“A YouTube for Data”
If you go to your Web browser and type in www.swivel.com, all you get is a pretty little “coming soon” banner. But if you read about Swivel here on TechCrunch, it sounds like a godsend — or at least a tremendous way to waste time — for data freaks.
Michael Arrington at TechCrunch says that Swivel’s founders describe the forthcoming website as “YouTube for data,” but it’s really much better than that. Here, according to Arrington, is how Swivel will work:
[T]he site allows users to upload data — any data — and display it to other users visually. The number of page views your website generates. Or a stock price over time. Weather data. Commodity prices. The number of Bald Eagles in Washington state. Whatever. Uploaded data can be rated, commented and bookmarked by other users, helping to sort the interesting (and accurate) wheat from the chaff. And graphs of data can be embedded into websites. So it is in fact a bit like a YouTube for Data.
But then the real fun begins. You and other users can then compare that data to other data sets to find possible correlation (or lack thereof). Compare gas prices to presidential approval ratings or UFO sightings to iPod sales. Track your page views against weather reports in Silicon Valley. See if something interesting occurs.
And better yet, Swivel will be automatically comparing your data to other data sets in the background, suggesting possible correlations to you that you may never have noticed.
Academic types are going to go nuts over this. I spent a summer in college running regression analysis models on economic data. Being able to simply upload data to Swivel and then begin to slice and dice the data would have saved a lot of time. And being able to compare our data to what others were doing in related fields could have yielded results that we would never have aimed for. Big companies, small companies, think tanks and non-classified government organizations are going to be similarly dazzled.
Swivel is putting significant computing power behind the scenes to run the data analysis. “We use farms of powerful computers and algorithms at the Swivel data centers to transform a lonely grid of numbers and letters into hundreds – sometimes thousands – of graphs that can be explored and compared with any other public data in Swivel.”
The possibilities seem endless. As do the deceptions. I wonder, e.g., how long it takes for people to start uploading fake data to fool competitors.
(Thanks to Pete Davias and Trey Ratcliff for the tip, and to Mike Arrington for the nice write-up.)