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

Interesting observation by Kevin Kelly. He says

Where ever attention flows, money will follow

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

Marketing and innovation produce results; all the rest are costs

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

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

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

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

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

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

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

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

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

KK link via Michael Nielsen

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

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

Technorati Tags: Science, Web 2.0

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

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

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

I like how Chris Brogan describes his reading goals.

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

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

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

Technorati Tags: Science, Web 2.0

by tanakawho
Digital intimacy:
[Via Bench Marks]

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

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

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

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

But they do work by spreading information farther and faster.

Technorati Tags: Social media, Web 2.0

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Technorati Tags: Science, Web 2.0

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!

Technorati Tags: Science, Web 2.0

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.

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.

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?

Technorati Tags: Science, Social media, Web 2.0

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.

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.

Technorati Tags: Science, Web 2.0

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

Image 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.

Technorati Tags: Science, Web 2.0