Paperista: Visual exploration of semantically annotated research papers

Abstract

We consider the problem of visualizing and exploring a dataset about research publications from the fields of Learning Analytics (LA) and Educational Data Mining (EDM). Our approach is based on semantic annotation that associates publications from the dataset with Wikipedia topics. We present a visualization and exploration tool, called Paperista (www.uzrok.com/paperista), which presents these topics in the form of bubble and line charts. The tool provides multiple views, thus allowing users to observe and interact with topics, understand their evolution and relationships over time, and compare data originating from different research fields (i.e., LA and EDM). Moreover, user can explore papers to which the presented topics are related to, and make related Web searches to access the papers themselves.