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SmartData Collective > Uncategorized > WikiDashboard: Visualizing Wikipedia Edits
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WikiDashboard: Visualizing Wikipedia Edits

Daniel Tunkelang
Daniel Tunkelang
3 Min Read
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Ed Chi, a senior research scientist at the Palo Alto Research Center (PARC), recently delivered a presentation at MIT about  WikiDashboard, a tool that he and PARC colleague Bongwon Suh developed in order to visualize the dynamic nature of Wikipedia’s collaborative editing process. Erica Naone, a regular here at The Noisy Channel, wrote a nice article about it in Technology Review, entitled “Who’s Messing with Wikipedia?“.

I like Ed Chi’s work, and we talked about the WikiDashboard project when I visited him at PARC just over a year ago.  But, as I was quoted in the article, I do wonder what problem this visualization aims to solve. A picture, it is said, is worth a thousand words, but this feels too much like looking at a thousand words. I hope that Ed and the team at PARC invest in distilling a more consumable signal out of this wealth of data that can be applied to solve real problems.

I also hope, that as Rob Miller points out in the article, the collection and publication of suh measurements does not simply enourage people to game them.

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Collective knowledge systems

Ed Chi, a senior research scientist at the Palo Alto Research Center (PARC), recently delivered a presentation at MIT about  WikiDashboard, a tool that he and PARC colleague Bongwon Suh developed in order to visualize the dynamic nature of Wikipedia’s collaborative editing process. Erica Naone, a regular here at The Noisy Channel, wrote a nice article about it in Technology Review, entitled “Who’s Messing with Wikipedia?“.

I like Ed Chi’s work, and we talked about the WikiDashboard project when I visited him at PARC just over a year ago.  But, as I was quoted in the article, I do wonder what problem this visualization aims to solve. A picture, it is said, is worth a thousand words, but this feels too much like looking at a thousand words. I hope that Ed and the team at PARC invest in distilling a more consumable signal out of this wealth of data that can be applied to solve real problems.

I also hope, that as Rob Miller points out in the article, the collection and publication of suh measurements does not simply enourage people to game them.

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