Demo for "Animating Research Collaboration Network using PIDs, Neo4j and Gephi"

Abstract

Understanding the research collaboration networks is the key to studying how science community operates. What we learned in 2020, at the time of the pandemic, highlighted how such networks evolve and transform disjointed scientific activities to a global movement working on the COVID-19 and the path to recovery. In this presentation, we use Research Graph COVID-19 cluster to demonstrate how PIDs' metadata can be used to animate this collaboration network. We will use ORCID and DOIs, and leverage the graph augmentation API to connected nodes and create a Neo4j graph database. The process is captured in an open Jupyter Notebook, enabling anyone to replicate the same process and hopefully expand on this work. Furthermore, we demonstrate how the combination of Neo4j and Gephi can be a powerful graph analytics and visualisation toolbox.