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Science was always about mashing up, taking one result and applying it to your [work] in a different way. The question is ‘Can we make that as effective [for] samples [of] data and analysis as it [is] for a map and set of addresses for a coffee shop?’ That is the vision. — Cameron Neylon
Those words, found on a great post at the Science Commons blog, have been stuck in my head since I saw them.
I’ve talked about mashing up science many times. In my time in the bioinformatics industry, the need to do “integrative genomics” comes up again and again, yet the approaches we adopt to solve those problems are either too heavy and complex, or simply abandoned due to the inherent gaps in our data.
Mashups, e.g. the ones with Google Maps that we are all used to, are not trivial. They are enabled by some very cool technology at the back end, but we’ve managed to abstract away the complexity and enable creativity and utility. We need innovators in the life sciences, people who will build the backend infrastructure and enable creativity. The Biogang and many others in the community would be so much more effective given the right tools. We end up locking too much away in proprietary software, in complexity, or in paradigms written for a different era, but I think we’re making slow progress. Increasingly people are becoming aware of what can be achieved in today’s web-scale world. There are people who are at the cutting edge, but don’t quite look as cutting edge as they might have a few years ago.
I would like to throw down the challenge to commercial providers of life science software. Join the web of data. Architect for innovation. Think about new business models, cause I am not sure the traditional ones are sustainable, and innovation is limited (with some notable exceptions). Help people not only collect and analyze data, but re-mix and re-purpose.
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5 Comments
Research, particularly biology, has been reductionist for a long time. Biology has been primarily analytical, breaking things down to their smallest parts.
Now we need, synthesis, mashups. We need to develop the business and non-business structures to support this.
Have you read this article by John Stine? It is really relevant to those of us in Seattle.
How do we support garage bio? How do we get these small focussed groups up to speed and provide outlets for the large number of scientists with no where else to go? Should we think convening a group of us to see what we can brainstorm?
Richard, I had not read that article. Thanks.
As for garage bio, the “bursty work” meme I adhere to is part of that concept, as are some of my own, somewhat slow starting, efforts. Personally I believe in distributed, somewhat informal, efforts like the biogang (http://openwetware.org/wiki/Biogang). I think the key is using the web and finding information and collaborators.
Richard, I had not read that article. Thanks.
As for garage bio, the “bursty work” meme I adhere to is part of that concept, as are some of my own, somewhat slow starting, efforts. Personally I believe in distributed, somewhat informal, efforts like the biogang (http://openwetware.org/wiki/Biogang). I think the key is using the web and finding information and collaborators.
Research, particularly biology, has been reductionist for a long time. Biology has been primarily analytical, breaking things down to their smallest parts.
Now we need, synthesis, mashups. We need to develop the business and non-business structures to support this.
Have you read this article by John Stine? It is really relevant to those of us in Seattle.
How do we support garage bio? How do we get these small focussed groups up to speed and provide outlets for the large number of scientists with no where else to go? Should we think convening a group of us to see what we can brainstorm?
Richard, I had not read that article. Thanks.
As for garage bio, the “bursty work” meme I adhere to is part of that concept, as are some of my own, somewhat slow starting, efforts. Personally I believe in distributed, somewhat informal, efforts like the biogang (http://openwetware.org/wiki/Biogang). I think the key is using the web and finding information and collaborators.