Combining DAML+OIL, XSLT, and Probabilistic Logics for Uncertain Schema Mappings in MIND

When distributed, heterogeneous digital libraries have to be integrated, one of the crucial tasks is to map between different schemas. As schemas may have different granularities, and as schema attributes do not always match precisely, a general-purpose schema mapping approach requires support for uncertain mappings. In this paper we present one of the very few approaches for defining and using uncertain schema mappings. We combine different technologies like DAML+OIL, probabilistic Datalog (since DAML+OIL—as similar ontology languages—lacks rules) and XSLT for actually transforming queries and documents. This declarative approach is fully implemented in the project MIND (which develops methods for retrieval in networked multimedia digital libraries). However, as DAML+OIL lacks some important features, the proposed approach is only a stepping stone for an integrated solution.

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