The course of history is inseparable from the actions of historical figures. From the perspective of contemporaneity, an important challenge is how to visualize large numbers of historical figures and their dynamic associations on a unified temporal scale. Yet existing large-scale data solutions often rely on aggregation strategies that diminish the visibility of key figures, while failing to provide smooth contextual transitions between overview and detail. Moreover, current approaches to representing inter-figure associations lack effective integration of the surrounding historical context. To address these challenges, we propose TimeScape, a large-scale biographical data exploration system supporting multi-resolution analysis. Anchored in absolute time, the system highlights the evolving dynamics of historical development. Through multi-level layouts, sampling, and semantic zooming, it enables efficient navigation of large-scale data, allowing users to move seamlessly between overview and detail and to "wander" freely across the historical landscape. The system further allows iterative switching of focal figures to explore concrete inter-personal associations, aligning them on the temporal axis so that these connections are grounded in traceable evidence and explicit context. Case studies and expert interviews demonstrate that TimeScape effectively supports multi-perspective understanding and exploration of large-scale biographical data, offering historians a new visualization pathway for research.
Ma et al. (Thu,) studied this question.