All posts by Richard Gayle

Science, Web 2.0

Browsing for researchers

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

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

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

RSS and newsreaders present an incredible set of tools to filter through a lot of information very rapidly. It is like you are directly hooked into to a diverse group of communities in real time. You can see how different items spread through a linked community and drive communication.

And the orderly vs crazy approaches to connecting help one’s own creativity and innovation by interacting with our tacit information, producing the opportunity to alert other communities.

I like how Chris Brogan describes his reading goals.

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

This sounds very much like an early adopter, who has connection outside to other media outlets, but uses trusted insiders to decide what things to use.

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

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

One of the major aspects of scientific research and innovation comes from browsing, from reading about something not directly related to a specific problem but which may provide valuable insight for the problem. This used to be relatively easy by doing things like sitting in the library once a week going through the table of contents of all the journals that came in that week, carefully writing down the bibliographic information on note cards, so they could be examined later at leisure.

Serendipity could raise its head. But the Internet made searching so much easier. So too many scientists spend their time on the first step, finding. This is, of course, very important but you will really only find what you are looking for. Serendipity is reduced.

A personal example. Many years ago, I was working on inducing protein production in E. coli from specific gene segments. We typically did this by shifting the temperature, which resulted in the inactivation of a repressor and the expression of the gene.

However, for large scale production (think 1000s of liters) this was not a tenable solution. It was really impossible to raise the temperature of the vessel quick enough to make it a viable solution.

I happened to be reading the Table of Contents of the Journal of Bacteriology and saw a paper which discussed some of the biological effects on the bacteria when the pH of the media was shifted to a more acidic condition. I recognized some of the bacterial proteins involved as being similar to the repressor we used.

So I went out and did some experiments and determined that by dropping the pH, large amounts of the specific protein could be produced. Dropping some acid in a large vessel and stirring quickly can rapidly expose all the cells to the same conditions and induce protein production.

But it could also be done under some different conditions, resulting in up to 15 times more recombinant protein being produced.

So, for me, the really important aspect of RSS/newsreaders is bringing browsing back. Every journal has newsfeeds now. I can typically go through several thousand titles in an hour, bookmark the ones I want to examine later and even post the links to a blog, where I can add comments.

My blog becomes my online note card file for interesting articles.

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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?
[More]

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

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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Web 2.0

Making Friends

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friends by jurvetson

I wanted to bring my personal perspective of the 5 steps people go through while adopting a new technology. It has to do with FriendFeed.

I have been aware of FriendFeed for several months, but never did much with it. I was not really sure what it provided, and I just did not have the time to explore it. But my interest built up as I saw more of the scientists whose newsfeeds I subscribe to begin to discuss their experiences with it. My interest increased seeing the mashups that were developing – such as the widgets that could connect a blog with FriendFeed comments, etc.

But I was still too busy and I was not sure if it was worth the time to figure out the best way to use it, what was required, etc. So my progression through the first stages was a little slow as I still did not really see how it would help me. There were no ‘local’ authorities of mine that had adopted it.

Then, just a few days ago, I got a lot of hits and the referer was a specific FriendFeed page about Science 2.0, where the website was being discussed. In fact, there was quite a conversation going on, one that I had to join. Now I began to see what could be really useful about FirendFeed.

So I actually raced through the last 2 steps very fast. Trial took about 2 minutes since FriendFeed is pretty straightforward and i was congratulating myself for the adoption stage even as I was writing my second comment.

All this would suggest that I am an early adopter. not an innovator. Which is what I expected. I needed some interactions with members of the community rather than hearing it from outside experts.

But this also indicates just how rapidly a new innovation can move if it finds the right path. Especially when there are conversations happening, information being exchanged,

People will adopt a new innovation really fast if there is a conversation about them or their research interest, and they want to be a part of the conversation. I would expect most scientists would plow right through the latter stages of the 5 steps if their research was directly influenced by the conversation.

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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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Web 2.0

Sharing – a business model

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Share Share Share Share Share:
[Via chrisbrogan.com]

PAB 2008 One of the things people will get wrong when trying to determine how to make a more human-shaped web for their company is sharing. Sharing is something that was left out of the business books for the last forty or fifty years. Your company isn’t set up to share. It’s not in the genetics, and as such, the people responsible for figuring out how to collaborate and do something in this whole new web are going to run into a problem quickly.

We Share Everything

Why do these web tools make so much sense to digital natives? Because they have sharing built into the infrastructure. We use Flickr because it’s easy to share the photos. We use Del.icio.us because it lets us share bookmarks easier. We’re blogging, podcasting, mashing up, remixing, sharing files, sharing everything because it’s easier.

This is a key difference between new tech organizations and MBA-base 20th Century ones. Sharing and collaboration are in the DNA. The problems being attacked are too complex for any one group to control all the answers. But collaboration provides a method, leveraging human social networks in novel ways, whereby these barriers can be surmounted.

Share Business

I won’ give the details but Shel Holtz has now twice shared with me business opportunities. He’s sent them through to me in such a way that the person contacting me makes me feel like Shel convinced him or her that I am the ultimate person ALIVE to do whatever they request of me.

Today’s request like that was to speak at a really great company. I couldn’ make the date, as I have a conference of my own during that time frame, so I did what Shel did. I shared. I passed the person on to a friend in Atlanta who would be able to do exactly what I would’ve done.

An organization that does not share will not be able to utilize the new online tools to their fullest. Web 2.0 is all about conversations. No one wants to have a conversation where one side only takes and does not give. Or one side only speaks and does not listen. Monologs are just not fruitful.

Collaborators will go elsewhere.

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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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