Storyline visualizations are a popular way of visualizing characters and their interactions over time: Characters are drawn as x-monotone curves and interactions are visualized through close proximity of the corresponding character curves in a vertical strip. Existing methods to generate storylines assume a total ordering of the interactions, although real-world data often do not contain such a total order. Instead, multiple interactions are often grouped into coarser time intervals such as years. We exploit this grouping property by introducing a new model called storylines with time intervals and present two methods to minimize the number of crossings and horizontal space usage. We then evaluate these algorithms on a small benchmark set to show their effectiveness.
@article{arxiv.2302.14213,
title = {Crossing Minimization in Time Interval Storylines},
author = {Alexander Dobler and Martin Nöllenburg and Daniel Stojanovic and Anaïs Villedieu and Jules Wulms},
journal= {arXiv preprint arXiv:2302.14213},
year = {2023}
}