LinkedMDR: A Collective Knowledge Representation of a Heterogeneous Document Corpus

Abstract

The ever increasing need for extracting knowledge from heterogeneous data has become a major concern. This is particularly observed in many application domains where several actors, with different expertise, exchange a great amount of information at any stage of a large-scale project. In this paper, we propose LinkedMDR: a novel ontology for Linked Multimedia Document Representation that describes the knowledge of a heterogeneous document corpus in a semantic data network. LinkedMDR combines existing standards and introduces new components that handle the connections between these standards and augment their capabilities. It is generic and offers a pluggable layer that makes it adaptable to different domain-specific knowledge. Experiments conducted on construction projects show that LinkedMDR is applicable in real-world scenarios.