Abstract

Data Visualizing is becoming an important research topic in computer science, and has received considerable attention in the last two decades. In several instances, visualization is a crucial step in order to easily access and properly understand the data. With it, the analysis and the decision making is a relatively easier task. In this thesis, we will focus on the visualization of the concept hierarchies by producing several geometric representations. The main tools used are the graphs where the concepts are represented by vertices and the edges represent the relationships between concepts. Our specific application is the development of a drawing system that interfaces with the description logic reasonner RACER . Unless there is no error in the ontology, the RACER system responds to the taxonomy queries correctly. The body of the response must contain information about a relational structure called a concept hierarchy. This information could be saved as a text file. In the first part of the thesis, we will present our system architecture and discuss its components then we will show how to collect the information about the concept hierarchy using the taxonomy query. We also describe methods for parsing hierarchies and the creation of an appropriate data structure that will be used by the set of algorithms we developed. The second part of the thesis contains the algorithms used to retrieve the properties of the concept hierarchy, as well as to study the specific structure of these hierarchies. It is well known that graph drawing in general is a very complex issue and, therefore, it is important that our approach in drawing takes into account the specificity of these graphs. We consider many aesthetic criteria that fit our specific application: the levels should be kept together as much as possible, the drawing area should be as small as possible, the number of crossings should be minimized, etc. Also, we will develop a decomposition technique that will be very useful in many instances.