Title: Knowledge Engineering for Hybrid Deductive Databases,
Abstract: Modern knowledge base systems frequently need to combine a collection of
databases in different formats: e.g., relational databases, XML databases, rule
bases, ontologies, etc. In the deductive database system DDBASE, we can manage
these different formats of knowledge and reason about them. Even the file
systems on different computers can be part of the knowledge base. Often, it is
necessary to handle different versions of a knowledge base. E.g., we might want
to find out common parts or differences of two versions of a relational
database.
We will examine the use of abstractions of rule bases by predicate dependency
and rule predicate graphs. Also the proof trees of derived atoms can help to
compare different versions of a rule base. Moreover, it might be possible to
have derivations joining rules with other formalisms of knowledge
representation.
Ontologies have shown their benefits in many applications of intelligent
systems, and there have been many proposals for rule languages compatible with
the semantic web stack, e.g., SWRL, the semantic web rule language. Recently,
ontologies are used in hybrid systems for specifying the provenance of the
different components.