COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature
Table 1. COVID-19 Knowledge Graph entity and relations.
['[BOLD] Entity Type Papers', '[BOLD] Count 42,220', '[BOLD] Relation Type authored_by', '[BOLD] Count 240,624']
Information on what these entities represent, their attributes, and how they are created follows. Here we defined all relation types. The ∼42k paper entities have on average 2.3 outgoing topic relations, 64.9 outgoing relations to concepts, 5.7 outgoing relations to authors and 3.2 outgoing citation relations. Furthermore, ∼29k paper entities have at least one outgoing citation relation to another paper, ∼18k have at least one incoming citation relation from another paper, ∼14.6k have at least one incoming and outgoing citation relation, and ∼9.7k have neither an incoming nor outgoing citation relation. The 163k author entities have on average 0.75 outgoing relations to institutions indicating not all authors have institution information in the data. When considering an undirected version of the graph, there are 109 connected components with the diameter of the largest connected component (CC) equaling 12 entities that indicates one large CC contains 99% of relations and entities, while the diameter (12) indicates the CKG is dense. We observe that the greatest change in degree distribution comes from the sub-graph without concept relations, exemplifying that concepts form key links in the graph.