Bridging the gap between data ontologies and process ontologiesDipl. Geogr. Christoph Rüther

Bridging the gap between data ontologies and process ontologies

Dipl. Geogr. Christoph Rüther

Institute for Geoinformatics, University of Münster

Robert-Koch-Str. 26-28, D-48149 Münster, Germany

ruether@ifgi.uni-muenster.de

Bridging the gap between data ontologies and process ontologiesDipl. Geogr. Christoph Rüther

Overview

Information Community Ontology

Presentation Ontology

Process OntologyDatabase Ontology

Bridging the gap between data ontologies and process ontologiesDipl. Geogr. Christoph Rüther

Research problem

• Different information communities (IC) have different perceptions of the real world

• Data models represent concepts, which may, or may not, conform to the perceptions in the information communities.

• Objective: to develop a mechanism to bind the perception of different ICs to the concepts represented in processes and in the database.

Bridging the gap between data ontologies and process ontologiesDipl. Geogr. Christoph Rüther

Example Problem

ATKIS Database

Transportation Planer Landscabe Ecologist

Bridging the gap between data ontologies and process ontologiesDipl. Geogr. Christoph Rüther

Research Question

What can a data provider do to support process ontologies ?

Bridging the gap between data ontologies and process ontologiesDipl. Geogr. Christoph Rüther

Approach

Develop functions which take objects from a database and produce objects according to a process ontology.

Bridging the gap between data ontologies and process ontologiesDipl. Geogr. Christoph Rüther

Approach Example

Roads

NameBoundingJunction

Attributes

transportation ontology

process ontology

process shortestPath (Node, Node, Graph)

Function Maps between these two Ontologies

Bridging the gap between data ontologies and process ontologiesDipl. Geogr. Christoph Rüther

Conclusion

• Most current research is focused on ontologies at the data level.

• Our research concentrates on the gap between data model and process model.

• We attempt to build ontologies supporting the processes of using data (e.g. network analysis).