Attention Profiling Markup Language (APML), the standard for sharing attention profiles that I wrote about recently, has received a major boost today. The prominent RSS aggregator Newsgator has announced that it is implementing APML, while Engagd reports that a range of significant players are joining the APML working group, including social bookmarking site Ma.gnolia, feed reader Bloglines, online application provider Peepel, social recommendation tool Me.dium, and the semantic content platform Talis.
The diversity of the new participants in APML points to some of the value of the standard. Starting from the more obvious applications, APML can be implemented by any news aggregator or feed reader to provide personalized, relevant information to the user. Those aggregators that provide this extra level of value will be more useful. One of the most interesting emerging spaces at the moment is that of social browsing recommendations. I wrote a few months ago about Cluztr, a website that gathers complete data about everything that users do online, including every site that they click on and how long they spend there. One of the most valuable things that emerges is the ability to find what is most interesting to people with similar interest (or attention) profiles to yourself. Clearly appropriate security and boundaries to the use of the data are required, but given that, extremely personalized recommendations can be made. Me.dium provides a related service, overlaying the browsing recommendations with a social network that enables users to link to people with similar interest profiles.
There are a range of good explanations of APML available, with today’s coverage of the Newsgator announcement by Read/Write Web giving an overview of the situation, while articles by Marjolein Hoekstra on Basics of Attention Profiling and Elias Bizannes on Explaining APML: what it is and why you want it give clear and detailed insights into the standard.
The critical thing to understand here is that APML is a standards initiative, a proposal for an open standard to provide a foundation for attention-based applications. Given this was only launched a few months ago, the traction it is getting is very encouraging. Other similar initiatives in the past have not been as successful. I think the simplicity of APML, together with the diverse group of highly innovative technologists in the working group, are key factors in the great momentum so far. There are complementary initiatives around, such as AttentionTrust, however APML has the potential to provide a vital glue in the fabric. As I’ve written before, I think attention profiling is one of the key trends in the online world. If APML helps to coalesce activities in the space, this could take off and provide immense value to all of us drowning in information overload. I’ll be following this space, particularly in how the APML standard is being used in useful ways.