On Constructing Enterprise Knowledge Graphs Under Quality and Availability Constraints

Matthew Kujawinski, Christophe Guéret, Chandan Kumar, Brennan Woods, Pavel Klinov, Evren Sirin

Abstract: Knowledge graph technologies have proven their applicability and usefulness to integrate data silos and answer questions spanning over the different sources. However the integration of data can pose some risks and challenges (security, audit needs, quality control, ...). In this paper we abstract from two client use-cases, one in the banking domain and one in the pharmaceutical domain, to highlight those risks/challenges and propose a generic approach to address them. This approach leverages Semantic web technologies and is implemented using Stardog.