The Mega Meta Opportunity

Seth Godin provided a teaser on his blog today about the lurking opportunities with metadata (information about information) that I’d like to expand on:

“Many people and organizations are contributing to this mass of data, but few are taking advantage of the opportunity to collate it and present it to people who desperately need it. Think about how much needs to be sorted, compared, updated and presented to people who want to choose or learn or trade on it.”

Think of metadata as descriptive attributes about something. For example, if you right-click on a file taken from any digital camera it gives you information about that picture, including: date it was taken, file size, dimensions, camera model, camera settings, etc (all of this before you even open the picture to see what it’s of). You then import these files into your photo management software and add even more metadata: the location or event the picture was take at, who is in the photo, and maybe a caption. This incremental data allows you to do increasingly useful things with the photo, like: find all those pictures from last year’s canoe trip, or all the pictures with “dad” in them, or even just to organize and share them in a way that’s more enjoyable.

The same idea applies to essentially every bit of data generated anywhere; and when you view the world as data waiting to be made into something useful, there is a A LOT of it. Now, venture into the social media sphere where publically available data about millions of individuals and companies is generated every second of everyday. I’m referring to Twitter Tweets, Facebook status updates, Foursquare check ins, YouTube video uploads, etc. The question that Social Media pundits have been trying to answer is, “is any of it useful?” Personally I believe the answer is YES, and that it is one of the largest opportunities for innovation of this decade. The trick to making any of it actionable is to create meaningful descriptions of items at a very granular level, and then another layer of meaningful descriptions of the descriptions which enable people and organizations to make sense of it all (remember the digital picture analogy here).  The magic lies in creating the right analytical algorithms to get at those useful meanings. Whoever figures that out will not just "change the game", they’ll own it.