  We introduce GrapAL (Graph database of Academic Literature), a versatile tool
for exploring and investigating a knowledge base of scientific literature, that
was semi-automatically constructed using NLP methods. GrapAL satisfies a
variety of use cases and information needs requested by researchers. At the
core of GrapAL is a Neo4j graph database with an intuitive schema and a simple
query language. In this paper, we describe the basic elements of GrapAL, how to
use it, and several use cases such as finding experts on a given topic for peer
reviewing, discovering indirect connections between biomedical entities and
computing citation-based metrics. We open source the demo code to help other
researchers develop applications that build on GrapAL.
