Category Archives: Science

Science, Web 2.0

As always

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cats 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?
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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.

These tools are rapidly becoming a part of how human communities disperse information. This decreases the diameter of a social network tremendously, meaning information of every type has to traverse fewer nodes.

Research networks that normally involved publications, seminars, conferences, etc. will also include these social media approaches. Because labs that remain unconnected will not be able to compete with labs that do use these tools to decrease the diameter of their sphere of collaborations and fid out about relevant information faster.

These tools are just part of finding out what is happening in relevant fields. I’ll give an example of how these tools can help move information in ways not possible before.

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.

Turns out they were having a conversation about my site and were asking a lot of questions, trying to get an idea of who I was , my reputation, etc. Seeing the conversation, I quickly joined and helped answer questions. Now I am a part of a group I can check in on every so often that does a great job finding and providing information I find useful.

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.

Human social networks are exceptionally great filters of information. The huge amounts of information being created today require human networks to help filter and disperse the info. These tools are simply one part.

All that will really be necessary is for a scientist just to be part of a research network, even just a lab, in which someone is connected to these online sites. What is important is the rate at which this information diffuses throughout the group, not that everyone in the group is connected to Twitter.

Each person in a network often has their own role, their own diverse viewpoint that helps the group. The best tools will be ones that allow people to use them for their own purposes and needs. They do not work by forcing everyone to join.

But they do work by spreading information farther and faster.

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Open Access, Science, Web 2.0

A five step process

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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.


Diffusionofinnovation


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.

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Science, Web 2.0

Mining with friends

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digging 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.

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Knowledge Creation, Non-Profits, Science, Web 2.0

An Announcement

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spirals by hendriko
All the details have been finalized for a three hour seminar SpreadingScience is sponsoring entitled

Transformed! Information, Bioscience and Web 2.0

October 7, 2008 6-9 PM
Lake Washington Rowing Club
910 N. Northlake Way
Seattle WA

The seminar will be given by Richard Gayle, Ph.D. and Mark Minie, Ph.D. It is geared for a general audience that includes researchers, lawyers, clinicians and anyone else interested in using modern technology to solve today’s problems. It will have three segments:

  1. The Transformation of Information into Knowledge
    Knowledge is the ability to make a decision, to perform an action. The knowledge creation cycle begins with data. Human social interactions transform data into knowledge. Social networks evolved to provide primates with diverse solutions to complex problems. However, there appear to be hardwired barriers to the size of these social networks, limiting the scope and complexities of the problems that can be solved. The huge amount of information being generated overwhelms these barriers. The difficult problems facing us today are too complex to be solved only the tools we evolved. We must use new digital tools to amplify our inherent abilities.
  2. The Transformation of Bioscience by Information
    Biology is now a branch of Information Science, and important new research, discovery and invention is taking place on the World Wide Web. From computer gaming/education to personal genomics, biological engineering and robotics, bioscience is undergoing a true renaissance with previously unexpected impact and dividends. This segment will explore bioscience’s new life on the Internet. It will focus on specific examples and new tools with potential practical uses for both scientists and non-scientists alike.
  3. The Web 2.0 Transformation
    Web 2.0 is about online conversations. These tools often remove the need for people to occupy the same space at the same time in order to transform information into knowledge. They permit the examination and understanding of human social networks many times larger than our hardwired limits. This enhances the ability to create knowledge and to increase the rate of diffusion of information in an organization. Communities that can use Web 2.0 tools to leverage human social networks will solve complex problems more rapidly than those that do not.

There is a glut of data in the world today. Our normal processes to deal with this glut – the interactions in a human social network – are overwhelmed. However, the same technologies that are permitting such huge amount of data to be created can also help us enhance our social network interactions, providing organizations with the possibility of solving much more complex problems than before.

 

Please join us on October 7 as we provide a foundation for understanding how Bioscience is being transformed by information and how we can use novel tools to leverage this transformation into critical solutions .

Until September 23, the cost is $175. After that date it rises to $225. So register early!

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Science, Web 2.0

Research of the future

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UW quad by nordique
The independent research institute will drive biomedical innovation:
[Via business|bytes|genes|molecules]

The Broad Institute just got a donation of $400 million from Eli and Edyth Broad. The donation is the formal start of an endowment, making the Broad Institute a permanent, standalone biomedical institution.

I have bemoaned the death of such bastions of innovation like Bell Labs in the past. But there is a trend in the biomedical sciences that is encouraging. Non-profit institutes and research centers like the Broad, The Wellcome Trust Sanger Institute, Janelia Farms, The Institute for Systems Biology, etc, with funding from powerhouse funders like the Wellcome Trust and the Bill and Melinda Gates Foundation are leading a trend towards independent research centers. Given the requirements for focussed cross-disciplinary research, I have a strong feeling that many of the innovations of the next quarter century are going to come from such institutions, funded by non-profits, private enterprises, and non-profit arms of companies like Google.

There will always be place for such federally funded institutes, especially those that fit the model of the ones described above, e.g. the Joint Bioenergy Institute. I wonder, in this changing environment, what the role of the traditional research university will be? In the life sciences, I see a continuum of research and collaboration, between universities, well-funding research institutes, and private enterprise. If we can harness the best of all three arms of research, I think we will be successful at innovation and not get in the kinds of rut we often do today, with too much overlap, little focus, and attempts at trying to leverage a somewhat broken federal funding system.

Is this a growing trend? Are we at risk of diluting the research pool by having too many institutes? We’ll just have to wait and see, but I am quite optimistic.

I think Deepak has hit on a very important trend. Independent, non-profit research centers are a real hotbed now, not only because of the large amount of money from large funders. There is also a lot of Federal money heading towards them.

Many large research universities do not handle collaboration well. It is just the what they are put together. Too often it is viewed as a zero-sum game, where helping other departments succeed is not viewed as helpful to your own.

Many corporations do not do research very well also, especially collaborations with other institutions. The focus on near-term profits prevents them from effectively dealing with really complex biological problems.

But non-profits fit right in the sweet spot. They HAVE to solve difficult problems, with deadlines much like small startups but with the freedom of endeavor and choice of research direction seen in universities. Since few are big enough to do everything themselves, collaboration is really required. This drives them to find the best solution to solve their problem, even if that requires collaboration.

Also, I think that this approach will draw many of the high powered researchers to the non-profit organization. At these non-profits, they can spend all their time dealing with research, and a much lower amount of their grants goes to overhead (up to 65% of each grant goes to such overhead at a university). This means that more money can actually be spent on research.

So, more money for research and less time devoted to other things means that more researchers may move to these non-profit research institutions, making them even more powerful.

It could well be that many universities simply return to undergraduate education and that large-scale research will move to these independent non-profit research institutes. What do you think?

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Science, Web 2.0

Data transformation

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potatoes by Avoir Chaud
Bioinformatics as mashup:
[Via business|bytes|genes|molecules]

bioinformatics: acquiring, collating and rearranging information already available elsewhere?

That is from a Tweet by Neil. My reaction was somthing along the lines of “boy that sounds like the definition of a mashup”.

Bioinformatics is a broad field, but part of it, a good part of what a bioinformatician does is exactly what Neil describes. The work of a bioinformatician is built on data collected by many people around the world and deposited in a variety of data bases. A lot of what we do is take information from one and try and match it up to information from a second source, presumably with the goal of getting additional insights. It might sound crude to call it that, but I think if we start thinking of bioinformatics as a mashup, we could start thinking about making those mashups available to others, and perhaps even new ways to present the information.

Disclaimer: This post was written early in the morning before any intake of caffeine

This is exactly right. Data just exists. It requires human interaction to provide context. Sitting in a database does nothing.

Mashups, as described here, take explicit information and transform it into knowledge. The key is to provide the right tools so that appropriate mashups can be performed. Perhaps Ubiquity will provide an avenue for such mashups.

Science, Web 2.0

Change the culture

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coral by jurvetson
How academic health research centers can foster data sharing:
[Via Science Commons]

PLoS Medicine today published a new paper that provides useful guidelines for people at academic health centers seeking to support scientific data sharing. The paper, Towards a Data Sharing Culture: Recommendations for Leadership from Academic Health Centers, discusses both the enormous benefits and the obstacles to forging a research culture that fosters data sharing, and outlines practical steps people can take to set the process in motion.
[More]

There are some very useful recommendations in the paper. It will really take some changes in scientific culture for some of them to be undertaken. But the faster these changes are made, the sooner the benefits can be seen.

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Science, Web 2.0

Ubiquity is hot

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The ‘Ubiquitous’ web:
[Via business|bytes|genes|molecules]

MozillaImage via Wikipedia
All of you know about it already, but I shall happily add to the noise. Last evening I had one of those “Holy S**t” moments. Was sitting in a coffee shop, catching up with the days news, when I saw a flurry of activity on Friendfeed around Ubiquity. Turns out Ubiquity is a new project by Mozilla Labs, which for want of a better description is like Quicksilver for the browser, a mini command line available with an Alt-space.

[More]

Ubiquity looks to be very interesting and useful. It will be nice to use this for various science mashups. One more reason to use Firefox.

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Science, Web 2.0

Blogging on research

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sand by fdecomite
More on bloggers and OA:
[Via Open Access News]
Bora Zivkovic, ResearchBlogging.org, v.2.0, A Blog Around the Clock, August 29, 2008.

… [W]e took a little look [at the new release of ResearchBlogging.org] at the PLoS HQ and noticed that out of 87 pages of ‘all results’ there are 8 pages of ‘PLoS’ results – implying that about 10% of all the [ResearchBlogging.org] posts are on PLoS papers from all seven journals – and of those, 4 pages are just on PLOS ONE papers – which is about 5%. All I can say is w00t! for Open Access – when bloggers can read, bloggers will write.

ResearchBlogging demonstrates how blogging can be used to disburse information. The individual writers serve as excellent filters. It is like a journal club online, providing a way to cut through some of the jargon in a paper and see what its real relevance is.

It is one step above “Hey, did you see the paper in the latest Blood about X?” Now when an interesting paper is found, a short synopsis, with the proper attribution is available to a large network.

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Science, Web 2.0

Science blogging = new email?

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51 188520673 18F6208421 by cadmanof50s
Science blogging is the new email:
[Via Gobbledygook]

The just finished conference Science Blogging 2008: London was a wonderful chance for real-life socialising networking. I started to upload some fotos to Flickr (e.g. Scott Keir explaining sign language, see all fotos tagged sciblog here), some of them are too embarrassing and I will keep them for bribes reference later on.

The meeting was also a great opportunity to think about where we are today with scienceblogging. Having a conference is a good sign that the field is evolving1, and you can see several subdisciplines evolving:

  • conference blogging (also includes event blogging)
  • edublogging
  • metablogging (blogging about blogging, by far the largest discipline)
  • research blogging (blogging about scientific experiments, the smallest discipline)
  • investigational blogging (the keynote lecture by Ben Goldacre described this very well)
  • evolution blogging (a large subdiscipline)
  • news blogging (blogging about science news)
  • watercooler blogging (small pieces of interesting or funny thoughts/pictures)
  • summary blogging (summarizing other blog posts and linking to them)
  • diary blogging (blogging as a personal diary of self-expression)
  • hoax blogging (see this example by Jonathan Eisen)

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This is a pretty interesting framing of the use of blogs for research. A lot of useful scientific inquiry is informal in nature, occurring around a coffee machine or at a pub. Blogs just allow people who do not share the same time or place to participate. And in a more useful fashion than email.

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