  Information retrieval from distributed heterogeneous data sources remains a
challenging issue. As the number of data sources increases more intelligent
retrieval techniques, focusing on information content and semantics, are
required. Currently ontologies are being widely used for managing semantic
knowledge, especially in the field of bioinformatics. In this paper we describe
an ontology assisted system that allows users to query distributed
heterogeneous data sources by hiding details like location, information
structure, access pattern and semantic structure of the data. Our goal is to
provide an integrated view on biomedical information sources for the
Health-e-Child project with the aim to overcome the lack of sufficient
semantic-based reformulation techniques for querying distributed data sources.
In particular, this paper examines the problem of query reformulation across
biomedical data sources, based on merged ontologies and the underlying
heterogeneous descriptions of the respective data sources.
