Paperista considers the problem of visualizing and exploring a dataset about research publications from the two fields of technology-enhanced learning: Learning Analytics (LA) and Educational Data Mining (EDM). Our approach is based on semantic annotation that associates publications from the dataset with Wikipedia topics.

As a visualization and exploration tool, Paperista 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.

The Paperista system consists of a Web application and a server application that provides RESTful API for communicating with the dataset. The Web-based visualization is written in D3.js.

Paperista was created as a collaboration between University of Belgrade's Good Old AI Lab and the Uzrok Studio, an interaction design and film production studio founded and ran by Srđan Keča, Bojan Franzee Brankov, Luka Knežević-Strika, Jovan Vesić, and me.