NoTube Project Collecting Data Social Web

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NoTube Workpackage 3 status update: a quick survey on the NoTube approach to gathering user data from the Social Web and representing them as a RDF graphs.

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NoTube Project Collecting Data Social Web

  1. 1. 3rd Project Meeting - 16/09/2009 @ Amsterdam The Beancounter: collecting data from the Social Web a ten-minutes long update on the WP3 status Davide Palmisano, Michele Minno and Michele Mostarda
  2. 2. User profiling and context models a (very) short ToC Where we are user data gathering in the Social Web the NoTube Beancounter: a general approach a simple demonstration Where we are going Linked Music Explorer and the Beancounter
  3. 3. User profiling and context models collecting data in the Social Web
  4. 4. User profiling and context models collecting data in the Social Web extremely high heterogeneity:
  5. 5. User profiling and context models collecting data in the Social Web extremely high heterogeneity: different data models
  6. 6. User profiling and context models collecting data in the Social Web extremely high heterogeneity: different data models syndications
  7. 7. User profiling and context models collecting data in the Social Web extremely high heterogeneity: different data models syndications auth technologies
  8. 8. User profiling and context models the Beancounter approach a possible dev process: choose a “social” application:
  9. 9. User profiling and context models the Beancounter approach a possible dev process: choose a “social” application: write code to:
  10. 10. User profiling and context models the Beancounter approach a possible dev process: choose a “social” application: write code to: implement the auth policy
  11. 11. User profiling and context models the Beancounter approach a possible dev process: choose a “social” application: write code to: implement the auth policy parse the response
  12. 12. User profiling and context models the Beancounter approach a possible dev process: choose a “social” application: write code to: implement the auth policy parse the response translate it in RDF and store it repeat for all the stuff in the Social Web
  13. 13. User profiling and context models the Beancounter approach a possible dev process: choose a “social” application: write code to: implement the auth policy parse the response translate it in RDF and store it repeat for all the stuff in the Social Web
  14. 14. User profiling and context models the Beancounter approach a possible dev process: choose a “social” application: write code to: implement the auth policy parse the response translate it in RDF and store it repeat for all the stuff in the Social Web
  15. 15. User profiling and context models the Beancounter approach a possible dev process: choose a “social” application: write code to: implement the auth policy parse the response translate it in RDF and store it repeat for all the stuff in the Social Web
  16. 16. User profiling and context models the Beancounter approach a possible dev process: choose a “social” application: write code to: implement the auth policy parse the response translate it in RDF and store it repeat for all the stuff in the Social Web
  17. 17. User profiling and context models the Beancounter approach a possible dev process: choose a “social” application: write code to: implement the auth policy parse the response translate it in RDF and store it repeat for all the stuff in the Social Web
  18. 18. a bit boring, isn’t it?
  19. 19. User profiling and context models the Beancounter approach instead, what I really want is: a framework that allows me to reduce at minimum the development effort a general architecture that embraces the heterogeneity allowing a decoupled and third party development
  20. 20. User profiling and context models the Beancounter approach
  21. 21. User profiling and context models
  22. 22. User profiling and context models the Beancounter architecture The NoTube Beancounter principles: a general architecture with hot- pluggable components (tubelets and modelets) an engine that allows to extract and aggregate users social data representing the data with RDF and storing them in a preferred triple store fully accessible with a set of REST APIs
  23. 23. User profiling and context models the Beancounter architecture
  24. 24. User profiling and context models the Beancounter architecture
  25. 25. User profiling and context models the Beancounter architecture
  26. 26. User profiling and context models the Beancounter architecture
  27. 27. User profiling and context models the Beancounter architecture
  28. 28. User profiling and context models the Beancounter architecture
  29. 29. User profiling and context models What you are going to see a quick demo around the following scenario: an instance of the Beancounter is running an administrator wrote a Tubelet for BrightKite and want to upload it to the Beancounter Davide wants to let the Beancounter storing his data from his Brightkite account
  30. 30. User profiling and context models Beancounter interactions How will Linked Music Explorer interact with an instance of the Beancounter?
  31. 31. User profiling and context models Beancounter interactions How will Linked Music Explorer interact with an instance of the Beancounter?
  32. 32. User profiling and context models Beancounter interactions How will Linked Music Explorer interact with an instance of the Beancounter?
  33. 33. User profiling and context models Further details architecture how the Beanconter interacts with other components? what kind of APIs? recommendation how to use the “beans” to provide content recommendation?
  34. 34. backup
  35. 35. Architecture sketch

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