Female Lion
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More than 25 years ago, a high school teacher of mine said presciently that what would matter in the future would be less “what you know” but more the ability to know where good information exists. There was just going to be too much information.

This was viewed as nearly sacrilegious in the setting of a school. After all, wasn’t the goal to pack our minds with knowledge?

People have worried about knowledge being stored outside human heads ever since Plato decried the printed word as a mere shadow of the thing it represented. However, storing knowledge in more durable and reliable containers has proven efficient and effective. After all, it’s how we know what Plato was droning on about.

Now comes Frank Schirrmacher, a German journalist, worrying about “The Age of the Informavore,” the natural occurrence when there is a population explosion of ideas and not enough brains to cover them. For him, putting more information into more virtual vessels is changing . . .

. . . the way humans think in real life. . . . And you encounter this not only in a theoretical way, but when you meet people, when suddenly people start forgetting things, when suddenly people depend on their gadgets, and other stuff, to remember certain things. This is the beginning, its just an experience. But if you think about it and you think about your own behavior, you suddenly realize that something fundamental is going on.

Schirrmacher’s observations are many. He worries that algorithms like Apple’s “Genius” in iTunes will impinge on the freewill of  our children. He notes how we are now using computing metaphors to describe thinking and actions. He talks about how attitudes about technology are reflected in politics. He also reflects on the the rather trite (by now) thought that while information isn’t scarce, attention can be exhausted. And since attention feeds information, competition for attention means Darwinian selection is going on at a high rate in the information space.

It’s a wide-ranging, if uneven, interview, sometimes really engaging and sometimes a bit opaque. Also, it’s based somewhat on strange information he himself possesses but that doesn’t stand up to external verification, such as his assertion that in the 1990s “nobody predicted the Web” or predicted Google. (People actually predicted both, in essence, decades earlier.)

Nicholas Carr picks up on Schirrmacher’s thinking, along with others, and worries that separating ourselves from the larger information cloud — “the database of intentions” as one person calls it — will continue to be difficult, and may eliminate some familiar experiences, like hunting down an elusive song or album. This is probably true, since we are integrating an increasingly available and multi-dimensional digital archive into every screen we can. Soon, we will have total information immersion.

Fundamentally, I like the term “informavore” because we’ve always been informavores. It’s just that now we have sufficient abundance to give it a name. When food was scarce, we didn’t have the luxury of contemplating omnivores versus herbivores vs carnivores. We were just hungry.

Informavores are going to be changing the health care system. I’ve been reading “Superfreakonomics,” and I just finished a chapter involving emergency room physicians who realized in the 1980s that emergency medicine was essentially predicated on information, and that their ER was suffering from “datapenia,” or a shortage of data. They invented a solution that automated information gathering, improving physician efficiency, improving outcomes, and ultimately becoming a major part of the healthcare information infrastructure.

Scholarly publishing provides one of the best information food chains around for informavores, and this is a huge opportunity. We may be on the brink of fulfilling, to a new and exciting level, the timeless desire to know. Want to know the origin of a “baker’s dozen”? Just look it up on your phone, and 30 seconds later, you know.

Humans are filters on the world. Our eyes receive light, but our brains see. Change how you think or what you know, and you see different things. Significance can be redefined. A colleague coughing on you this month means something more than it did a year ago. The color green on the Empire State Building this year means something other than it would have last year.

Context shifts, cultures change, and perspectives emerge. Yet, the hunt continues.

It seems like we now have more choices, more options, and more information — not just the received wisdom of a dominant ideology that filters information down to such an extent that it actually shapes reality, even becomes reality. Isn’t it better to have verifiable, divergent, and multi-faceted information rather than incomplete information from authorities?

We’ve always been informavores. The difference is now that we have supermarkets to prowl rather than a gruel pot in a hovel at the center of town.

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Do open access (OA) membership fees save institutions money?  In the case of Columbia University, the answer is clearly, “No.”

A talk titled, “Cost/Benefit Analysis of BioMed Central Membership at a Large Medical Institution,” was presented last Friday afternoon at the 2009 Charleston Conference by Susan Klimley, the Serials and Electronic Resources Librarian in the Health Sciences Library at Columbia University.

What motivated Klimley to undertake such a study was seeing her BMC membership fees rise each year by 8%, and then by 10% in 2009. Klimley’s materials budget has been flat for the last five consecutive years, and in January she was told that she needed to trim an additional 10%.

This is a familiar story for many research libraries in the United States.

Until this year, her library was paying BMC almost $10,000 as a supporter member, which entitled Columbia authors to receive a 15% discount on author processing charges (APC).  Calculating whether her membership fees made fiscal sense should have been easy, or so she thought.

But figuring out which APCs were attributed to Columbia authors was no simple matter.  Columbia University has many relationships with surrounding institutions like teaching hospitals, and many of these institutions don’t include “Columbia University” in their name.  In addition, authors may list multiple affiliations.  To make matters even more complicated, most biomedical articles are co-authored, sometimes by scores of authors located at multiple institutions.  Figuring out who paid the APC wasn’t obvious.

Klimley worked under three possible cost/benefit models where payment was attributed to the first author, last author, and corresponding author.  In each of these calculations she discovered that Columbia was paying more money to BMC under their membership model than if their authors had paid full price.  Klimley remarked:

No matter how you sliced it, the 15% cost savings did not equal the cost of the membership

The decision to cancel Columbia’s BMC membership seemed pretty clear — until things got more complex.

Joining five other institutions, Columbia will soon sign the Compact for Open-Access Publishing Equity (COPE) and create a pot of money from their library materials budget to pay for article processing charges.  Since the compact stipulates that the author publication fund could only be used for those without existing sources of funding, determining which articles would be eligible for COPE funds on multi-authored, multi-affiliated papers will not be a straightforward matter.

Details aside, Klimley views the creation of author funds as helping to reinforce what she views as a fundamental disconnect between who creates, and who pays for, article publication.

“Setting up a pot of money [to pay article processing fees] is not going to solve that problem,” Klimley stated emphatically.  For her, authors need to be more sensitized to the cost of producing information, and author publishing funds work against that aim.

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In an entertaining short classroom activity with an all-pays auction, David Zetland shows how $1 can actually sell for $3.75.

The lesson shows how political lobbying works:

all-pay auctions reproduce the dynamics of political lobbying in which the politician is auctioning the wording to some law, and lobbyists from both (many?) sides are contributing money, perks and attention to get their version of the law. All of the lobbyists pay, but only the politician wins.

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In this age of declining viewership, television ratings for sporting events are showing surprising resiliency and are on a major upswing. Entrepreneur and gadfly Mark Cuban has an explanation for this. According to Cuban, the internet has trained us to assign two values to all content: participation value and shelf-life.

Participation value is a measure of how much engagement with others the content inspires. Are you going to get a group of friends together to see that new movie? Will you have people over to watch the big game? Are you going to blog or tweet from the audience of the event? Will you go to a discussion forum and talk about how your team is doing?

Shelf-life measures how long the content is available, and perhaps more importantly, how long the participation value is likely to last:

The higher the participation value, the shorter the shelf-life. . . . While some may think that combining the presentation of events/shows/etc and the participation into a single webpage makes sense. It doesn’t. The internet has also trained us that if it can be shown on the internet, its probably not going to have a high participation value. Why? Because the expectation is that if its on the internet, you can get to it any time you want it. Its out there waiting for you to stream or download at your pleasure. There is a long perceived shelf-life. So there is no rush.

While sporting events and scholarly publications are obviously different, there are some clear points here that explain why so many attempts at discussion forums revolving around scholarly papers have failed. Papers should have great participation value — every field of study revolves around the presentation of results, and there’s a near constant level of interpretation and reinterpretation of those results. So why aren’t there online forums overflowing with discussion as each new issue of a journal is released?

Much participation is hampered by cultural issues within research communities, discussed here, particularly a hesitancy to speak openly and critically. But there are other factors involved that limit participation value. First, there’s a huge amount of diverse material continuously published. With few exceptions, each paper published is relevant to only a small subset of the overall academic community. If there were a thousand professional football leagues, each with hundreds of teams, it would be a lot more difficult to drive participation around an individual game than it is to unite the country around the current one national Monday night game.

Beyond that, shelf-life is playing a role here, particularly considering the asynchronous way that papers are accessed (there’s that word “asynchronous” again — there’s probably a reason it’s popping up in so many posts recently). If there’s a Mets game on television tonight, that’s the one Mets game that most Mets fans will be watching and using as the basis of their participation tonight (assuming they’re masochists). But if an interesting paper on signal transduction comes out in this month’s issue of Cell, some cell biologists will read it the day it comes out, others later in the week, later in the month, or even years and years from now.

I have a hard time staying involved in a blog comment thread for more than a few days, so the idea of following an intermittent conversation over months or years is hard to imagine.

There are certainly revolutionary papers that have instantaneous impact, overturning dogma in an entire field, but these are rare events. For run of the mill papers, there’s an immediacy for only a small number of researchers. Their needs are often better met with directed communication, rather than relying on serendipity. If I read a paper and need details on how an assay is performed, it’s not very efficient for me to leave a comment on the paper asking for help and then sit idly until a Good Samaritan stumbles upon my comment and provides an answer. This could take months or years, and by then my grant funding will have dried up. Instead, I can have my answer in minutes with an e-mail or phone call to the author.

For others, there’s relevance, but not immediacy, which lengthens the schedule for getting around to reading them and lowers the likelihood of having important comments or questions to ask. Research is a long, slow process, an evolutionary one where your directions and needs for background knowledge change over time. I may work on a worm gene for years, and then knock out its function and see a particular effect. That effect may open a whole new avenue of research, and I may discover that there’s a paper from ten years ago where someone saw a similar effect in a fruit fly experiment. I may be excited and ready to discuss that decade-old paper, but it’s unlikely that there’s still an ongoing internet discussion still revolving around it.

So in scholarly publishing, it’s an odd combination of extreme immediacy for very few and lengthy shelf-life for the majority that’s hampering participation value. Combine those factors with the rampant fear of getting scooped or committing career suicide by revealing too much in public, and perhaps it’s unrealistic to expect scholarly papers to engender the sort of frenzied participation we see around current events on Twitter or blog comments.

If you’re interested in building robust discussion forums for academics, you may be better suited focusing on more fleeting things with broad appeal, like meetings.

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Google Chrome
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One of the more interesting themes of the online world has been its role as a disruptive technology for incumbent businesses. As bookstore chains, music providers, video companies, and newspapers have all experienced, their businesses can be disrupted when a competitor changes the rules of the game so severely that the only possible choice is to gut yourself. Bookstore chains suddenly had a competitor with an endless catalog they couldn’t match. Music providers had song-by-song purchasing and digital delivery. And newspapers, which specialized in presenting yesterday’s news for a price, couldn’t compete with the Internet relaying today’s news today at no cost.

In a fascinating post by Bill Gurley on abovethecrowd.com, Google’s aspirations in the mapping, GPS, smartphone, and OS areas are analyzed. Taken together, the moves Google is making add up to disruption for mapping, smartphone, software, and advertising — all nearly simultaneously.

How will Google accomplish this astounding feat?

  1. End reliance on third-party turn-by-turn GPS mapping companies by deploying vehicles to recreate the maps and thereby own them. CHECK.
  2. Create an open-source smartphone operating system that providers prefer, and which eliminates expensive royalties to third-party mapping companies. CHECK.
  3. Create an advertising model based on geo-location to supplement a hugely successful advertising model based on search terms. UNDERWAY.
  4. Create revenue-shares with smartphone providers so that they actually make money off the phones from advertising in addition to subscriber fees for connectivity and data services. UNDERWAY.
  5. Deploy the same revenue-share model for a computer operating system (Google Chrome) for netbooks first, other computers later. LIKELY PLANNED.

So while Chris Anderson has been waxing philosophic about “free” as a “radical price,” Google has been busy creating a disruptive approach based on “less than free.” They are reaching “free” with their turn-by-turn mapping data, then plan to insinuate their technologies into devices using a disruptive model that rewards providers and manufacturers with revenue sharing.

The likely effects of this could be huge. For consumer, it could mean lower prices for technology since onerous GPS charges would be negated and device sales and usage would drive profitability, incentivizing manufacturers to cut prices to ensure adoption.

This is how disruption occurs. To match Google, Apple or Nokia or Palm would have to deploy their own cars across the world to generate turn-by-turn data. And that’s just to match the “free” portion of Google’s plan. To match the “less than free” portion, they’d each have to create a version of AdSense. And by the time they could do any of this, the game would likely be over.

Catching Google will be too expensive and time-consuming. Yet what Google’s competitors will chasing is a value currently described as “less than free.”

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My social Network on Flickr, Facebook, Twitter...
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Recently, David Crotty observed that scientists are not joining social networks. The comments indicated that this might not be a fair generalization, and that adoption in some fields might be quite high. In addition, the use of social media tools remained unaddressed.

In an analysis published in the October 30th issue of Cell, Laura Bonetta quotes a number of scientists who are using Twitter to broadcast awareness of papers they find interesting while learning about papers others find interesting. Most of those quoted have 1,000+ followers. In addition, scientists Bonetta found are Twittering from meetings to help peers follow along.

Interestingly, one of the controversies Bonetta uncovers originated at Cold Spring Harbor Labs (CSHL), where David works. Tweets from a meeting caught the attention of the meeting organizers thanks to tattling by Genomeweb, which was upset because its journalists were being scooped by Twitter:

Because of the complaints, a month later CSHL released a statement that “any participant intending to blog, twitter or otherwise communicate or disseminate results or discussion presented at the meeting to anonymous third parties must obtain permission from the relevant presenting author before communicating any results or discussion to third party groups, message boards, blogs or other online resources (other than your own lab or departments).”

As an aside, Genomeweb is here the “traditional” provider, yet is built on Drupal, which “supports a variety of websites ranging from personal weblogs to large community-driven websites.”

Apparently, there was enough impact from science Twittering to give a non-traditional (now, traditional) provider cause for concern.

Digging into this brought me back to David’s assertion that scientists aren’t joining social networks. Clicking through to his primary source, I found the curious opening sentence:

A quick analysis of online social networks, such as LinkedIn and Xing would suggest that a mere 1 in 7 research scientists use such tools as part of their work.

An adoption rate of 1/7 is a little over 14%. But you have to parse the sentence closely to see that this is probably an underestimation, possibly quite severe. First of all, it was a “quick analysis,” which I think sub-texts into “I barely scratched the surface.” Then there are the networks examined — LinkedIn and Xing, which are networks targeted at businesspeople wishing to keep their contacts up, not necessarily collaborative social networks and certainly not flexible social media tools like Twitter.

Reading further into the same source, there is this even more curious sentence from the author:

Now, personally I know a lot of scientists who are using social media and social networking tools. I have enlisted more than 600 members in a Twitter group after all, and hundreds of my contacts in research are on FriendFeed, LinkedIn, Facebook etc.

Now, I didn’t start writing this post with the intent of quibbling with David. But digging into these links led me to see some things differently, and I have to quibble now.

It seems there’s plenty of evidence that scientists are using social networks (from general ones like Facebook and LinkedIn to more specialized ones like Academia.edu and others), as well as social media tools, from blogs to Twitter to RSS.

It’s often hard to pin down new cultural developments, especially when there are many scattered initiatives, making it hard to aggregate information and spot trends. Yet, it seems scientists are finding value in social tools, and are moving into social networking.

And while you can argue that they won’t want to because they’ll have to divulge secrets, this is like saying they won’t go to parties because they might have to talk shop. Social media requires social skills and social know-how. Scientists know how to chat about what they can and keep secret what they must. This familiar social terrain is hardly a barrier to adoption if there are new advantages to be found in social media.

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united states currency seal - IMG_7366_web
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It’s a theme I’ve heard many times over the past 6-12 months — companies are cutting back on R&D, training, and hiring big-ticket talent. These intangibles were the first to be cut when the budget axes came out, and are likely to be the last to come back as a recovery mounts. And they don’t figure into GDP estimates.

In an interesting analysis, Business Week writer Michael Mandel talks about how the mismeasure of these intangibles could lead to a premature assumption that the recession is over and an even longer lag before these spending areas are replenished.

As Mandel writes,

official statistics are not designed to pick up cutbacks in “intangible investments” such as business spending on research and development, product design, and worker training. There’s ample evidence to suggest that companies, to reduce costs and boost short-term profits, are slashing this kind of spending, which is essential for innovation. Without investment in intangibles, the U.S. can’t compete in a knowledge-based global economy. Yet you won’t see that plunge reflected in the GDP and productivity statistics, which are still too focused on more traditional sectors, such as motor vehicles and construction. In effect, government statisticians are trying to track a 21st century bust with 20th century tools. Not only is that distorting the critical data that investors, policymakers, and corporate executives use to evaluate the economy, but it might also be creating a false sense of relief as Americans battle a brutal recession.

How important are intangible assets? Recent research finds they account for $1.6 trillion in our economy, compared to $1.2 trillion for machinery and buildings. In 1995, the two were roughly equal, yet growth in the economy has largely come from growth in intangibles — valuable knowledge, skills, and design thinking.

A “false sense of relief” arrived at by measuring a smaller portion of our economy, and one not driving growth over the past 15 years, is exactly what may lead to a lag in restoring spending on innovation, as companies and policymakers are misled by mismeasures into thinking that everything’s OK, and spending in these areas at pre-recession levels might have been unnecessary for economic vitality.

Overall employment of scientists and engineers has fallen 6.3% since the recession began, while overall employment has only fallen 4.1%. Of course, science and engineering jobs pay much better than average, so when they go, more economic vitality vanishes.

Yet, when it comes to what is measured, companies continue to slash:

Alcoa (AA), in an effort to preserve cash, reduced its third-quarter R&D spending by 36% from the year before. “It’s a matter of focusing on your priorities,” says Alcoa spokesman Kevin Lowery. “We surprised people by announcing a profit [last] quarter.” Texas Instruments (TXN), meanwhile, expects to spend $1.5 billion on R&D in 2009, down 20% from 2008, owing to workforce reductions and cost-control efforts. And Johnson & Johnson (JNJ) has reduced its R&D by 13% over the past year.

It is a matter of priorities, but since the GDP will capture the profitability of the less-intangible assets of Alcoa and others, while missing entirely the loss of intangible contributions, a false picture is created.

The issues stemming from these analytical deficiencies affect science spending, scientists, spending on information resources, and innovation around all aspects of endeavor. Cuts to corporate budgets, educational budgets, and governmental budgets have left people with advanced degrees, important skills and abilities, and innovative ideas struggling to find their footing while companies with more traditional property, plant, and equipment have been bailed out. To be fair, the economic stimulus passed under the Obama administration did include funding for R&D, but corporate cuts have been widespread and deep. Yet they aren’t measured.

It gets worse. To cut costs, it seems some companies are targeting the more highly educated, more experienced scientists in their ranks since they are more highly paid and perhaps even more “intangible.”

Mergers and acquisitions are another source of job loss for researchers and scientists, as companies like Pfizer and Wyeth merge, allowing the combined firm to shed thousands of biologists and bench researchers. Outsourcing to CROs and offshore research firms are other ways companies are racing back to profitability. All of these hurt US-based researchers and scientists.

Training is another intangible that has been cut dramatically during the recession, another investment in the future that’s been set aside as companies struggle to regain profitability as quickly as they can. Luckily, some companies like Autodesk, makers of AutoCAD, are allowing unemployed engineers and architects to download their student version free if they say they’re unemployed. They understand the importance of keeping your intangibles sharp.

So, the next time you hear that perhaps the recession is lifting, that halcyon days are on the horizon, remember that the numbers being used for those rosy projections are based on items that are easy to measure, slower to grow, of decreasing value, and not vital for future growth.

This could be a lesson in how intangibles become tangible, I’m afraid.

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google wave logo
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Google Wave was built to answer the question, “How would email look if it were invented today?”  But Wave goes far beyond email-like functionality and tries to get to the heart of communication in all the forms that we’ve come to know.  Wave is part email, part IM, part Wiki, and part document management, to name a few.

I’ve been experimenting for a couple of weeks now.  After a slow start in almost complete isolation, I connected with a very active user, John Blossom.  John had already amassed quite a following.   Seeing how an active group is using Google Wave proved fascinating.  There were blogs that had been transformed into waves,  personal profiles constructed as waves, public waves instructing others on how to get started, and waves that identified known bugs and workarounds.

However, finding people is quite difficult.  You must either know someone’s exact login ID or happen to see them on a wave.  Since many users do not have pictures and use ID’s that are not readily identifiable as them, this is exceptionally frustrating.  There is no way to search for users and no integration with email or other apps.  Wave isn’t even integrated with Gmail. I actually found several of the people with whom I’m connected through Facebook, Twitter, and blogs where they mentioned they were on Google Wave and offered to connect with others.

Once you have connected with others, if you don’t use Google Wave continually, you have no way of knowing that someone has added you to a wave or tried to interact with you in any way.  Again, there is no integration to IM, email, or any other applications, not even Google applications.

Another frustration is that it is very difficult to get started.  Google Wave is a cacophony of functionality that doesn’t even try to reveal its value or purpose to the user. You have to be determined to use Google Wave in order to make it work for you. Even then, since it’s a “preview,” the functions you try to use don’t always work.  Being a new user you are left wondering if the function doesn’t work or if you’re just not doing it right.

What could make it more useful?

  • Integration with email clients, contacts, and other collaborative spaces (Google applications would be a great start: Google Docs, Spaces, Gmail, IM, etc.)
  • A more intuitive user interface that works in all browsers equally as well
  • The ability to easily find others
  • Configuration options that allow a user to more precisely structure their view
  • Some pre-configured views that optimize screen layout based on what the user is trying to accomplish

All that being said, there is the potential for intense collaboration on Google Wave.  As it is now, it’s just too vast and complicated to be useful. It’s currently a drain on productivity, not a boon to it.

Steve Rubel put it well:

So definitely get excited about Wave. It is way cool. It is real time – where the world is going. But, for now, it does create more problems than it solves. Let’s see if Wave 2.0 fixes that.

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Image representing DeepDyve as depicted in Cru...
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Yesterday, the online article intermediary DeepDyve announced a rental model for scientific papers, prompting one news outlet to call this new business, “Netflix for Researchers.”

DeepDyve is a search engine specializing in indexing and providing direct access to scientific articles.  But it does so in a novel way — by renting, not selling, access.

Their motto is, “Research. Rent. Read.” It forgoes the ownership model of access.  Like DVDs that need to be mailed back to Netflix, DeepDyve is based on a short-term rental period of journal article access.

Users can sign up for three types of membership:

  1. Basic. Pay as you go at $0.99 per article for a 24-hour rental
  2. Silver. A monthly subscription plan at $9.99 , which allows 20 articles at any one time with a 7-day rental, and
  3. Gold. A subscription plan of $19.99 allows unlimited rentals with no rental period

The list of publishers who have teamed up with DeepDyve include:  Oxford University Press, Sage, Taylor & Francis, Wiley-Blackwell, and PLoS, along with many of the society publishers hosted by HighWire and BioOne. DeepDyve is also indexing open access repositories like the arXiv and PubMed Central. Conspicuously missing from list are some of the biggest publishers that charge the highest pay-per-view prices, Elsevier and Springer.

One wonders whether some publishers feel that DeepDyve will cannibalize revenues by introducing a pricing model that focuses on article access, rather than journal or database access.

But DeepDyve sees their service as reaching to a unique potential user groups that have generally been underserved by academic publishers including individual knowledge workers and small businesses.  Indeed, the recent study of small and medium UK enterprises on their uses and desires for the professional and academic literature revealed that the price per article charged by many publishers was deemed excessive, considering that users can’t preview the full-text before purchase and that abstracts were often “uninformative or misleading,” requiring potential readers to “purchase blind.”  The rental model reduces the economic risk to the paying reader.

High prices have been one of the chief arguments promoting article deposit in public access archives.  A $30-50 article price tag for a layperson interested in the medical literature for personal or family health concerns may be excessive for many.  But $0.99?  One has to wonder whether DeepDyve’s existence a few years ago would have taken some of the steam out of the Federal Research Public Access Act of 2009 (S.1373).

The prices set per article take advantage of the psychological concept of anchoring.  With iTunes, we’ve been trained to see $0.99 as a price point, a reasonable price to pay for a unit of information, even though a two-minute pop song and a 10-page academic paper may share very little in common.  Still, others like Geoff Bilder of CrossRef have been promoting the idea of an iPubs service for some time as a way of dismantling the information silos built by publishers and libraries.

Outsiders to publishing and academic libraries may not view the development of services like DeepDyve to be significant and noteworthy, but I think this product may indicate that our views of information-as-property are finally changing.  What the Big Deal did to the library’s relationship with publishers — and supplanting our notion of ownership with licensing — DeepDyve may reorient the reader’s relationship with libraries and publishers.

Google doesn’t want our content.  DeepDyve does.

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National Institutes of Health

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A quick follow-up to last week’s post titled, “Scientists Still Not Joining Social Networks.” The NIH recently announced that they are financing “a network some are calling a Facebook for scientists” to the tune of $12.2 million (link via Richard Sever). I guess we’re seeing real progress made–every network used to advertise itself as “Myspace for scientists” , so at least we’ve moved into the Facebook era.

If there’s any hope for success for such a network, the NIH is probably the best bet as the host and organizer. They’ve already got the massive database covering the literature in PubMed. Unlike most of the companies and publishers trying to capitalize on this space, the NIH can create a truly neutral system, one that isn’t limited to featuring one company’s products or connections to only one publisher’s journals. A taxpayer-funded network would also be free from the pressure of having to find a sustainable business model to ensure survival. Of course, science is a global activity, so it’s unclear whether a US government-run network would play nicely with non-US scientists.

That said, I’m willing to bet that this effort ends up doing about as well as all the other failures of the last several years. As Ted Freeman noted in the comments on the last article, the vast majority of scientists work in the for-profit sector, not in academia, and the open sharing of a social network is generally antithetical to the aims of those companies. Even more damning is the kool-aid drinking attitude displayed by the head of the project being funded here:

If a researcher is looking for someone else in a very specialized field, he or she would usually think of all the people he has met or simply scan recent scientific journals for names, said Michael Conlon, interim director of biomedical informatics at the College of Medicine at the University of Florida and the principal investigator on the grant. Mr. Conlon calls those methods “haphazard.”

A careful review of the literature to find a collaborator who has a history of publishing quality results in a field is “haphazard”, whereas placing a want-ad, or collaborating with one’s online chat buddies, is systematic? Yikes.

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