Category Archives: Science

Loving FriendFeed

friends by freeparking
London Science Blogging Conference on Friendfeed:
[Via Confessions of a Science Librarian]

Boy, do I ever love Friendfeed.

You can follow what’s going on at today’s London Science Blogging Conference in its very own Friendfeed room. Each session has it’s own thread with multiple people commenting on the proceedings. It actually gives a very good and surprisingly understandable impression of what’s going on in the sessions. Most of the sessions have dozens of comments. Check it out.

You can also check me out on Friendfeed (join, you won’t regret it). Michael Nielsen has also created a room for the upcoming Science in the 21st Century conference.

As a sort of aggregator of one’s life, FriendFeed can be especially useful for all sorts of ad hoc social meetings, such as conferences. I wonder what the ‘room’ looks like for a really large conference, the 10,000 attending ones? I’ll be sure and check out the Science in the 21st Century room.

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Royalties

ribosome by Vik Nanda
Royalties for journal article authors:
[Via Bench Marks]

I’m happy to say that this week we sent out our first round of royalty payments to authors of original articles in CSH Protocols. Because we’re doing some reprinting of material from our already-published laboratory manuals, we built in a system to pay royalties to the editors of those manuals. We chose at the time to extend those royalties to authors of new material as well. The idea of writing up methods isn’t something that immediately occurs to most laboratories–they’re usually more interested in publishing data, so we’re hoping that these royalty payments will at least serve as something of a motivation for publishing (and continuing to publish) protocols with us. We’re not talking about huge sums of money, but as I recall from my graduate student days, every little bit helps. It also addresses one of the complaints one hears about us greedy science publishers–that we fail to compensate scientists for the work they’ve put into the publication and keep all the cash for ourselves. While CSHL Press is part of a not-for-profit research institute, and any money we make from our publications goes to fund research at Cold Spring Harbor Laboratory, we’re very curious to see what happens from this experiment in revenue-sharing. Does this make a difference to you as an author?

This set of royalties covers the calendar year 2007. A portion of our subscription revenue is set aside and divided among all authors/editors based on the usage of their individual articles during that calendar year. Those who published articles late in the year may not see much in terms of revenue given the relatively small time scale that their articles were available, but hopefully their articles will see a little more use in 2008.

This is a really interesting experiment. Many researchers will need a little extra incentive to write up a protocol paper, but they can be very useful to have. CSH Protocols has been leading on many ways from their free access articles each month to, now, the use of royalties.

Finding the right niche in an online/offline world is what keeps everyone on their toes. CSH Protocols looks to be making a nice place for itself. I’d imagine there will be some other tweaks to the publishing industry before it is all said and done.

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An interesting start

mandalay by mandj98
Mendeley = Mekentosj Papers + Web 2.0 ?:
[Via bioCS]

Via Ricardo Vidal: Mendeley seems to be a Windows (plus Mac/Linux) equivalent of Mekentosj Papers (which is Mac OS X only, and has been described as “iTunes for your papers”). In addition to handling your PDFs, it has an online component that allows sharing your papers and other Web 2.0 features (billing itself as “Last.fm for papers”).

Here, I’m reviewing the Mac beta version (0.5.6). I am focusing most on the desktop side and compare it to Papers, because I have a working solution in place and I would only switch to Mendeley if the experience is as good as with Papers. (I.e., my main problem is off-line papers management, Web 2.0 features are icing on the cake.)

By Mac standards, the app is quite ugly. Both Mendeley and Papers allow full-text PDF searches, which is important if you want to avoid tagging/categorizing all your papers. Papers can show PDFs in the main window, copy the reference of the paper and email papers. Mendeley in principle can also copy the reference, but special characters are transformed to gibberish in this beta version. Papers allows you to match papers against PubMed, Web of Science etc., while Mendeley only offers to auto-extract often incomplete meta-data. This matching feature is extremely useful as you get all the authorative data from the source, and most often Papers can use the DOI in the PDF to immeadiately give you the correct reference. Update: Mendeley also uses DOIs to retrieve the correct metadata, if available. (Thanks, Victor for your comment.)
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Well, this is a beta being compared to a product on the market (and Papers is quite a good application). I would expect some of the rough edges to come off as it progresses. What will be interesting to see is how the Web 2.0 aspects turn out. They could provide a route for useful filtering of information as people’s paper databases build up. By having these accessible, it will be much easier to see which papers are really being read and used.

The links between literature libraries, online profiles and readership are potentially very interesting. Something to keep an eye on, particularly as the edges are evened out.

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Missing the point?

pendulum by sylvar

It has been about a month since Science published
Electronic Publication and the Narrowing of Science and Scholarship by James Evans. I’ve waited some time to comment because the results were somewhat nonintuitive, leading to some deeper thinking.

The results seem to indicate that greater access to online journals results in fewer citations. The reasons for this are causing some discussion. Part of what I wlll maintain is that papers from 15 years ago were loaded with references for two reasons that are no longer relevant today: to demonstrate how hard the author had worked to find relevant information and to help the reader in their searches for information.

Finding information today is too easy for there to be as great a need to include a multitude of similar references.

Many people feel the opposite, that the ease in finding references, via such sites as PubMed, would result in more papers being cited not less. Bench Marks has this to say:

Evans brings up a few possibilities to explain his data. First, that the better search capabilities online have led to a streamlining of the research process, that authors of papers are better able to eliminate unrelated material, that searching online rather than browsing print “facilitates avoidance of older and less relevant literature.” The online environment better enables consensus, “If online researchers can more easily find prevailing opinion, they are more likely to follow it, leading to more citations referencing fewer articles.” The danger here, as Evans points out, is that if consensus is so easily reached and so heavily reinforced, “Findings and ideas that do not become consensus quickly will be forgotten quickly.” And that’s worrisome–we need the outliers, the iconoclasts, those willing to challenge dogma. There’s also a great wealth in the past literature that may end up being ignored, forcing researchers to repeat experiments already done, to reinvent the wheel out of ignorance of papers more than a few years old. I know from experience on the book publishing side of things that getting people to read the classic literature of a field is difficult at best. The keenest scientific minds that I know are all well-versed in the histories of their fields, going back well into the 19th century in some fields. But for most of us, it’s hard to find the time to dig that deeply, and reading a review of a review of a review is easier and more efficient in the moment. But it’s less efficient in the big picture, as not knowing what’s already been proposed and examined can mean years of redundant work.

But this is true of journals stored in library stacks, before online editions. It was such a pain to use Index Medicus or a review article (reading a review article has always been the fastest way to get up to speed. It has nothing to do with being online or not) and find the articles that were really needed. So people would include every damn one they found that was relevant. The time spent finding the reference had to have some payoff.

Also, one would just reuse citations for procedures, adding on to those already used in previous papers. The time spent tracking down those references would be paid out by continuing usage, particularly in the Introduction and Materials & Methods sections. Many times, researchers would have 4 or 5 different articles all saying the similar things or using the same technique just to provide evidence of how hard they had worked to find them (“I had to find these damned articles on PCR generated mutagenesis and I am going to make sure I get maximum usage out of them.”)

There are other possible answers for the data that do not mean that Science and Scholarship are narrowing, at least not in a negative sense. A comment at LISNews leads to one possible reason – an artifact of how the publishing world has changed.
The comment takes us to a commentary of the Evans’ article.While this is behind the subscription wall, there is this relevant paragraph:

One possible explanation for the disparate results in older citations is that Evans’s findings reflect shorter publishing times. “Say I wrote a paper in 2007” that didn’t come out for a year, says Luis Amaral, a physicist working on complex systems at Northwestern University in Evanston, Illinois, whose findings clash with Evans’s. “This paper with a date of 2008 is citing papers from 2005, 2006.” But if the journal publishes the paper the same year it was submitted, 2007, its citations will appear more recent.

[As an aside, when did it become Evans’s rather than Evans’? I’d have gotten points of from my English teacher for that. Yet a premier journal like Science now shows that I can use it that way.]

The commentary also mentions work that appears to lead to different conclusions:

Oddly, “our studies show the opposite,” says Carol Tenopir, an information scientist at the University of Tennessee, Knoxville. She and her statistician colleague Donald King of the University of North Carolina, Chapel Hill, have surveyed thousands of scientists over the years for their scholarly reading habits. They found that scientists are reading older articles and reading more broadly–at least one article a year from 23 different journals, compared with 13 journals in the late 1970s. In legal research, too, “people are going further back,” says Dana Neac u, head of public services at Columbia University’s Law School Library in New York City, who has studied the question.

So scientists are reading more widely and more deeply. They just do not add that reading to their reference lists. Why? Part of it might be human nature. Since it is so much easier to find relevant papers, having a long list no longer demonstrates how hard one worked to find them. Citing 8 articles at a time no longer means much at all.

That is, stating “PCR has been used to create mutations in a gene sequence 23-32” no longer demonstrates the hard work put into gathering those references. It is so easy to find a reference that adding more than a few looks like overkill. That does not mean that the scientists are not reading all those other ones. They still appear to be, and are even reading more, they just may be including only the relevant ones in their citations.

Two others put the data into a different perspective. Bill Hooker at Open Reading Frame did more than most of us. He actually went exploring in the paper itself and added his own commentary. Let’s look at his response to examining older articles:

The first is that citing more and older references is somehow better — that bit about “anchor[ing] findings deeply intro past and present scholarship”. I don’t buy it. Anyone who wants to read deeply into the past of a field can follow the citation trail back from more recent references, and there’s no point cluttering up every paper with every single reference back to Aristotle. As you go further back there are more errors, mistaken models, lack of information, technical difficulties overcome in later work, and so on — and that’s how it’s supposed to work. I’m not saying that it’s not worth reading way back in the archives, or that you don’t sometimes find overlooked ideas or observations there, but I am saying that it’s not something you want to spend most of your time doing.

It is much harder work to determine how relevant a random 10 year old paper is than one published last month. In the vast majority of cases, particularly in a rapidly advancing field (say neuroscience) papers that old will be chock full of errors based on inadequate knowledge. This would diminish their usefulness as a reference. In general, new papers will be better to use. I would be curious for someone to examine reference patterns in papers published 15 years ago to see how many of the multitude of citations are actually relevant or even correct?

Finally, one reason to include a lot of references is to help your readers find the needed information without having to do the painful work of digging it out themselves. This is the main reason to include lots of citations.

When I started in research, a good review article was extremely valuable. I could use it to dig out the articles I needed. I loved papers with lots of references, since it made my life easier. This benefit is no longer quite as needed because other approaches are now available to find relevant papers in a much more rapid fashion than just a few years ago.

Bill discusses this, demonstrating that since it is so much easier to find relevant article today, this need to help the reader in THEIR searches is greatly diminshed.

OK, suppose you do show that — it’s only a bad thing if you assume that the authors who are citing fewer and more recent articles are somehow ignorant of the earlier work. They’re not: as I said, later work builds on earlier. Evans makes no attempt to demonstrate that there is a break in the citation trail — that these authors who are citing fewer and more recent articles are in any way missing something relevant. Rather, I’d say they’re simply citing what they need to get their point across, and leaving readers who want to cast a wider net to do that for themselves (which, of course, they can do much more rapidly and thoroughly now that they can do it online).

Finally, he really examines the data to see if they actually show what many other reports have encapsulated. What he finds is that the online access is not really equal. Much of it is still commercial and requires payment. He has this to say when examining the difference between commercial online content and Open Access (my emphasis):

What this suggests to me is that the driving force in Evans’ suggested “narrow[ing of] the range of findings and ideas built upon” is not online access per se but in fact commercial access, with its attendant question of who can afford to read what. Evans’ own data indicate that if the online access in question is free of charge, the apparent narrowing effect is significantly reduced or even reversed. Moreover, the commercially available corpus is and has always been much larger than the freely available body of knowledge (for instance, DOAJ currently lists around 3500 journals, approximately 10-15% of the total number of scholarly journals). This indicates that if all of the online access that went into Evans’ model had been free all along, the anti-narrowing effect of Open Access would be considerably amplified.

[See he uses the possessive of Evans the way I was taught. I wish that they would tell me when grammar rules change so I could keep up.]

It will take a lot more work to see if there really is a significant difference in the patterns between Open Access publications and commercial ones. But this give and take that Bill utilizes is exactly how Science progresses. Some data is presented, with a hypothesis. Others critique the hypothesis and do further experiments to determine which is correct. The conclusions from Evans’ paper are still too tentative, in my opinion, and Bill’s criticisms provide ample fodder for further examinations.

Finally, Deepak Singh at BBGM provides an interesting perspective. He gets into one of the main points that I think is rapidly changing much of how we do research. Finding information is so easy today that one can rapidly gather links. This means that even interested amateurs can find information they need, something that was almost impossible before the Web.

The authors fail to realize that for the majority of us, the non-specialists, the web is a treasure trove of knowledge that most either did not have access to before, or had to do too much work to get. Any knowledge that they have is better than what they would have had in the absence of all this information at our fingertips. Could the tools they have to become more efficient and deal with this information glut be improved? Of course, and so will our habits evolve as we learn to deal with information overload.

He further discusses the effects on himself and other researchers:

So what about those who make information their life. Creating it, parsing it, trying to glean additional information to it. As one of those, and having met and known many others, all I can say is that to say that the internet and all this information has made us shallower in our searching is completely off the mark. It’s easy enough to go from A –> B, but the fun part is going from A –> B –> C –> D or even A –> B –> C –> H, which is the fun part of online discovery. I would argue that in looking for citations we can now find citations of increased relevance, rather than rehashing ones that others do, and that’s only part of the story. We have the ability to discovery links through our online networks. It’s up to the user tho bring some diversity into those networks, and I would wager most of us do that.

So, even if there is something ‘bad’ about scientists having a more shallow set of citations in their publications, this is outweighed by the huge positive seen in easy access for non-scientists. They can now find information that used to be so hard to find that only experts ever read them. The citation list may be shorter but the diversity of the readers could be substantially enlarged.

Finally, Philip Davis at The Scholarly Kitchen may provide the best perspective. He also demonstrates how the Web can obliterate previous routes to disseminate information. After all the to-do about not going far enough back into the past for references, Philip provides not only a link (lets call it a citation) from a 1965 paper by Derek Price but also provides a quote:

I am tempted to conclude that a very large fraction of the alleged 35,000 journals now current must be reckoned as merely a distant background noise, and as far from central or strategic in any of the knitted strips from which the cloth of science is woven.

So even forty years ago it was recognized that most publications were just background noise. But, what Philip does next is very subtle, since he does not mention it. Follow his link to Price’s paper (which is available on the Web, entitled Networks of Scientific Papers). You can see the references Price had in his paper. a total of 11. But you can also see what papers have used Price’s paper as a reference. You can see that quite a few recent papers have used this forty year old paper as a reference. Seems like some people maintain quite a bit of depth in their citations!

And now, thanks to Philip, I will read an interesting paper I would never have read before. So perhaps there will be new avenues to find relevant papers that does not rely on following a reference list back in time. The Web provides new routes that short circuits this but are not seen if people only follow databases of article references.

In conclusion, the apparent shallownesss may only be an artifact of publishing changes, it may reflect a change in the needs of the authors and their readers, it may not correctly factor in differences in online publishing methods, it could be irrelevant and/or it could be flat out wrong. But it is certainly an important work because it will drive further investigations to tease out just what is going on.

It already has, just by following online conversations about it. And to think that these conversations would not have been accessible to many just 5 years ago. The openness displayed here is another of the tremendous advances of online publication.

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Accessible databases

Trendspotting: Molecular profiling data resources:
[Via business|bytes|genes|molecules]

This image was generated in an academic instit...Image via WikipediaLet us say you are a researcher and are doing a gene expression study on some tissue. Today, the chances are that you will run some microarrays and look at the expression profile and then try and correlate the expression profiles of a number of samples with associated data.

Fast forward a few years. I am convinced that a lot of such data will be available via search engines or data portals. Already you are beginning to see a number of commercial and public engines come to life (NextBio, Oncomine, etc). Earlier this week I read an announcement (sub reqd) by the NCI to create a Cancer Molecular Analysis Portal, which will integrate data sets from the Cancer Genome Atlas project and other cancer genomics studies.

The key here is that we already have a body of work using microarrays and other molecular profiling systems, and in many cases, people are just repeating experiments which someone, somewhere has already carried out. Unless there is something inherently proprietary in those studies (e.g specific dose-response studies), there is no reason to repeat that experiment, especially for technologies that are relatively stable and don’t have too much cross-platform/cross-lab variation (one of the goals of the MAQC projects has been to understand these variations). The second key, and to an extent perhaps even more important, is how these data are made available. Personally, I really like the NextBio interface. Will the business model work? I am not sure, but definitely the idea and concept make a lot of sense.

[More]

There is a lot of work being repeated over and over again because access to the data is not easily available. This is one of the big changes that will take place over the next few years, as the same principles that make PubMed or GenBank so useful start permeating all databases.

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Filtering after publication

 32 96723190 5E04F9Ccf2 by aslakr
Public Rambling: Post-publication journals:
[Via Public Rambling]

With the increase in the number of journals and articles being published every year and the possibility of having an even larger set of “gray literature” available online we face the challenge of filtering out those bits of information that are relevant for us.

Let us define as “perceived impact” this subjective measure of importance that some bit of information holds for us as scientists. This information is typically an article but it could be applied later to pre-prints and database entries in general.

So begins a nice essay looking at possible ways to filter articles AfTER publication on the Web, rather than BEFORE publication, which is what happens now with most journals.

No real answer except the idea that leveraging all the eyes on the web could accomplish a lot of this. RSS can be used to rapidly identify articles. Links to the PDFs plus any comments I may have can be quickly placed on my personal blog.

I can then come back later, when I have more time and spend it with the articles I have shown some interest in. If I am a good filter of articles, others can subscribe to my newsfeed, leveraging my abilities without having to do the filtering themselves.

Perhaps something could be done with a similar process. It would not replace other approaches but serve as an adjunct.

It’s a thought.

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Multi-level experience

 122 405446783 A88C63Ce0C by laffy4k
Cameron Neylon and the full web2.0 experience:
[Via OpenWetWare]

Earlier today fellow OWW blogger Cameron Neylon gave a talk at the Institutional Web Managers Workshop in Aberdeen and did so, not only for those present at the venue, but also to anyone with internet access.

Cameron set out to stream the talk via webcast, have updates via FriendFeed and also microblogging via Twitter.

The presentation was viewed by quite a few folks and many participated on FriendFeed. Cameron even stated that he noticed 20 new followers on his twitter account!

Giving talks can be stressful as is, so this requires some congratulating for the effort. Great work Cameron!

It is very likely that presentations in the near future will not only be in-person and streamed on the web, but also include much larger back channels using FriendFeed and Twitter.

There will not only be a way to enlarge the audience, but all these conversations can be examined in order to get a much better idea of how the presentation went and what effect any new data will have on other investigations.

Presentations will not simply be monologs anymore but will have be just a part of the overall conversation. This means scientific information travels farther, faster, with greater vetting by peers than ever before.

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Digital notebooks

lab notebook by Marcin Wichary
Electronic notebooks are cool, and so is RDF:
[Via business|bytes|genes|molecules]

Had a conversation earlier today, all about RDF and linked data. I am a big believer, which is why posts like this one by Cameron Neylon on A new way of looking at science? bring a smile.

Andrew Milsted, a PhD student, enabled an RDF dump of the content in the lab notebook used by Cameron’s group (and others I suspect). The result, a graph that shows each post in the notebook as a node and links between posts as edges. It is a universe of the work going on in the lab, and how that work interacts. It would be interesting to see the dynamics of this graph evolve, and various other ways of visualizing the underlying data and relationships. It would also be cool to put this up on the web as linked data and link it to data outside Cameron’s lab. Might even lead to some very interesting observations and relationships.

This is a simple example, but highlights why it is so important to be able to put data into machine readable formats. RDF is a naturally good model, since it highlights relationships within the underlying data.

In the not too distant future, lab notebooks will be digitized and all the info will be available online, at least for the use of the researchers creating the data. This will be because most of the experimental results will be in digital form, making it much easier to attach them to the electronic notebook but also because the work can be accessed and examined in totally novel ways.

As shown here, the digital material can be examined for links and mined in ways that are just impossible today. Linkages between pages, data and comments could be examined. Possible relationships between projects could be highlighted. Areas for collaboration could be determined.

Context can be added to data in order to create a deeper examination of the information created.

The groups that more rapidly embrace these sorts of approaches will be able to turn the creativity cycle faster, increase the rates of diffusion of innovation in the community and find solutions to complex problems that are unsolvable by simply analog approaches.

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Liking knol somewhat

drops by eye of einstein

So, after
writing about my knol dislikes, let me discuss some of my positive thoughts about knol. Knol is the newest feature from Google.

As I wrote earlier, I do not like some of the non-Web 2.0 features seen in some of the early essays (i.e. lack of any links to other pages, static text, lack of effective conversations). But I do like some of the principles behind this product.

Huge amounts of information are collected inside a person’s head or on their computer. And it is not accessible to anyone else. Getting this tacit information out, making it explicit so that others can use it, is an important goal of many Web 2.0 tools.

By providing singular authorship, knols allow a more ego-driven approach for making the information explicit than Wikipedia does.

That is, Wikipedia also provides a means for moving tacit information into the explicit realm. But, there is no real sense of authorship, nothing to really plant a flag and say I did this, I am providing this to the world.

Knols permit this to happen, which should enlarge the amount of information seen on the web. Because there are a plethora of experts who do not want an anonymous reputation built from Wikipedia but might want a renowned one from a knol.

Finding ways to transform tacit information into explicit are crucial in today’s world. Wikis can do this. Blogs can do this. And so can knols. Knols will not replace other approaches. They provide a new path for the transformation to occur.

Being a scientist, I have a pretty healthy ego (almost a necessity to do research) and I want people to know about the work I do, not simply as an anonymous entry but with my name attached. It is why I want to have my name on a paper that as many people as possible can read. I can then point to it and say This is mine. That is also part of the reason I write a blog. Ego is good.

So, Web 2.0 tools that provide an avenue for ‘named’ publication will find a market.

Plus, a knol entry would probably look a little better to the tenure committee for an academic than an Wikipedia entry or even a blog. The author could use the web stats to demonstrate the impact of the article in ways that current journal articles can not. It would be a novel approach for dissemination of scientific knowledge.

So, I can see a knol developing into some sort of secondary arena for publication of scientific research, for example. This would be a paradigm-shifting possibility. I will be very interested to see if this avenue is used much by the scientific community.

However, the same problem of filtering still matters. Knols could be a tremendous path to transforming tacit information but there will still be an information glut to deal with. My concerns come more from how these articles are found and dealt with.

In the scientific community, this sort of authorship is now dealt with by peer review and publication in reputable, high impact journals. If a knol is going to provide anything similar, especially when it comes to reputation, it will have to function a little differently than it does now.

I don’t worry strictly about people plagiarizing as much as diverting. An example off the top of my head:

I put something up about my latest, cutting edge research. Perhaps about some research in press but with more detail than normal. Perhaps I include some of the information from my grant requests.

The essay provides a spot for people to read about my work and comment, potentially providing insights and questions that can accelerate my ability to innovate, leading me to new areas of research while providing me with documentation for my performance reviews. Great.

This is what the Web provides that no other medium does. And everyone wins. I get my ego-driven scientific reputation enhanced and the world gets a lot of information made available for others to use.

But my article is written for a scientific audience.

Then someone (say a good science writer) takes that information, rewrites it and uses SEO approaches to make sure that people find that article before mine and create ad-driven revenue for themselves.

They get very popular (as I hope they would be, since good science writers are important), get found first from search engines and my page views plummet. So then I have to justify why I wasted my time publishing my research.

No one here is doing anything wrong but it becomes more of a zero-sum game now instead of a win-win. I would no longer have any incentive to use this approach to write about my work.

So, at this point, I am still a little worried about how the articles will be found, just how reputation will be determined and how the filtering of information will be accomplished.

But I do think there is a place for this sort of approach. It may not be there yet but having information ‘owned’ by someone will provide new avenues of dissemination not seen with more anonymous approaches.

It just may take a few iterations to get to perfection.

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What scientists are we talking about?

research by SqueakyMarmot
Obligatory Reading of the Day: Opening up Scientific Culture [A Blog Around The Clock]:
[Via ScienceBlogs : Combined Feed]

Why are so many scientists reluctant to make full use of Web 2.0 applications, social networking sites, blogs, wikis, and commenting capabilities on some online journals?

Michael Nielsen wrote a very thoughtful essay exploring this question which I hope you read carefully and post comments.

Michael is really talking about two things – one is pre-publication process, i.e., how to get scientists to find each other and collaborate by using the Web, and the other is the post-publication process, i.e., how to get scientists to make their thoughts and discussions about published works more public.

Those of you who have been reading me for a while know that I am thinking along some very similar lines. If you combine, for instance, my review of Rainbows End by Vernor Vinge with

On my last scientific paper, I was both a stunt-man and the make-up artist with Journal Clubs – think of the future! with The Scientific Paper: past, present and probable future, you will see a similar thread of thinking.

But, what do you think?

Read the comments on this post…

Michael Nielsen’s essay is well worth reading, since it goes into some detail about the need for openness in science. It has a lot of depth and it very thought provoking.

The comments are also very interesting, with an ongoing dialog between skeptics and believers. But a lot of these discussions only examine the barriers and pressures of a very small slice of the researchers in the US.

The science that is discussed in these essays really only encompasses those scientists in research universities where tenure competition is the fiercest. Take a look at some recent statistics (2006):

22 million scientists/engineers in US
18.9 million actually employed
69.4% work in the business sector
11.8% work for the government
8.2% work at 4 year institutions
9.7% work in the business/industry sector for a non-profit

This discussion seems to have focused on just a small fraction (but an important one) of the number of scientists who would benefit from these tools. These researchers are funded by grants and are in tenure-track positions at 4 year research universities.

More scientists work at non-profits. What sorts of pressures are brought to bear there to prevent open collaboration? How different are these pressures from a research university? Those in business might also benefit from these approaches but have another set of barriers. Can they be surmounted?

This discussion is really important but it also conflates a large number of scientists/engineers who have different needs and pressures. There are 12 million in business who will have different needs than the 1.6 million at research universities.

How do Web 2.0 approaches impact them differently? Will some be more readily accepting of these tools than others?

We need to realize that scientists encompass a much larger group than those in tenure track positions at universities.

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