowing Doing Gap

tunnel by ThunderChild the Magnificent
Square One: The Knowing Doing Gap:
[Via Creativity Central]

Let’s go back 1999. Crown Prince Abdullah becomes the ruler of Jordan on the death of his father, King Hussein. Lance Armstrong wins first Tour de France. And most importantly Family Guy airs its pilot episode.

It’s also the year that Jeffrey Pfeffer and Robert Sutton wrote The Knowing-Doing Gap. Nearly a decade later a significant number of companies have amnesia. A lot of mangers read the book. A lot of managers ignored what they learned.

Their preface does a masterful job of setting up the premise. “We wrote this book because we wanted to understand why so many managers know so much about organizational performance, say so many smart things about how to achieve performance, and work so hard, yet are trapped in firms that do so many things they know will undermine performance.”

In a nutshell: There are more and more books and articles, more training programs and seminars and more knowledge that, although valid, often had little or no impact on what managers actually did.

Nothing has really changed.

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In my rubric, knowledge allows decisions to be made and actions to be taken. Data interacts with humans to gain context and become information. Information interacts with human social networks to become knowledge. While knowledge allows decisions to be made, widsom permits the correct decision to be made.

Knowledge, by itself, does not guarantee that the decision will be the correct one. It does permit a decision to be made, even if the decision is to collect more data. Wisdom often requires several false starts to be taken before the right path can be found. In many settings, groups actually learn more from their mistakes than from a success.

P.S.

If you want to dig a little deeper, here are a few lines in an interview that Pheffer did with Fast Company

“If companies genuinely want to move from knowing to doing, they need to build a forgiveness framework — a tolerance for error and failure — into their culture. A company that wants you to come up with a smart idea, implement that idea quickly, and learn in the process has to be willing to cut you some slack. You need to be able to try things, even if you think that you might fail.

The absolute opposite mind-set is one that appears to be enjoying a lot of favor at the moment: the notion that we have to hold people accountable for their performance. Companies today are holding their employees accountable — not only for trying and learning new things, but also for the results of their actions. If you want to see how that mind-set affects performance, compare the ways that American Airlines and Southwest Airlines approach accountability — and then compare those two airlines’ performances.

American Airlines has decided to emphasize accountability, right down to the departmental — and even the individual — level. If a plane is late, American wants to know whose fault it is. So if a plane is late, what do American employees do? They spend all of their time making sure that they don’t get blamed for it. And while everyone is busy covering up, no one is thinking about the customer.

Southwest Airlines has a system for covering late arrivals: It’s called “team delay.” Southwest doesn’t worry too much about accountability; it isn’t interested in pinning blame. The company is interested only in getting the plane in the air and in learning how to prevent delays from happening in the future.

Now ask yourself this: If you’re going to be held accountable for every mistake that you make, how many chances are you going to take? How eager are you going to be to convert your ideas into actions?

So the final point from Square One is that a learning culture driven by creativity and innovation must allow mistakes to be made. The goal of mistakes is to learn from them, not to assign blame. People must be recognized for the attempt, not always for the solution.

One of the strong points of Web 2.0 tools is that they create much more openness and transparency. This makes it much easier to tell identify someone who pushes the envelope in order to help create knowledge that is useful to the organization. If the only way to succeed is never to fail, then the organization will eventually find itself with only followers and no leaders in creativity.

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Innovation as a job

golf ball by makelessnoise
Innovation Development:
[Via InnoCentive]
This site uses new tools to solve problems. It essentially acts as a broker between organizations that need problems solved and the large external community that may be able to find a solution.

The rewards can be pretty substantial if someone can become a successful solver. The site not only has problems in specific areas, but there are pavilions sponsored by single entities for directed solutions. The Rockefeller Foundation Accelerating Innovation for Development is one such organization.

So the possibility exists that external investigators could solve internal problems, and make a reasonable living at it. It will be interesting to see if this does become a form of livelihood.

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Cutting edge Open Science

lecture hall by yusunkwon
Best. Freshmen. Evar.:
[Via Unqualified Offerings]

By Thoreau

I decided to give my freshmen a taste of real physics. I offered extra credit to anybody who could give me a useful critique of my grant proposal. Amazingly enough, two of my students actually rose to the occasion. Although they couldn’t really dissect the science, they could tell that I wasn’t really explaining why this would be significant for the field, and they told me what I’d need to say to convince them of the significance. (I guess some people just can’t appreciate the inherent AWESOMENESS of simulating a new technique for optical nanolithography and identifying the necessary molecular parameters.) They earned themselves some extra credit points for the upcoming midterm. Prior to this these students flew under my radar, but if this grant gets funded, they’ll be the first ones that I consider for research assistantships.

I don’t know many researchers who would do this but Thoreau accomplished something very useful. Not only were several deficiencies in the grant identified but the students may have lined up some nice work for themselves. A nice win-win situation.

I think the extra-credit idea is a nice approach. Anyone who can make it through a government grant (which can range well over 60 or so pages) should get some credit just for making it through. The students were able to identify holes even without understanding the exact protocols.

I wonder if this could be applied further down the system – during the grant review process. Not have students critique but find a way to open up the review process to a wider group of people?

I know from comments reviewers have given my grants that sometimes they really did not read what was written, since the text directly contradicted their comments. I have had comments from two reviewers that directly contradicted each other.

Now, these days, very few grants are awarded the first time they are submitted. So being able to answer comments is important. But what if the comments themselves are useless? Perhaps using a more Long Tail approach would help.

Obviously there are barriers to overcome (e.g. proprietary information) but I wonder?

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The Community Speaks

ginger by twoblueday
These three posts run the gamut from exuberance to wonder to doubt to reconciliation:

A Breakthrough In Taxonomy?:
So Much For Taxonomies:
Taxonomies Again — What Behavior Do We Want?:
[Via A Journey In Social Media]

They describe the process of creating taxonomies for a group of communities, an attempt to create some order. The very rapid path this took, from the excitement of a brand new idea, its implementation and then the very rapid feedback all demonstrate the power of Web 2.0. Life moves faster.

The problem here is probably a very old one. Some people feel better with a described space, using tags that mean specific things. The tags define the space. Others like the space to define the tags. There will always be a conflict here, between those who want an orderly desktop and those who prefer an unorganized one, especially if both types are represented in the community.

Neither view has a monopoly on wisdom. As brought out here, it is operational the difference between a search and a browse. Tags make searches much easier and allows people to find the exact information they want. The path to the information is sharply defined.

Browsers like to take a less defined path to the information. They like little cul-de-sacs and interesting dead ends. The surprise of new spaces is innervating for them.

One group will always find what they are looking for. The other will be surprised at the novel things they happen upon.

The approach described here was not satisfactory to the users, they let people know and the leaders of the taxonomy project quickly tried to reel it back in and find figure out what to do. They pulled back and asked “What question are we trying to answer?”

They understood that the problem was really getting new users on board as quickly as possible. Here a taxonomy would help them get started. But there are other ways to help newbies that would not disrupt the established users. Now they can try to fix the real problem.

Web 2.0 approaches allowed them to reach this conclusion in just a few days, rather than months, something that happened in the Web 1.0 world.

We tried this at Immunex, with defined tags being used for research projects. The Bioinformatic people spent months putting together the applications to allow tags to be attached to research projects. They finally rolled them out and they were a failure.

The problem was that the users could not define the tags. They were created by some unknown person. So what happens when a new project did not have an appropriate tag? Do you try and use something close, even though it might corrupt the system? Do you leave it blank, subverting the entire purpose? How do new tags get added? Who decides that they should be?

The tags never really got fully utilized. Research moved too fast to rely totally on pre-defined tags. Different people would categorize the same project differently. Without flexibility, too many projects would just get tagged with ‘Other’ negating the whole purpose.

A useful system has to be respectful of the users. It has to be malleable enough to have both structure and flexibility. It would also encourage browsing as easily as it does searching. Not easy things to do. But EMC will get to it faster by using a Web 2.0 approach.

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A New Page – What is Science 2.0?

Well, Science 2.0 must be the next full release after Science 1.5.b13, right? Not quite. It takes its lead from applying Web 2.0 approaches to scientific research. So, what is Web 2.0?

In 2005, Tim O’Reilly described in detail what he meant by Web 2.0. Since then, there has been a lot of discussion on just what this means, if anything. So, I am going to add my own two bits to the mix. There really are not many technical differences between Web 1.0 and 2.0. The differences come from how they are used, and how usable they are.

Web 1.0 is static. Web 2.0 is dynamic.

As mentioned in the Wikipedia article on Web 2.0, Web 1.0 was about displaying information. Web 2.0 is about conversations, about participation in the flow of information.

Web 2.0 uses many new approaches for dealing with information including wikis, weblogs, syndication, aggregators, RSS, podcasts, forums and mashups. These often require the active participation of users. They have been used to create hugely popular social media sites, such as Facebook and YouTube, where the very content seen by all is created totally by the users. User-generated content.
Continue reading A New Page – What is Science 2.0?

Open science 0.9 beta

sunrise by Wolfgang Staudt
The science exchange:
[Via Science in the open]

How do we actually create the service that will deliver on the promise of the internet to enable collaborations to form as and where needed, to increase the speed at which we do science by enabling us to make the right contacts at the right times, and critically; how do we create the critical mass needed to actually make it happen? In another example of blog based morphic resonance there has been a discussion a discussion over at Nature Networks on how to enable collaboration occurred almost at the same time as Pawel Szczeny was blogging on freelance science. I then hooked up with Pawel to solve a problem in my research; as far as we know the first example of a scientific collaboration that started on Friendfeed. And Shirley Wu has now wrapped all of this up in a blog post about how a service to enable collaborations to be identified might actually work which has provoked a further discussion.
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Open Science is really in the very early stages. It may very well evolve into an important adjunct for research. Collaborations are the prime driver of much of today’s science.

Collaboration is difficult in some organizations. Without it, they will not be able to effectively solve the difficult questions in science today. The organizations that can harness effective collaborations will survive and flourish.

Currently, collaborations are usually set up using well known social networking skills honed through years of experience. Who you know is important. What Open Science holds the potential for, when it comes to collaborations, deals with who you don’t know.

OS can leverage an online community so that connections can be made that would have been difficult or impossible if face time was required. However, it will take a little work, like porcupines mating, to make this really effective.

Part of the reason for this is trust. Science has some free loaders, people who take short cuts. Not many but they can degrade interactions until trust is established. which takes a little time. Reputation is an important part of this trust.

There are many examples of peer reviewers abusing the process and scooping someone on a paper that they held up in review, giving the reviewer time to replicate the work in his lab and submit a paper.

Grant proposals have been abused in a similar fashion. Researchers have altered data in order to fit a preconceived hypothesis. Collaborating with such people is a possible danger without more information.

So trust and reputation will have to be a part of OS, particularly since the participants may not meet face to face. But reputation and trust are a common problem with many Web 2.0 approaches.

One way Web 2.0 surmounts this is the very openness and transparency that gives it power. Ebay, for example, would not work if people did not trust the seller to have the item and the buyer to have the cash. Being able to see how each rates the other help establish trust.

Research has shown that what is important in human social networks is not that the network prevents cheats or freeloaders from existing. It is that the network has a method for identifying them and expelling them from the network if they fail to change.

Now OS will not be like Ebay, which is a site of commerce. But the power of many eyeballs watching the interactions will help apply social norms to the most egregious behavior. A reputation lost in the open like this will be very difficult to untarnish.

Another important aspect of scientific collaborations is power, a very human trait. Scientists with power (i.e. large, well funded labs) sometimes have a very different view of a collaboration than those with a small lab and a single grant. People often tend to confuse large and well-funded with innovative.

Remember well funded does not always mean cutting edge investigations of important questions. Sometimes it means doing what everyone knows will work, just more of it with greater efficiency. Risk is many times found in the smaller labs, not the larger, something also seen in corporations. The unwillingness to take a risk, found in many large organizations, often make collaboration with smaller, risk-taking groups problematic.

But on the Internet, this sort of power is defused somewhat. There is a leveling effect, allowing many more researchers to have an equal voice. On the Internet, no one knows you are a dog. They also may not know whether you have a lab of 40 researchers and $10 million in grants. What will be important are your ideas and how you treat others in the network.

So, watch as this discussion happens out in the open, as it should. Become part of it if you can.

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Old versus New

sheet music by cesstrelle74
Web 2.0: In defense of editors:
[Via Bench Marks]

Ran into a few very interesting (and very different) articles last week, which I wanted to comment on (more posts to follow).
First up is a blog posting on Sciencebase that quotes chemist (and blogger) Joerg Kurt Wegner, with a proposal that the solution for information overload is to do away with editorial oversight and instead rely on social software. Now, obviously, I’m heavily biased here, and I admit that up front. I’m an editor, it’s what I do for a living, and if I didn’t think I made valuable contributions, I would do something else. That said, there are several problems with Wegner’s proposal.
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Web 2.0 encourages people to publish quickly, then work to make it better. This may not be the best route for many scientific endeavors, particularly biological ones.

Editors and peer reviewers perform a vital task – they make sure that the science is done right. It requires special training and a firm understanding of the topic to do this well. Even then there are some important mistakes, as recently happened in Proteomics, where a misleading and plagiarized article was published in February.

The editors/reviewers made a mistake in allowing publication. But the errors and plagiarism were discovered by well-educated people (mostly other scientists and interested individuals) on the web. And this information spread rapidly, forcing the journal to publish a retraction and pull the paper.

Science will need editors and peer reviewers from some time, since good science does require careful scrutiny by experts. But, of necessity, this will be a small group of people, who may not see the forest for the trees.

Perhaps some middle ground will be found between the old approaches and the Wikipedia’s of the world. I am sure that the editors of Proteomics, whose reputation was hurt by this, would have liked to have some way for a larger group to review before publication.

Preprints have been the standard way of sending a draft around to colleagues in order to get comments. Web 2.0 approaches using Open Science may hold similar appeal. Many hard science papers (physics, math, etc.) are online at very early points in the process.

The journal Nature is doing something similar with Precedings. These will be important adjuncts to the old way.

They will enhance but never replace. At least for scientists.

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Discussing Science 2.0

toolsby geishaboy500
Web 2.0 for Biologists-Are any of the current tools worth using?:
[Via Bench Marks]

David Crotty has been leading a discussion regarding the acceptance of Science 2.0 by scientists. Or rather the non-acceptance.

It is ironic to use Web 2.0 approaches to examine why scientists do not use Web 2.0 approaches. But entirely appropriate. Because these technologies will help researchers.

But not because we tell them so. No Internet technology ever became used simply because people were told so. They used it because it made it easier to do what they wanted to do.

What scientists can be told is how Web 2.0 will make their life easier. Once they can see how these approaches deal with the glut of data being generated and will help create knowledge, they will be ready for some of the more emergent aspects of Science 2.0.

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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