Increasing the Productivity of Scholarship: The Case for Knowledge Graphs

Over the past several years, we have seen an explosion in the number of tools and services that enable scholars to improve their personal productivity whether it is socially enabled reference managers or cloud-hosted experimental environments. However, we have yet to see a step-change in the productivity of the system of scholarship as a whole. While there are certainly broader social reasons for this, in this talk I argue that we are just now at a technical position to create radical change in how scholarship is performed. Specifically, I will discuss how recent advances in machine reading, developments in open data and explicit social networks, can be used to create scholarly knowledge graphs. These graphs can connect the underlying intellectual corpus with ongoing discourse allowing the development of algorithms that hypothesize, filter and reflect alongside humans.