Our recent research work titled “Visualizing Sets and Changes in Membership Using Layered Set Intersection Graphs” won the Best Paper Award at the Vision, Modeling, and Visualization (VMV) 2020 conference. The conference was held virtually together with the German Conference on Pattern Recognition (DAGM GCPR) and Visual Computing for Biology and Medicine (EG VCBM). The paper can be found here.

We propose a novel and general approach to visualize dynamically changing categories of data elements. Since elements can belong to more than one category, the categories overlap in various levels. We use a layered network for visualization, enriched with various visual marks showing all details of the data. The proposed approach is universally applicable to categorical data, for instance, can be used to analyze researcher’s field of interest, evolution of developer activities in a software project, changing market strategy of companies, etc.

The work was led by Shivam Agarwal and done in collaboration with colleagues from University of Stuttgart, Germany and Open University, UK. Project advisor Prof. Fabian Beck summarizes: “We have been working already for some time to make dynamic categorical data explorable. Now, this work, together with our also recently published approach, Set Streams, lays a foundation for a new way to visually analyze this kind of dynamic data.”