Publishing Attention Data

26. December 2007 – 20:51 by Carsten Pötter

Attention Data

While surfing the web we leave traces, some unintentionally, some intentionally. Sometimes we are aware of them, sometimes we’re not. Unintentional traces (often they are even unavoidable by the average, non-tech savvy surfer) are cookies which can be read by ad services, IP addresses logged by websites, and much more. Intentional traces are blog posts, Twitter messages, songs we listen to and send to Last.fm, bookmarks, photos and videos shared on the web, events we attend by posting them to Upcoming or Wevent,… That’s our attention data.

APML or How to Use Attention Data

The data is there but what can we do with it? We can publish it. The idea of publishing attention data is not a brand new one, though. Lifestreams are an opportunity to do that. However if you have a closer look at the data it is quite obvious that it is valuable. It is reflecting a lot of what we do and especially what we like. But is there a way to share it and even value it?

apml Actually APML is doing just that; it means Attention Profiling Markup Language. Recently it has gained some more attention as people have a go at it. Admittedly there are not much use cases yet.

APML could be used for commercial purposes, e.g. I make it available to an online shop so that I am offered products that fit my interests. Of course, there has to be a possibility to block further use of that data if I don’t want to share it anymore. Another use case could be social networks; I will see users who share similar interests. I am confident, though, that APML will gain some more popularity in 2008 as it lets users control their data and complements efforts like DiSo; more products and use cases will follow then.

For further reading: introduction, plugins, applications:

No related posts.

Sorry, comments for this entry are closed at this time.