Ontology understanding without tears: The summarization approach

Given the explosive growth in both data size and schema complexity, data sources are becoming increasingly difficult to use and comprehend. Summarization aspires to produce an abridged version of the original data source highlighting its most representative concepts. In this paper, we present an advanced version of the RDF Digest, a novel platform that automatically produces and visualizes high quality summaries of RDF/S Knowledge Bases (KBs). A summary is a valid RDFS graph that includes the most representative concepts of the schema, adapted to the corresponding instances. To construct this graph our algorithm exploits the semantics, the structure of the schema and the distribution of the corresponding data/instances to initially identify the most important nodes. Then we explore how to select the edges connecting these nodes by maximizing either locally or globally the importance of the selected edges. The performed evaluation demonstrates the benefits of our approach and the considerable advantages gained. Furthermore, we present our first steps into enabling summary exploration through extensible summaries.