Visual Query Languages

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 because the social data are often quite large and assembled from a large number of different sources and because of the lack of structure information like ontologies. 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 be used. Furthermore, our system also supports a number of other functionalities, for example, precise suggestions to extend and refine existing queries. An online demonstration of our VQS is publicly available at http://www.ifis.uni-luebeck.de/index.php?id=luposdate-demo.