Since elements of data sets can belong to more than one category, the categories overlap in various levels. In order to achieve a clear visualization for this kind of data the research partners use a layered network, enriched with various visual marks showing all details of the data. The proposed approach is universally applicable to analyze the evolution of categorical data, for instance, researcher’s fields of interest, the developer activities in a software project, or the changing market strategy of companies.

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.”

Agarwal, Shivam; Tkachev, Gleb; Wermelinger, Michel; Beck, Fabian: Visualizing Sets and Changes in Membership Using Layered Set Intersection Graphs. In: Proceedings of Vision, Modeling, and Visualization. 2020. doi:10.2312/vmv.20201189

Link to the Conference: Vision, Modeling, and Visualization (VMV) 2020