Visual query system for analyzing social semantic web

Abstract

The social web is becoming increasingly popular and important, because it creates the collective intelligence, which can produce more value than the sum of individuals. The social web uses the Semantic Web technology RDF to describe the social data in a machine-readable way. RDF query languages play certainly an important role in the social data analysis for extracting the collective intelligence. However, constructing such queries is not trivial since the social data is often quite large and assembled from a large number of different sources. In order to solve these challenges, we develop a Visual Query System (VQS) for helping the analysts of social data and other semantic data to formulate such queries easily and exactly. In this VQS, we suggest a condensed data view, a browser-like query creation system for absolute beginners and a Visual Query Language (VQL) for beginners and experienced users. Using the browser-like query creation or the VQL, the analysts of social data and other semantic data can construct queries with no or little syntax knowledge; using the condensed view, they can determine easily what queries should to be used. Furthermore, our system also supports precise suggestions to extend and refine existing queries.