Scientific Researchers and Web 2.0: Social Not Working? forum: topic
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Are there too many data to construct scientific hypotheses?
Maxine Clarke
Sunday, 29 June 2008 08:42 UTC
Chris Anderson has written an article in Wired magazine: The End of Theory: The Data Deluge Makes the Scientific Method Obsolete, which has stimulated much discussion (some examples are in the thread of comments to the Wired piece).
A central point of the Wired article is that biology has become “too big”: there are too many data for hypotheses to be proposed and tested. The article goes on to propose that, as David Basanta writes in a post on his blog at Nature Network, “with plenty of data and clever algorithms (like those developed by Google), it is possible to obtain patterns that could be used to predict outcomes…and all that without the need of scientific models.”
The most persuasive rebuttal to the Wired article that I have read (so far!) is at ArsTechnica website, which concludes: “the data cloud is changing science, and leaving us in many cases with a Google-level understanding of the connections between things. Where Anderson stumbles is in his conclusions about what this means for science. The fact is that we couldn’t have even reached this Google-level understanding without the models and mechanisms that he suggests are doomed to irrelevance. But, more importantly, nobody, including Anderson himself if he had thought about it, should be happy with stopping at this level of understanding of the natural world.”
(Note, Chris Anderson is Editor of Wired. He is author of “The Long Tail” and some years ago was a science news journalist at Nature.)
Updated 29 June 2008 08:57 UTC
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Replies
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The FriendFeed life scientists group is underwhelmed by the Wired piece. This, for example, is Deepak’s view:
“We were crunching the genome with huge clusters a decade ago. As we get more information, our models get better. To make more sense of this information our theory has to get better to as Lee Hood always says.”
I cannot work out if I can or how to link to the Friend Feed conversation itself, but it is taking place within the Life Sciences group, which is here. I have invited them all to join this Nature Network group. -
Maxine, interesting cross-posting. I would agree that the large amounts of data produced in many experiments today require a different scientific approach. But that doesn’t change the fundamentals of how we do science. But the Wired article certainly was intended to stir up a discussion.
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Maxine, every item on FriendFeed has “comment hide like more” links — click on “more” and you get an option “link to this entry” which will give you a permalink. You can’t link to a comment but the thread you mentioned is here.
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Thanks, Bill, much appreciated.
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Here’s another comment from the FriendFeed group, this one from Neil Saunders, perhaps worth a forum post and comment thread of its own:
I think very little “web 2.0 for scientists” is working. In terms of not only uptake, but also the type of sites being developed. It’s the data that need to be social, not the people. -
The more I read the piece, the more irritated I get. It comes across repeatedly as writing that betrays Anderson’s complete lack of understanding of science. Every time some big change happens, e.g. the volume and complexity of the data types, it requires us to rethink our approach (nothing new there). That also means refining our models, and trying to understand how things work. It is no surprise that a lot of efforts in pharma for exampl are now towards understanding pathways and mechanisms, cause the focus on trying to get the data to tell us something is not working. One needs to start with some questions and hypotheses and then query the data. Just because the data exist doesn’t mean they are magically going to explain molecular interactions and behavior. To think otherwise is foolish.
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Bob O’Hara has provided his perspective here — lots of data, too few samples.
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On the topic of the ‘data deluge’, the UK Government has opted for an increasingly used technique (e.g. Elsevier’s Grand Challenge ) to scope ideas for a strategy for how to make best use of interrelated information.
See the BBC coverage of it here and the Cabinet Office’s Power of Information Taskforce pages ‘Show Us a Better Way’ here.
Here is the BBC blurb:
The UK government has launched a competition to find innovative ways of using the masses of data it collects. It is hoping to find new uses for public information in the areas of criminal justice, health and education. The Power of Information Taskforce, headed by cabinet office minister Tom Watson – is offering a £20,000 prize fund for the best ideas. To help with the task, the government is opening up gigabytes of information from a variety of sources.I think it’s quite interesting that both business and Government are realising that harnessing the ‘power of the crowd’ and offering a prize may be the most cost-effective way of harnessing innovative ideas around postmodern challenges. A penny for your thoughts?
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There is a little bit more discussion of the Wired article at From the blogosphere. In the comment thread there, Sabine Hossenfelder links to her interesting post about Chris Anderson’s proposal, from the phyisical sciences perspective.
Changing subject slightly, that government initiative is interesting, Sarah. I picked it up for the Peer to Peer blog, where we previously discussed technical solutions to the question of peer-review. In that debate, we published one article by a certain Chris Anderson, about the “wisdom of the crowds” approach to peer-review. Let the [online] readers decide! (That was the thesis.)
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