WWDC 2013 and the Web Squared

So I watched the livestream of the 2013 WWDC keynote last Tuesday. I found it very inspiring and it actually motivated me to update my Mac to Mountain Lion, in order to be able to download the iBook Authoring app. Talk about marketing huh.

One of the things that struck me in that keynote is that the theoretical underpinning of the new version of the iOS 7 Photos feature is very Web Squared (Web2). iOS 7 Photos is able to automatically manage and organise your pictures in different categories (Collections, Moments, and Years), based on the time and place data tags. In other (non-technical) words: the camera remembers where and when you took the picture, and sorts the images accordingly, creating smart groups. The idea being that it will organise your pictures for you. So for instance, it will automatically group together all those pictures from that weekend in Paris last winter, because it knows the photos were taken in that place and at that time. You don’t have to go into your machine and do it yourself. Let’s face it, who has the time or the energy to organise photos? How many untagged, unnamed, disorganised pictures do you have in your machine/s?

What I found interesting about iOS 7 is that it was so close to one of the best reads I’ve had in a long while: Tim O’Reilly & John Battelle‘s Web2. The basic idea behind it is that everything that we do with machines casts an information shadow. Just think of your own information shadow in your favourite social network. Consider all the information about you that you generate via your Twitter account, for instance. And that is only one fraction of your information shadow in cyberspace. Let’s follow with the example of Photos: every time you take a picture with your smartphone, the information shadow it casts consists of (among other things) the place and the time. Indeed, when I re-read the WebWhite Paper whilst preparing this post, I realised that O’Reilly and Battelle had literally pointed in this direction already in 2009:

“Consider geotagging of photos. Initially, users taught their computers the association between photos and locations by tagging them. When cameras know where they are, every photo will be geotagged, with far greater precision than the humans are likely to provide”

In a way, the basic day-to-day idea that is so appealing about the Web2 is that machines work for us, in quite a natural, almost organic way, adapting to our movements and using the information we generate to make our own lives easier. The distance between the real world and the virtual world Web is shorter than ever: the world and Web are becoming a continuum. The key concept behind Web2 is that, finally, the Web meets the world. It is the natural evolution of the Web 2.0, its missing link.

To summarise all this, I’ll leave you with the beautiful equation created by O’Reilly & Battelle:

Web 2.0 + World = Web2