  Using the knowledge discovery framework, it is possible to explore object
databases and extract groups of objects with highly heterogeneous movement
behavior by efficiently integrating a priori knowledge through interacting with
the framework. The whole process is modular expandable and is therefore
adaptive to any problem formulation. Further, the flexible use of different
information allocation processes reveal a great potential to efficiently
incorporate the a priori knowledge of different users in different ways.
Therefore, the stepwise knowledge discovery process embedded in the knowledge
discovery framework is described in detail to point out the flexibility of such
a system incorporating object databases from different applications. The
described framework can be used to gain knowledge out of object databases in
many different fields. This knowledge can be used to gain further insights and
improve the understanding of underlying phenomena. The functionality of the
proposed framework is exemplarily demonstrated using a benchmark database based
on real biological object data.
