Ontology-based modelling is becoming increasingly important in the design of complex knowledge management applications. However, many problems related to large-scale ontology development, deployment and collaborative maintenance of related metadata still remain to be solved. Making online modifications to an ontology whose concepts are simultaneously being used for metadata generation may potentially disrupt metadata semantics and even introduce inconsistencies. In this paper we analyzed and classified operations on ontology according to their impact on metadata. The approach is aimed at environments (like our own Knowledge Hub) relying on a relational database for storing ontologies and metadata assertions and it is based on the use of database triggers for automating metadata maintenance.
Managing ontology evolution via relational constraints / P. Ceravolo, A. Corallo, G. Elia, A. Zilli - In: Knowledge-based intelligent information and engineering systems : 8. international conference, KES 2004 : Wellington, New Zealand, september 20-25, 2004 : proceedings. 3. / [a cura di] M.G. Negoita, R.J. Howlett, L.C. Jain. - Berlin : Springer, 2004. - ISBN 9783540232056. - pp. 335-341 (( Intervento presentato al 8. convegno International Conference on Knowledge-Based Intelligent Electronic Systems (KES) tenutosi a Wellington nel 2004.
Managing ontology evolution via relational constraints
P. CeravoloPrimo
;
2004
Abstract
Ontology-based modelling is becoming increasingly important in the design of complex knowledge management applications. However, many problems related to large-scale ontology development, deployment and collaborative maintenance of related metadata still remain to be solved. Making online modifications to an ontology whose concepts are simultaneously being used for metadata generation may potentially disrupt metadata semantics and even introduce inconsistencies. In this paper we analyzed and classified operations on ontology according to their impact on metadata. The approach is aimed at environments (like our own Knowledge Hub) relying on a relational database for storing ontologies and metadata assertions and it is based on the use of database triggers for automating metadata maintenance.
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