Crowd-Sourcing: Strength in Numbers. Ball, P. 506(7489):422–423. ![Crowd-Sourcing: Strength in Numbers [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Researchers are finding that online, crowd-sourced collaboration can speed up their work if they choose the right problem. [Excerpt] [...] Yet this open approach has taken root as an ongoing crowd-sourcing project called Polymath. [...] Polymath 8 was a triumph for the collaborative approach, says Tao. If mathematicians had been attacking the problem in the standard way, with what he describes as ” a flood of mini-papers”, it might have taken years to get the bound down that far. Polymath has not always worked so well, however: some of the challenges simply never got off the ground. But after five years of experience with it, users have begun to home in on the features that determine success. For example, says Tao, ” It helps if the problem is broadly accessible and of interest to a large number of mathematicians”. This tends to draw a wide range of participants with a rich mix of skills, but it works only if the problem can easily accommodate what they have to offer. That was one of the virtues of the twin-primes challenge, says Maynard. ” The proof can be split into separate sections, with each section more-or-less independent of the others,” he says. Perhaps the most important lesson is that setting up and sustaining a Polymath project is a big commitment. So far, Tao and Gowers have initiated all but two of the Polymath projects. ” It's quite difficult to get people interested,” Gowers admits. ” It needs an active leader who is willing to spend a fair amount of effort to organize the discussion and keep it moving in productive directions,” says Tao. ” Otherwise, the initial burst of activity can dissipate fairly quickly.” [...]
@article{ballCrowdsourcingStrengthNumbers2014,
title = {Crowd-Sourcing: Strength in Numbers},
author = {Ball, Philip},
date = {2014-02},
journaltitle = {Nature},
volume = {506},
pages = {422--423},
issn = {0028-0836},
doi = {10.1038/506422a},
url = {https://doi.org/10.1038/506422a},
abstract = {Researchers are finding that online, crowd-sourced collaboration can speed up their work if they choose the right problem.
[Excerpt] [...] Yet this open approach has taken root as an ongoing crowd-sourcing project called Polymath. [...] Polymath 8 was a triumph for the collaborative approach, says Tao. If mathematicians had been attacking the problem in the standard way, with what he describes as ” a flood of mini-papers”, it might have taken years to get the bound down that far.
Polymath has not always worked so well, however: some of the challenges simply never got off the ground. But after five years of experience with it, users have begun to home in on the features that determine success. For example, says Tao, ” It helps if the problem is broadly accessible and of interest to a large number of mathematicians”. This tends to draw a wide range of participants with a rich mix of skills, but it works only if the problem can easily accommodate what they have to offer.
That was one of the virtues of the twin-primes challenge, says Maynard. ” The proof can be split into separate sections, with each section more-or-less independent of the others,” he says.
Perhaps the most important lesson is that setting up and sustaining a Polymath project is a big commitment. So far, Tao and Gowers have initiated all but two of the Polymath projects. ” It's quite difficult to get people interested,” Gowers admits. ” It needs an active leader who is willing to spend a fair amount of effort to organize the discussion and keep it moving in productive directions,” says Tao. ” Otherwise, the initial burst of activity can dissipate fairly quickly.” [...]},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13073389,cooperation,crowd-sourcing,editorial,free-scientific-knowledge,knowledge-freedom,mathematics,research-management,scientific-knowledge-sharing},
number = {7489}
}
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