Distributed Multi-contextual Ontology Evolution – A Step Towards Semantic Autonomy
In today’s world there is a need for knowledge infrastructures that can support several autonomous knowledge bases all using different ontologies and constantly adapting these to their changing local needs. Moreover, these different knowledge bases are expressing their unique points of view and constitute different local contexts. At the same time interoperability is needed in order to connect these semantically dispersed knowledge bases, and we formalized this as a type of consistency. Both these aspects are included in our definition of semantic autonomy. We present a layered framework that shows how to design a scalable system having this property. In our approach both ontology and mapping evolution take place, at the same time as the whole system is kept coherent using lightweight methods for maintaining global consistency. However, in order to achieve this several restrictions are necessary and the logical language used by the individual ontologies is kept simple. Finally, we present some experimental results that demonstrate the scalability of our approach.
KeywordsLocal Context Knowledge Source Ontology Evolution Ontology Mapping Framework Mechanism
Unable to display preview. Download preview PDF.
- 1.Bonifacio, M., Cuel, R., Mameli, G., Nori, M.: A Peer-to-Peer Architecture for Distributed Knowledge Management. In: Proceedings of the 3rd International Symposium on Multi-Agent Systems, Large Complex Systems, and E-Businesses (MALCEB 2002) (2002)Google Scholar
- 2.Zurawski, M.: Towards a context-sensitive distributed knowledge management system for the knowledge organization. In: Motta, E., Shadbolt, N.R., Stutt, A., Gibbins, N. (eds.) EKAW 2004. LNCS (LNAI), vol. 3257. Springer, Heidelberg (2004)Google Scholar
- 3.Froehner, T., Nickles, M., Weiß, G.: Towards modeling the social layer of emergent knowledge using open ontologies. In: ECAI Workshop on Agent-Mediated Knowledge Management (AMKM, Workshop Notes pp. 10–19) (2004)Google Scholar
- 6.Zurawski, M.: Reasoning about multi-contextual ontology evolution. In: The First International Workshop on Context and Ontologies: Theories, Practice and Applications, The Twentieth National Conference on Artificial Intelligence (AAAI 2005), July 9-13, Pittsburgh, PA, USA, (2005)Google Scholar
- 8.Heflin, J., Hendler, J.: Dynamic Ontologies on the Web, In: Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI 2000). AAAI/MIT Press, Menlo Park (2000) Google Scholar
- 13.Euzenat, J.: Corporate Memory through Cooperative Creation of Knowledge Base Systems and Hyper-Documents. In: Proc. of Knowledge Acquisition Workshop (KAW 1996), Banff, Canada (1996)Google Scholar