Interconnection and Alignment of Semantic Representations of Various Aspects of a Problem Domain - ¡°Semantic Heterogeneity Resolution¡±in federated databases by Seongwook Youn

A key aspect of interoperation among data-intensive systems involves the mediation of metadata and ontologies across database boundaries. One way to achieve such mediation between a local database and a remote database is to fold remote metadata into the local metadata, thereby creating a common platform through which information sharing and exchange becomes possible. Schema implantation and semantic evolution, our approach to the metadata folding problem, is a partial database integration scheme in which remote and local meta-data are integrated in a stepwise manner over time. We introduce metadata implantation and stepwise evolution techniques to inter-relate database elements in different databases, and to resolve conflicts on the structure and semantics of database elements (classes, attributes, and individual instances). We employ a semantically rich canonical data model, and an incremental integration and semantic heterogeneity resolution scheme. In our approach, relationships between local and remote information units are determined whenever enough knowledge about their semantics is acquired. The metadata folding problem is solved by implanting remote database elements into the local database, a process that imports remote database elements into the local database environment, hypothesizes the relevance of local and remote classes, and customizes the organization of remote metadata. We have implemented a prototype system and demonstrated its use in an experimental neuroscience environment.

A coorperative federated database system (CFDBS) is an information sharing environment in which units of information to be shared are substantially structured, and participants are actively involved in information sharing activities. We focus on the problem of building a common ontology for the purpose of information sharing in the CFDBS context. We introduce the concept and mechanism of the dynamic classificational ontology (DCO), which is a collection of concepts and inter-relationships to describe and classify information units exported by participating information providers; a DCO contains top-level knowledge about exported information units, along with knowledge for classification. By contrast with fixed hierarchical classifications, the DCO builds domain-specific, dynamically changing classification schemes. Information providers contribute to the DCO when information units are exported, and the current knowledge in the DCO is in turn utilized to assist information sharing activities. At the cost of information providers¡¯ cooperative efforts, this approach supports effective information sharing in the CFDBS environment.

Top level view of a cooperative federated database system