Attention Data

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Attention is time spent interacting with someone or something. Attention data is a digital record that describes the time spent interacting with someone or something. (

Benefits of Attention Data?


"How is value created using attention data? As I see it, there are at least six different flavors:

  • Personal value - improved user experience and productivity
  • Network value - use your network to learn and discover, build relationships and strengthen friendships
  • Enterprise value - optimize the use of available resources within the enterprise including people and their competencies
  • Community value - expand your social network and discover outside the limits of your existing social network
  • Consumer value - better customer service through personalization and recommendations
  • Global value - smarter search and better relevance in online search."


Continuous data vs. Schema data

Joe Reger at

"When you start datablogging (see Personal Data Streams you quickly realize that the things you track fall into one of two camps:

1) Continuous data

2) Schema data

An example of continuous data is a Body Weight Log. If you make a Body Weight Log entry every day they all track one thing, body weight, over time. You build a continuous history of that one thing. You can chart and graph it, relate it to other things, use it as a benchmark, etc.

An example of schema data is a Movie Review Log. If you make a Movie Review Log entry every day they all track separate things of the same type... they're all movies but never the same movie. Over time you build a collection of movie reviews.

The role of continuous data is to define your identity. It helps you track things that you do over time. How far you ran last week and how far you ran this week. How much you weighed in 1997 and how much you weigh today.

An interesting common-sense outcome of this is that identity has velocity. People change over time. You can't capture a person in a single static profile. You have to look at where they've been.

The role of schema data is to define your place in the group... the group being whatever social network, blogosphere or society you define yourself as being part of. When you review a movie and give it a 7 of 10 you then see that the rest of your group gave it an 3 of 10. Suddenly you see where you stand with the group.

The challenge of finding value from schema data involves critical mass. You have to have enough people tracking the things you're tracking to get a network effect that allows you to properly define your place in the group.

The Structured Blogging effort and sites like Microformats seem more focused on schema data. They're trying to incite a critical mass of data so that people can experience social network effects. Most of their formats are intended to allow many different people to provide data on the same thing... i.e. the same movie, the same restaurant, the same song." (

More Information

See our entries on Attention, Lifelogging and Personal Data Streams