Scientists love to publish their work. As a result, important insights can be gleaned from scientific publications about who is working on what, for what purpose, an with what result. Scientific publication analysis has thus long been an important tool of scientific intelligence. 

The purpose of this project is to develop tools and workflows that enable bulk classification and analysis of scientific publications to identify new insight. The project uses APIs to bulk collect scientific publication information. It also involves the training of machine learning text classifiers and the use of NLP tools to extract data from relevant publications. 

This project is also examining tools for large scale analysis of academic publication data, such as Graph databases. The project is also examining tools for academic paper visualization, including tools such as Vosviewer and custom-developed visualization tools.