Semantic Sensor Networks 2011

The explosion in user-generated content (on the Social Web) published from mobile devices has seen microblog platforms like Twitter grow exponentially. Twitter is a microblogging platform founded in 2006, which by October 2010 had roughly 175m users and as of June 2011, Twitter processed 200m posts per day. Twitter data has been utilised to predict/report natural disasters, civil unrest, and media topics. Smartphones and other mobile devices contain an array of sensors but are under-utilised on the Social Web. In this paper, we propose a method for annotating microblog posts with multi-sensor data by representing it with ontologies such as SSN and SIOC. We present an alignment of these ontologies and outline an enhanced Twitter client that would allow users to enter an emergency mode where all or most of the available sensor data would be published as annotations to the users post, allowing relief organisations to use any data relevant.