Modelling text-fact-integration in digital libraries

Digital Libraries currently face the challenge of integrating many different types of research information (e.g. publications, primary data, expert‘s profiles, institutional profiles, project information etc.) according to their scientific users‘ needs. To date no general, integrated model for knowledge organization and retrieval in Digital Libraries exists. This causes the problem of structural and semantic heterogeneity due to the wide range of metadata standards, indexing vocabularies and indexing approaches used for different types of information. The research presented in this paper focuses on areas in which activities are being undertaken in the field of Digital Libraries in order to treat semantic interoperability problems. We present a model for the integrated retrieval of factual and textual data which combines multiple approaches to semantic interoperability und sets them into context. Embedded in the research cycle, traditional content indexing methods for publications meet the newer, but rarely used ontology-based approaches which seem to be better suited for representing complex information like the one contained in survey data. The benefits of our model are (1) easy re-use of available knowledge organisation systems and (2) reduced efforts for domain modelling with ontologies. (author's abstract