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Instance assisted ontology alignment for digital museums

It is desirable to the distribute data and knowledge of a huge amount of cultural heritage and to make them available readily to people, but the distributed, heterogeneous and autonomous nature of the databases of digital museums gives rise to the challenge of achieving the best retrieval results in cross-system searching. To make this difficult task tractable, we analyze semantic heterogeneities among these data sources and describe an instance based approach to accomplishing soundness and completeness preserving ontology alignment by using the information flow theory.