Knowledge Management and Acquisition in Digital Repositories - A Semantic Web Perspective

Information management, description and discovery, as they are today implemented in digital repositories and digital libraries systems, can surely benefit from the stack of Semantic Web technologies. Most importantly, the ability to infer implied information over declared facts and assertions, based on their rich descriptions and associations, can span new possibilities in how stored assets can be accessed, searched and discovered. In this paper we propose a process and implementation that provides for inference-based knowledge discovery, retrieval and navigation on top of digital repositories, based on existing metadata and other semi-structured information. We show that it is possible to produce added-value and meaningful results even when existing descriptions are only flatly organized and we achieve this with little manual intervention. Our work and results are based on real-world data and applied on the official University of Patras institutional repository that is based on DSpace.