Abstraction of Representation for Interoperation

ion of Representation for Interoperation David A. Maluf and Gio Wiederhold Department of Computer Science Stanford University Stanford, CA 94305 Abstract. When combining data from distinct sources, there is a need to share meta-data and other knowledge about various source domains. Due to semantic inconsistencies, problems arise when combining knowledge across domains and the knowledge is simply merged. Also, knowledge that is irrelevant to the task of interoperation will be included, making the result unnecessarily complex. An algebra over ontologies has been When combining data from distinct sources, there is a need to share meta-data and other knowledge about various source domains. Due to semantic inconsistencies, problems arise when combining knowledge across domains and the knowledge is simply merged. Also, knowledge that is irrelevant to the task of interoperation will be included, making the result unnecessarily complex. An algebra over ontologies has been proposed to support disciplined manipulation of domain knowledge resources. However, if one tries to interoperate directly with the knowledge bases, semantic problems arise due to heterogeneity of representations. This heterogeneity problem can be eliminated by using an intermediate model that controls the knowledge translation from a source knowledge base. The intermediate model we have developed is based on the concept of abstract knowledge representation and has two components: a modeling behavior which separates the knowledge from its implementation, and a performative behavior which establishes context abstraction rules