Harvesting Web Semantics Augmented with Social Annotations

Abstract. The amount of information on the web is constantly growing causing an erosion of its usefulness through information overload. Semantic Web copes with this erosion by creating a web in which information is interlinked and ef-fectively queried. But how to transform the web information into semantically interlinked metadata? Currently there is no convincing solution to this problem; a number of methods for providing/acquiring semantics were created but none of them is widely adopted. Additionally, a lot of semantics is delivered by the online communities in form of tags; there is no standard way to utilise this information either. In this paper we introduce a standard process of harvesting the web semantics. The process employs existing methods to collect or acquire data from web re-sources; it also enriches the gathered information with semantics from social annotations. IKHarvester is a prototype that implements this process to gather as much semantics as possible from the given source. As a result IKHarvester creates and delivers interlinked, semantic data enriched with community annota-tions, accessible to other applications