by Marcin Wichary
An experiment in open access publishing:
[Via Bench Marks]

The new edition of Essentials of Glycobiology, ” the largest, most authoritative volume available on the structure, synthesis, and biology of glycans (sugar chains), molecules that coat cell surfaces and proteins and play important roles in many normal and disease processes” came out yesterday. What’s particularly interesting about this edition is that it is simultaneously being released online in a freely accessible version, which will hopefully allow the textbook to reach a wider audience.

The theory often espoused is that online release of books leads to higher sales of the print edition, and for us, this is a good test case. Quoting from the press release, John Inglis, Executive Director and Publisher of CSHL Press notes that,

“We will be tracking its usage and how readers of the site respond to the availability of a print version, for both research and teaching purposes.”

“This is an innovative development in the distribution of an established textbook that we hope will benefit readers, authors and editors, and the publisher,” says Ajit Varki, M.D., the book’s executive editor and a leader of the Consortium of Glycobiology Editors, which initiated the project. Varki is Professor at the University of California, San Diego. The Consortium also includes Professors Richard Cummings, Emory University; Jeffrey Esko, UC San Diego; Hudson Freeze, Burnham Institute for Medical Research; Pamela Stanley, Albert Einstein College of Medicine, New York; Carolyn Bertozzi, UC Berkeley; Gerald Hart, Johns Hopkins University School of Medicine; and Marilynn Etzler, UC Davis.

The online edition of Essentials of Glycobiology can be found here, and the print version can be ordered here.

This is a very interesting experiment. I knw that there are books I want to have to be able to access important data when I am not online, usually when I am writing. Being online can be distracting then.

But sometimes when I am online, I want a quick fact. Then finding them in an authoritative source is really important. I personally think that this sort of dual use could be very productive. It has been successful for some fiction works.

I too will be looking to see how well this works.

Technorati Tags: Open Access, Science, Web 2.0

by Snap®
Current Biomedical Publication System: A Distorted View of the Reality of Scientific Data?:
[Via Scholarship 2.0: An Idea Whose Time Has Come]

Why Current Publication Practices May Distort Science

Young NS, Ioannidis JPA, Al-Ubaydli O

PLoS Medicine Vol. 5, No. 10, e201 / October 7 2008

[doi:10.1371/journal.pmed.0050201]

Summary

The current system of publication in biomedical research provides a distorted view of the reality of scientific data that are generated in the laboratory and clinic. This system can be studied by applying principles from the field of economics. The “winner’s curse,” a more general statement of publication bias, suggests that the small proportion of results chosen for publication are unrepresentative of scientists’ repeated samplings of the real world.

The self-correcting mechanism in science is retarded by the extreme imbalance between the abundance of supply (the output of basic science laboratories and clinical investigations) and the increasingly limited venues for publication (journals with sufficiently high impact). This system would be expected intrinsically to lead to the misallocation of resources. The scarcity of available outlets is artificial, based on the costs of printing in an electronic age and a belief that selectivity is equivalent to quality.

Science is subject to great uncertainty: we cannot be confident now which efforts will ultimately yield worthwhile achievements. However, the current system abdicates to a small number of intermediates an authoritative prescience to anticipate a highly unpredictable future. In considering society’s expectations and our own goals as scientists, we believe that there is a moral imperative to reconsider how scientific data are judged and disseminated.

Full Text Available At:

[http://medicine.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pmed.0050201]
[More]

There are also several other article links at Scholarship 2.0 that are important to read. In particular, there is a discussion of the Winner’s Curse This is an observation that the winner of an auction in which all the bidders have similar information will usually overbid. The idea of the Winner’s Curse was first observed by oil companies bidding on offshore leases.

I expect this work to produce some interesting discussions. I would be surprised if it is entirely true but it does propose some changes that might be worth implementing.

Technorati Tags: Open Access, Science

by NathanFromDeVryEET
Your personal health: Free means education:
[Via business|bytes|genes|molecules]

One more post today. Russ Altman talks about how the cost of genotyping is asymptoting to free
(eerie parallels to Chris Anderson’s Free). The post comes on the heels of the launch of Complete Genomics and that they will enable a $5000 genome in 2010.
But that’s not the part that I want to talk about. It’s another part of the post

We must work to educate every day people about how to interpret their genome and how to use the information beneficially. Trying to protect them in a paternalistic manner is going to fail, I fear–because it will be too easy to get the information cheaply. So solutions that rely on government regulations or mandatory insertion of a physician in the process of ordering genetic sequencing (don’t get me wrong, I love physicians–I am one) are not going to work.

Given past writings on this subject, no surprise, I agree wholeheartedly. We need to educate, and educate fast.

There are many things that will be changed when sequencing a genome becomes almost as fast in reality as it is on CSI. Without proper education about this, people will be open to really bad science.

The best approach may not be the government or physicians, who have no stake in really explaining things. Perhaps there will be trusted genome advocates whose job is to carefully explain to someone what their genome really means, in a way that truly educates them. And provide quarterly updates of new information for them.

Technorati Tags: Science, Web 2.0

by kentbye
Social Media vs. Knowledge Management: A Generational War:
[Via Enterprise 2.0 Blog]

You’d think Knowledge Management (KM), that venerable IT-based social engineering discipline which came up with evocative phrases like “community of practice,” “expertise locater,” and “knowledge capture,” would be in the vanguard of the 2.0 revolution. You’d be wrong. Inside organizations and at industry fora today, every other conversation around social media (SM) and Enterprise 2.0 seems to turn into a thinly-veiled skirmish within an industry-wide KM-SM shadow war. I suppose I must be a little dense, because it took not one, not two, but three separate incidents before I realized there was a war on. Here’s what’s going on: KM and SM look very similar on the surface, but are actually radically different at multiple levels, both cultural and technical, and are locked in an undeclared cultural war for the soul of Enterprise 2.0. And the most hilarious part is that most of the combatants don’t even realize they are in a war. They think they are loosely-aligned and working towards the same ends, with some minor differences of emphasis. So let me tell you about this war and how it is shaping up. Hint: I have credible neutral “war correspondent” status because I was born in 1974.

[More]

A very clear post that describes the conflict between Boomer and Millennial thinking when it comes to dealing with large amounts of data. Knowledge management (Boomer) is a top-down put the data in the proper bin sort of approach. There are names for each bin and everything needs to fit in the correct one.

One way of thinking has to know whether Schrodinger’s cat is dead or alive, while the other is comfortable with knowing it is simultaneously dead and alive.

Biology needs the Millenial approach because it is creating data at too fast a pace to put it all into bins. Social networks can help tremendously with the filters needed to find knowledge in the huge amount of data.

Technorati Tags: Science, Web 2.0

by blmurch
Magical Thinking:
[Via FasterCures]
Margaret Anderson, COO, FasterCures

I appreciated the message of Carol Diamond and Clay Shirky’s recent piece in the August 2008 Health Affairs titled “Health Information Technology: A Few Years of Magical Thinking?” In it they say that “proponents of health IT must resist “magical thinking,” such as the notion that isolated work on technology will transform our broken system.” It’s interesting to think about systems change at the front end, and how easy it is to get stars in our eyes about how things like health IT or personalized medicine will transform the world as we know it, and how all of our problems will then magically go away.

The article discusses how it might be easier to implement IT in health if the whole system is redone, rather than bolting on IT. IT will not fix the problems without key changes in how medicine is practiced.

A press release discusses some of their points.

Diamond and Shirky propose an alternative route to using health IT to help transform the U.S. health system. “This alternative approach would focus on a minimal set of standards at first,” they say, and would make utility for the user and improved health outcomes, rather than vendor agreement, the key criteria.

Diamond and Shirky’s alternative approach “would mean working simultaneously on removing other obstacles while concentrating on those standards necessary for sharing the information, however formatted in the short term, to flow between willing and authorized participants. Finally, it would require clear policy statements that will guide the design of technology.”

Sounds like a bottom up approach with the end user driving the technology, rather than health vendors. More from Margaret Anderson:

Cell phones, email, and the Internet have certainly transformed things in ways we couldn’t have imagined, but they’ve introduced problems we couldn’t have imagined. Technologies such as FAX machines have been leapfrogged over. Problems such as the overabundance of information, and the speed of information flow are here to stay it seems. In the case of health IT, FasterCures sees it as a vital bridge to the future of more rapid information collection, characterization, and analysis which could speed our time to cures.

But there needs to be careful attention to the fact that too much information, particularly in the health field, can make it much harder to make accurate decision. eventually we will get the complexity of the system under control but in the meantime, there will be some problems. Faster Cures is examining them.

We are working on a white paper for the U.S. Department of Health and Human Services about educating and building awareness among consumers about personalized healthcare. This is another area where we must resist “magical thinking” and get down to brass tacks. Too often, the discussion about personalized medicine has been at a 30,000 foot level. For this paper, we’ve talked to many patient advocacy and disease research groups and everyone holds their breath about the potential power that these technologies may hold for their disease areas. They all want more targeted therapies with fewer side effects, which is ultimately the promise of personalized medicine. But they also recognize its complexities. It needs to take into account the world of co-morbidities we all live in; even if baby boomers are out running marathons and eating their greens and blueberries, the reality is that many of us are living with many conditions and diseases, not just one. It will probably raise costs before it can lower them. It’s unlikely many diseases will yield to the relatively easy HER2-Herceptin gene-to-drug relationship. Patients are likely to get much more information about their genetic makeup than they can act on in the near-term.

Health care is still too complex in most cases. The real magical thinking comes in the form of so many fraudulent ‘cures’ that have plagued mankind for thousands of years. Perhaps as we really get IT involved in health, we can begin to gain a fuller understanding of what causes disease and how to attempt a cure.

Technorati Tags: Health, Science, Web 2.0

by txd
Attention, science and money:
[Via business|bytes|genes|molecules]

Interesting observation by Kevin Kelly. He says

Where ever attention flows, money will follow

To some extent, that’s somewhat obvious. Peter Drucker, whom I admire a lot, said the following

Marketing and innovation produce results; all the rest are costs

Part of the problem with many corporations that commercialize science and technology is that they only focus on the marketing and not the innovation. I remember being told by a higher up that marketing made money - For every dollar we spend on Marketing, we get $3 back. But he told me that research cost money, money that was never directly recouped.

There are good metrics for marketing, not so much for innovation. Yet without the latter the former has nothing to do.

Attention can be driven by many mechanisms, marketing being the most effective one. The key is gaining sufficient mindshare, which is often accompanies by a flow of capital. In science, the money follows topics of research that have mindshare. Similarly people fund companies in areas that generate mindshare for whatever reason.

The question I often ask myself, both from my time as a marketer and as someone interested in science communication, is how can we bring more mindshare to some of our efforts and science in general. What does money flow mean? Is it just research funding? Is it investment in such concepts as “bursty work”? Take something else Kelly writes

New things that don’t work or serve no purpose are quickly weeded out of the system. But the fact that something does work or is helpful is no longer sufficient for success.

Part of the problem is that many researchers feel the data should speak for itself. They fail to realize that gaining mindshare or convincing people requires social interactions. It is a very rare thing that requires no further work in order to sell itself.

We all realize that nothing in science is this way. That is, when we deal with each other, we realize that further experimentation is required to convince us of a new innovation. Few things just emerge from Zeus’ head. we know the process to market to our peers - publications, conferences and seminars.

But the idea of doing something similar to get innovations out to non-scientists is not on an researcher’s radar screen. We don’t have enough time for that. Perhaps just a recognition that there is a process people go through to adopt an innovation and the attempt to facilitate some of those steps would go a long way.

I have written about the lack of marketing in science (stealing shamelessly from Larry Page). It’s critical that we do a better job of highlighting the power of our activities and learn some marketing tricks along the way. No I am not talking about the in your face stuff that gives marketing a bad name, but about the kinds of activities that maintain that attention, and get people to notice. The good news, many of us already do that, perhaps without even realizing it. It’s still niche awareness, but I have a feeling that we are close to actually crossing the hump and bringing some of our activities into the mainstream.

KK link via Michael Nielsen

Marketing is really just convincing people to make a change in their life, to adopt an innovation. It may have a bad odor in science (because ads make people want things that they do not really need) but marketing is really what everyone does who truly wants to compete for mindshare.

We just need to do it in a way that supports research while helping others through the process of adopting innovations.

Technorati Tags: Science, Web 2.0

I use a RSS reader and read feeds because it is part of my writing process. Lately, my RSS reading habits have changed. I haven’t given up on it completely, but my process has changed. My feeds are organized into folders and the folders ordered by priority. Like a farmer tending his crops, I’d scan through each folder, each feed, bookmarking and annotating what caught my eye, and looking for patterns and connections. This scan, capture, analyze patterns, and write a blog post is a part of my routine.

It still is, but I now use other methods for scanning. It’s more like hanging out in a village square or a pub — conversations, news, and resources come to me. I’m finding new links and posts either through twitter, comments on my blog post, or through people who have linked to me.

So, it’s like I have a left brain, orderly, linear way to scan and a right brain, wildly creative way to scan.

I like how Chris Brogan describes his reading goals.

1. Reading what friends write.
2. Reading about the “new marketing” industry and the tech industry (fishbowl).
3. Reading what people recommend.
4. Reading off the wall stuff that inspires new thoughts (outside the bowl).

Michele Martin wrote a post summarizing a paper titled How Knowledge Workers Use the Web and pulls out some the classifications referenced in the paper. My RSS reading is mostly information gathering or browsing.

Finding–Looking for something specific, such as an answer to a specific question.
Information gathering–Less specific than finding, this is research that’s focused on a particular goal that’s broader-based than simply getting a specific piece of information.
Browsing–Visiting personal or professional sites with no specific goal in mind other than to “stay up-to-date” or be entertained.
Transacting–Using the web to execute a transaction, such as banking or shopping.
Communicating–Participating in chat rooms or forums (remember–this was done in 2002, prior to Facebook and the explosive growth of blogs, etc.)
Housekeeping–Using the web to check or maintain the accuracy and functionality of web-based resources, such as looking for dead links, cleaning up outdated information, etc.

Technorati Tags: Science, Web 2.0

by tanakawho
Digital intimacy:
[Via Bench Marks]

Recently, the NY Times had an article discussing the concept of “ambient awareness”, or as the article puts it, “incessant online contact”. Now, first off, I have to admit that I’m one of the over-30-year-olds the article mentions, who finds the concept of subjecting others to (and being subjected to) a stream of trivial details about one’s day completely unappealing. The proponents of Twitter and FriendFeed and the like feel that they’re getting a more intimate understanding of people, “something raw about my friends,” as one user puts it. I’m more in line with the critics quoted in the article that the end result is more “parasocial” than social, and that it ends up an extension of reading gossip magazines and following celebrities from afar.
So how do these new practices apply to the world of science research?
[More]

David always brings up really good points to discuss. I don’t expect every scientist will want or need to be a direct part of the ‘conversation’ happening on Twiiter or FriendFeed. Few have the time. But it will be important that the social network (ie. lab, department, etc.) they belong to includes people who are connected.

I had looked a little bit at FriendFeed but just did not have the time to really dig. Then I noticed that there were a lot of hits at my website that were being referred from the Science 2.0 room.

Like any social setting, I introduced myself, answered some questions and provided insight. Now I am connected to a group that provides very useful information for me.
I don’t have to check it constantly to be able to see useful items that I would not have if I were not part of this particular conversation.

But they do work by spreading information farther and faster.

Technorati Tags: Social media, Web 2.0

I’ve mentioned some of the work by Everett Rogers on technology adoption. The bell curve seen refers to the adoption of innovations by a community. But what about individuals? Is there a process whereby they adopt new technology?

Turns out there is. You can read the work by George Beal and Joe Bohlen in 1957. There is a five step path that each individual appears to go through, although some people are slower to transition between steps.

1. Awareness. The individual is simply aware the innovation exists.
2. Interest. The individual wants more information. They begin to wonder if the innovation can help them.
3. Evaluation. The individual mentally examines the innovation using the information gathered, trying to determine whether it will really impact their work.
4. Trial. The individual actually tests the innovation to see if reality matches expectations.
5. Adoption. The individual likes the innovation and adopts it wholeheartedly.

Beal and Bohlen also described what sources of information were used at each stage. Through the first two, mass media and government agencies were most important.

This was really an attempt to get an ‘unbiased’ viewpoint since friends and salesmen (saesmen always came in last) were the next two sources. But for the last 3 stages, neighbors and friends were the largest source of information, moreso than any other group.

So, early in the diffusion process, unbiased experts are sought. But when the evaluation process is started, the experiences of close ties within a local social network become the most important. For most people, the opinions and personal experiences of their friends are most important for adoption of a new innovation than any external source.

Now the innovators in a community race through these steps. They often are connected to outside groups and use social interactions unavailable to others in the community to more rapidly move through the last 3 steps.

The early adopters take information from the innovators and use their own connections to move through the stages, not as fast as the innovators, but with reasonable speed.

But it is the majority of the community that relies on the early adopters and innovators within the community to inform themselves. Research has shown that they require much more information from trusted sources within the community than innovators and early adopters. Without this information from peers, they will not progress rapidly through the last 3 stages.

The laggards are the slowest to move through the 5 stages. They do not trust most outside sources, so the awareness and interest stages are slowed. Plus they will only listen to certain trusted sources within the community. Until those trusted sources make their own way through the 5 stages, the laggards will not progress.

So, to alter the rate of diffusion of innovation in a community, increased lines of communication must be available, increasing the information that can be provided to individuals.This helps with the first 2 steps. but mostly only for the 16% of the community at the left side of the curve.

However, of greatest importance are the connections between members within the community, particularly the thought-leaders found in the early adopters. About 70% of a community will not adopt new innovations unless they hear clear reasons why, from trusted individuals within the community.

No amount of salesmanship or external proof will easily move them. But, tgiven he right opinion from a community thought-leader and they will rapidly make the transition.

This is an area that Web 2.0 technologies can be of real value. Not only do they make it easier for members of a community to disburse information, they also help the community more accurately identify who is in each group, permitting more focused, explicit approaches to be used to move individuals through the 5 steps.

The thought-leaders can more rapidly progress through the stages and can extend their opinions much more rapidly to the majority because they are not required to be in the same place at the same time as the others in the group. Thus there will be more opportunities for their viewpoints to be assimilated by the majority.

Increasing the rate of diffusion of innovation in a community really means increasing the speed with which each individual progresses through the 5 step.

Technorati Tags: Knowledge Creation, Open Access, Science, Web 2.0

by Untitled blue
Friends and feedy thoughts:
[Via business|bytes|genes|molecules]

I hope Bret and co are paying attention. I’ve heard people say that Friendfeed is too noisy, that they don’t get the value, etc. The tech world has the unique ability to make anything too noisy and the worlds ultimate echo chamber. The scientific community on the other hand (life scientists, physicists, librarians and technologists) have made it a second home. We use it to discuss ideas and ask questions. Of course, every conference seems to get it’s own backchannel on Friendfeed, e.g. ISMB, BioBarCamp, Science in the 21st Century, Science Blogging 2008, etc. We even have rooms for programming and development efforts now, e.g.for Ruby for Python and for the Chemistry Development Kit.

It’s a classic example of successful micro-communities, all coming together, driven by common interests. Makes you want to think ahead. Friendfeed has an API, a decent search engine, but what I would love to see is some way of mining all that data, cause in all the science rooms there is a ton of interesting information. I suspect you can do it today, just not sure what the best approach might be, and the graph of likes and comments and connections just HAS to be fascinating.

To me, at least, Friendfeed conversations actually have a different ‘feel’ to them than the different ‘Web 2.0′ tools that make them up. Things like blog entries, direct links, messages, etc. each have their own flavor. But put them all together, with added comments, more links, more blogs and you end up with something that is much richer than simply the sum of each part.

It is interesting that many scientists have gravitated to Friendfeed. I suspect that the ability to rapidly aggregate a wide variety of different types of conversations and the information they disburse would be one reason. Mining this would be a very interesting proposition.

Technorati Tags: Science, Web 2.0