Integration of the DOLCE top-level ontology into the OntoSpec methodology

Computer Science – Artificial Intelligence

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

This report describes a new version of the OntoSpec methodology for ontology building. Defined by the LaRIA Knowledge Engineering Team (University of Picardie Jules Verne, Amiens, France), OntoSpec aims at helping builders to model ontological knowledge (upstream of formal representation). The methodology relies on a set of rigorously-defined modelling primitives and principles. Its application leads to the elaboration of a semi-informal ontology, which is independent of knowledge representation languages. We recently enriched the OntoSpec methodology by endowing it with a new resource, the DOLCE top-level ontology defined at the LOA (IST-CNR, Trento, Italy). The goal of this integration is to provide modellers with additional help in structuring application ontologies, while maintaining independence vis-\`{a}-vis formal representation languages. In this report, we first provide an overview of the OntoSpec methodology's general principles and then describe the DOLCE re-engineering process. A complete version of DOLCE-OS (i.e. a specification of DOLCE in the semi-informal OntoSpec language) is presented in an appendix.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Integration of the DOLCE top-level ontology into the OntoSpec methodology does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Integration of the DOLCE top-level ontology into the OntoSpec methodology, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Integration of the DOLCE top-level ontology into the OntoSpec methodology will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-193779

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.