SizePairs: Achieving Stable and Balanced Temporal Treemaps using Hierarchical Size-based Paring - Han, Chang; Jo, Jaemin; Li, Anyi; Lee, Bongshin; Deussen, Oliver; Wang, Yunhai (IEEE Transactions on Visualization and Computer Graphics (VIS 2022), 2023)
We present SizePairs, a new technique to create stable and balanced treemap layouts that visualize values changing over time in hierarchical data. To achieve an overall high-quality result across all time steps in terms of stability and aspect ratio, SizePairs employs a new hierarchical size-based pairing algorithm that recursively pairs two nodes that complement their size changes over time and have similar sizes. SizePairs maximizes the visual quality and stability by optimizing the splitting orientation of each internal node and flipping leaf nodes, if necessary. We also present a comprehensive comparison of SizePairs against the state-of-the-art treemaps developed for visualizing time-dependent data. SizePairs outperforms existing techniques in both visual quality and stability, while being faster than the local moves technique.