BioNav: An Ontology-Based Framework to Discover Semantic Links in the Cloud of Linked Data

Abstract

We demonstrate BioNav, a system to efficiently discover potential novel associations between drugs and diseases by implementing Literature-Based Discovery techniques. BioNav exploits the wealth of the Cloud of Linked Data and combines the power of ontologies and existing ranking techniques, to support discovery requests. We discuss the formalization of a discovery request as a link-analysis and authority-based problem, and show that the top ranked target objects are in correspondence with the potential novel discoveries identified by existing approaches. We demonstrate how by exploiting properties of the ranking metrics, BioNav provides an efficient solution to the link discovery problem.