Abstract
Structured data and complex schemas are becoming the main way to represent the information many Digital Libraries provide, thus impacting the services they offer. When searching information among distributed Digital Libraries with heterogeneous schemas, the structured query with a given schema (the global or target schema) has to be transformed into a query over the schema of the digital library it will be submitted to (the source schema). Schema mappings define the rules for this query transformation. Schema matching is the problem of learning these mappings.In this paper we address the issue of automatically learning these mappings and transforming a structured query over the target schema into a new structured query over the source schema. We propose a simple and effective schema matching method based on the well known CORI selection algorithm and two ways of applying it. By evaluating the effectiveness of the obtained structured queries we show that the method works well in accessing distributed, heterogeneous digital libraries.
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