Distributed multi-contextual ontology evolution - A step towards semantic autonomy

Abstract

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. © Springer-Verlag Berlin Heidelberg 2006.