Faceted Visual Exploration of Semantic Data

Tools for searching and interactively exploring the rapidly growing amount of semantically annotated data on the Web are still scarce and limited in their support of the users’ manifold goals and activities. In this paper we describe a method and a tool that allows humans to access and explore Semantic Web data more effectively, leveraging the specific characteristics of semantic data. The approach utilizes the concept of faceted search and combines it with a visualization that exploits the graph-based structure of linked semantic data. The facets are represented as nodes in a graph visualization and can be interactively added and removed by the users in order to produce individual search interfaces. This provides the possibility to generate interfaces with different levels of complexity that can search arbitrary domains accessible through the SPARQL query language. Even multiple and distantly connected facets can be integrated in the graph facilitating the access of information from different user-defined perspectives. This approach facilitates searching massive amounts of data with complex semantic relations, building highly complex search queries and supporting users who are not familiar with the Semantic Web.