Thesis full text (PDF) - Politecnico di Milano

additions and deletions. Its technique presented in [49] is implemented upon the tableau decision
procedure for consistency checking in DL languages. It offers debugging of a knowledge base
providing explanations for the cause of unsatisfiable concepts [50]. It has new optimization
techniques for DL reasoning in presence of nominals [51], and supports reasoning both with
XML Schema data types and user defined ones.
It is implemented in Java and it provides a variety of communication interfaces: command-line
access, implementation of DIG 1.1 interface, bindings for OWL API and Jena interfaces, its own
Java API, and a Web-based access. Examples of its usage in tools for ontology editing and
querying are found in Protegè 4.0 and SWOOP.
Besides the above standard reasoning tasks, Pellet offers (i) incremental update of the instance
base [52], (ii) debugging through assertions [53], (iii) optimization reasoning techniques in
presence of nominal [54], and (iv) reasoning both with XML Schema and user defined data
types. Test cases in [55] show that RacerPro generally performs better. However, frequent
updates in the assertions increase the Pellet overall performance with respect to the RacerPro
system, since RacerPro builds the concepts hierarchy from scratch.
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