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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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The Beancounter: collecting data from the
Social Web
Davide Palmisano, Michele Minno and Michele Mostarda
3rd Project Meeting - 16/09/2009 @ Amsterdam
a ten-minutes long update on the WP3 status
a (very) short ToC
User profiling and context models
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
collecting data in the Social Web
User profiling and context models
User profiling and context models
collecting data in the Social Web
extremely high heterogeneity:
User profiling and context models
collecting data in the Social Web
extremely high heterogeneity:
different data models
User profiling and context models
collecting data in the Social Web
extremely high heterogeneity:
different data models
syndications
extremely high heterogeneity:
different data models
syndications
auth technologies
User profiling and context models
collecting data in the Social Web
a possible dev process:
choose a “social” application:
User profiling and context models
the Beancounter approach
choose a “social” application:
write code to:
User profiling and context models
the Beancounter approach
a possible dev process:
choose a “social” application:
write code to:implement the auth policy
User profiling and context models
the Beancounter approach
a possible dev process:
choose a “social” application:
write code to:
parse the responseimplement the auth policy
User profiling and context models
the Beancounter approach
a possible dev process:
choose a “social” application:
write code to:
translate it in RDF and store it
repeat for all the stuff in the Social Web
parse the responseimplement the auth policy
User profiling and context models
the Beancounter approach
a possible dev process:
choose a “social” application:
write code to:
translate it in RDF and store it
repeat for all the stuff in the Social Web
parse the responseimplement the auth policy
User profiling and context models
the Beancounter approach
a possible dev process:
choose a “social” application:
write code to:
translate it in RDF and store it
repeat for all the stuff in the Social Web
parse the responseimplement the auth policy
User profiling and context models
the Beancounter approach
a possible dev process:
choose a “social” application:
write code to:
translate it in RDF and store it
repeat for all the stuff in the Social Web
parse the responseimplement the auth policy
User profiling and context models
the Beancounter approach
a possible dev process:
choose a “social” application:
write code to:
translate it in RDF and store it
repeat for all the stuff in the Social Web
parse the responseimplement the auth policy
User profiling and context models
the Beancounter approach
a possible dev process:
choose a “social” application:
write code to:
translate it in RDF and store it
repeat for all the stuff in the Social Web
parse the responseimplement the auth policy
User profiling and context models
the Beancounter approach
a possible dev process:
a bit boring, isn’t it?
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
User profiling and context models
the Beancounter approach
User profiling and context models
the Beancounter approach
User profiling and context models
The NoTube Beancounter principles:
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
a general architecture with hot-pluggable components (tubelets and modelets)
User profiling and context models
the Beancounter architecture
User profiling and context models
the Beancounter architecture
User profiling and context models
the Beancounter architecture
User profiling and context models
the Beancounter architecture
User profiling and context models
the Beancounter architecture
User profiling and context models
the Beancounter architecture
User profiling and context models
the Beancounter architecture
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
User profiling and context models
What you are going to see
How will Linked Music Explorer interact with an instance of the Beancounter?
User profiling and context models
Beancounter interactions
How will Linked Music Explorer interact with an instance of the Beancounter?
User profiling and context models
Beancounter interactions
How will Linked Music Explorer interact with an instance of the Beancounter?
User profiling and context models
Beancounter interactions
User profiling and context models
Further details
architecture
how the Beanconter interacts with other components?
recommendation
how to use the “beans” to provide content recommendation?
what kind of APIs?
backup
Architecture sketch
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