Michael Nielsen on Networked Science - WSJ.com
In January 2009, a mathematician at Cambridge University named Tim Gowers decided to use his blog to run an unusual social experiment. He picked out a difficult mathematical problem and tried to solve it completely in the open, using his blog to post ideas and partial progress. He issued an open invitation for others to contribute their own ideas, hoping that many minds would be more powerful than one. He dubbed the experiment the Polymath Project.
Several hours after Mr. Gowers opened up his blog for discussion, a Canadian-Hungarian mathematician posted a comment. Fifteen minutes later, an Arizona high-school math teacher chimed in. Three minutes after that, the UCLA mathematician Terence Tao commented. The discussion ignited, and in just six weeks, the mathematical problem had been solved.
Other challenges have followed, and though the polymaths haven't found solutions every time, they have pioneered a new approach to problem-solving. Their work is an example of the experiments in networked science that are now being done to study everything from galaxies to dinosaurs.
These projects use online tools as cognitive tools to amplify our collective intelligence. The tools are a way of connecting the right people to the right problems at the right time, activating what would otherwise be latent expertise.
Networked science has the potential to speed up dramatically the rate of discovery across all of science. We may well see the day-to-day process of scientific research change more fundamentally over the next few decades than over the past three centuries.
But there are major obstacles to realizing this goal. Though you might think that scientists would aggressively adopt new tools for discovery, they have been surprisingly inhibited. Ventures such as the Polymath Project remain the exception, not the rule.
Consider the idea of sharing scientific data online. The best-known example of this is the human genome project, whose data may be downloaded by anyone. When you read in the news that a certain gene is associated with a particular disease, you're almost certainly seeing a discovery made possible by the project's open-data policy.
Despite the value of open data, most labs make no systematic effort to share data with other scientists. As one biologist told me, he had been "sitting on [the] genome" for an entire species of life for more than a year. A whole species of life! Just imagine the vital discoveries that other scientists could have made if that genome had been uploaded to an online database.
Why don't scientists share?
If you're a scientist applying for a job or a grant, the biggest factor determining your success will be your record of scientific publications. If that record is stellar, you'll do well. If not, you'll have a problem. So you devote your working hours to tasks that will lead to papers in scientific journals.
Even if you personally think it would be far better for science as a whole if you carefully curated and shared your data online, that is time away from your "real" work of writing papers. Except in a few fields, sharing data is not something your peers will give you credit for doing.
There are other ways in which scientists are still backward in using online tools. Consider, for example, the open scientific wikis launched by a few brave pioneers in fields like quantum computing, string theory and genetics (a wiki allows the sharing and collaborative editing of an interlinked body of information, the best-known example being Wikipedia).
Specialized wikis could serve as up-to-date reference works on the latest research in a field, like rapidly evolving super-textbooks. They could include descriptions of major unsolved scientific problems and serve as a tool to find solutions.
But most such wikis have failed. They have the same problem as data sharing: Even if scientists believe in the value of contributing, they know that writing a single mediocre paper will do far more for their careers. The incentives are all wrong.
If networked science is to reach its potential, scientists will have to embrace and reward the open sharing of all forms of scientific knowledge, not just traditional journal publication. Networked science must be open science. But how to get there?
A good start would be for government grant agencies (like the National Institutes of Health and the National Science Foundation) to work with scientists to develop requirements for the open sharing of knowledge that is discovered with public support. Such policies have already helped to create open data sets like the one for the human genome. But they should be extended to require earlier and broader sharing. Grant agencies also should do more to encourage scientists to submit new kinds of evidence of their impact in their fields—not just papers!—as part of their applications for funding.
The scientific community itself needs to have an energetic, ongoing conversation about the value of these new tools. We have to overthrow the idea that it's a diversion from "real" work when scientists conduct high-quality research in the open. Publicly funded science should be open science.
Improving the way that science is done means speeding us along in curing cancer, solving the problem of climate change and launching humanity permanently into space. It means fundamental insights into the human condition, into how the universe works and what it's made of. It means discoveries not yet dreamt of.
In the years ahead, we have an astonishing opportunity to reinvent discovery itself. But to do so, we must first choose to create a scientific culture that embraces the open sharing of knowledge.—Mr. Nielsen is a pioneer in the field of quantum computing and the author of "Reinventing Discovery: The New Era of Networked Science," from which this is adapted.