Department of Computer, Control and Management Engineering

Ontologies are an important resource for knowledge representation. Their structure can be complex due to role relations between several concepts, distinct attributes, and different instances. In this paper, we discuss a Visual Analytics solution, relying on the use of multiple coordinated views for exploring different ontology aspects and a novel use of the degree of interest (DoI) suppression technique to reduce the complexity of the ontology visual representation. Visual Analytics facilitates the understanding of the domain and tasks represented by ontologies, thus allowing to carry out exploratory analysis to optimize the comprehension of data semantics including non-explicit relationships between data. Through the DoI technique, we place the main concept in focus, distinguishing it from the unnecessary information and facilitating the analysis and understanding of correlated data. We evaluated all the devised solutions, and the results reinforce the importance of providing visualization and analysis techniques dedicated to the schema and instances levels of ontologies for the discovery of non-explicit information.