ArhiNet – A Knowledge-Based System for Creating, Processing and Retrieving Archival eContent

Abstract

This paper addresses the problem of creating, processing and querying semantically enhanced eContent from archives and digital libraries. We present an analysis of the archival domain, resulting in the creation of an archival domain model and of a domain ontology core. Our system adds semantic mark-up to the historical documents content, thus enabling document and knowledge retrieval as response to natural language ontology-guided queries. The system functionality follows two main workflows: (i) semantically enhanced eContent generation and knowledge acquisition and (ii) knowledge processing and retrieval. Within the first workflow, the relevant domain information is extracted from documents written in natural languages, followed by semantic annotation and domain ontology population. In the second workflow, ontologically guided natural language queries trigger reasoning processes that provide relevant search results. The paper also discusses the transformation of the OWL domain ontology into a hierarchical data model, thus providing support for the efficient ontology processing.