Scientific Knowledge Graph

#artificialintelligence 

In the last decade, we experienced an urgent need for a flexible, context-sensitive, fine-grained, and machine-actionable representation of scholarly knowledge and corresponding infrastructures for knowledge curation, publishing and processing. Such technical infrastructures are becoming increasingly popular in representing scholarly knowledge as structured, interlinked, and semantically rich Scientific Knowledge Graphs (SKG). Knowledge graphs are large networks of entities and relationships, usually expressed in W3C standards such as OWL and RDF. SKGs focus on the scholarly domain and describe the actors (e.g., authors, organizations), the documents (e.g., publications, patents), and the research knowledge (e.g., research topics, tasks, technologies) in this space as well as their reciprocal relationships. These resources provide substantial benefits to researchers, companies, and policymakers by powering several data-driven services for navigating, analysing, and making sense of research dynamics.