We present a novel approach to representing uncertain information in ontologies based on design patterns. We provide a brief description of our approach, present its use in case of fuzzy information and probabilistic information, and describe the possibility to model multiple types of uncertainty in a single ontology. We also shortly present an appropriate fuzzy reasoning tool and define a complex ontology architecture for well-founded handling of uncertain information.
fuzzy-type fi-instance
fi-instance-1 -f-value : float = 0.8 fi-type
One of major advantages of our modeling approach is that it enables us to model various kinds of uncertainty in same ontology at the same time. Using approach described above we can define well-founded architecture of ontology that fully supports handling uncertainty – Uncertainty Modeling Framework (UMF): crisp ontology is aligned to foundational ontology (i.e. DOLCE) while fuzzy and i.e. probabilistic ontology are based on appropriate patterns of UMF. Such architecture is modularized, so these parts of ontology are separated to independent modules. On top of these ontologies there can be number of different specialized reasoners operating (Fig. 2).
Uncertainty Modelling Framework
More information can be found in full paper draft6. M. Vacura, V. Sv´atek and N. Simou are supported by the EC under FP6, project K-Space (no.: FP6027026), and first two also by the Czech IGA VSE grant no.12/06. P. Smrˇz is supported by the EU FP6 project CARETAKER (no.: FP6-027231).