The Web 2.0 revolution has produced an explosion in social data that is fundamentally transforming business, politics, culture, and society in general. Using tools such as wikis, blogs, online forums, and social networking sites, users can now express their point of view, build relationships, and exchange ideas and multimedia content. Combined with portable electronic devices such as cameras and cell phones, these tools are enabling the citizen journalist who can report facts and events faster than traditional media outlets and government agencies.
One of the challenges posed by this explosion in social data is data portability between social networking sites. But the next biggest challenge will be the ability to harvest all that social data in order to extract actionable intelligence (e.g. a better understanding of consumer behavior or the events unfolding at a particular location). In addition, in a world where security has become the number one priority, various sensors from traffic cameras to satellite sensors are also collecting huge amounts of data. The integration of sensor data and social data offers new possibilities.
Those are the types of integration challenges that Semantic Web technologies are designed to solve. The SIOC (Semantically Interlinked Online Communities) Core ontology describes the structure and content of online community sites. A comprehensive list of SIOC tools is available at the SIOC Applications page. Using these tools, developers can export SIOC compliant RDF data from various data sources such as blogs, wikis, online forums, and social networking sites such as Twitter and Flickr. Once exported, the SIOC data can be crawled, aggregated, stored, indexed, browsed, and queried (using SPARQL) to answer interesting questions. Natural Language Processing (NLP) techniques can be used to facilitate entity extraction from user generated content.
SIOC leverages the FOAF ontology to describe the social graph on social networking sites. For example, this can offer deeper insights for marketers into how social recommendations affect consumer behavior.
One unique capability offered by Semantic Web technologies is the ability to infer new facts (inference) from explicit facts based on the use of an ontology (RDFS or OWL) or a set of rules expressed in a rule language such as the Semantic Web Rule Language (SWRL). Using constructs such as owl:sameAs or rdfs:seeAlso, it becomes easy to express the fact that two or more different web pages relate to the same resource (e.g. different profile pages of the same person on difference social networking sites). Linked Data principles can help in linking social data, therefore building bridges between the data islands that today's social networking sites represent.
SIOC compliant social data can be meshed up with other data sources such as sensor data to reveal very useful information about events related to logistics, public safety, or political unrest at a particular location for example. With the advent of GPS-enabled cameras and cell phones, temporal and spatial context can be added to better describe those events. The W3C Time OWL Ontology (OWL-Time) and the Basic Geo Vocabulary have been developed for that purpose.