Smajic, AmelPreiner, ReinholdComino Trinidad, MarcMancinelli, ClaudioMaggioli, FilippoRomanengo, ChiaraCabiddu, DanielaGiorgi, Daniela2025-11-212025-11-212025978-3-03868-296-72617-4855https://doi.org/10.2312/stag.20251320https://diglib.eg.org/handle/10.2312/stag20251320We introduce Topographic Lifeline Maps (TLMs), a visualization technique that combines a network of lifelines with topographic time maps to present genealogical graphs with both temporal detail and structural clarity. In TLMs, each individual's life is represented as a continuous curve that encodes birth, life events, and death in chronological order, while couples are depicted as parallel, merged lifelines. The layout is computed by a hybrid force model combining repulsion, temporally scaled springs, curvature-straightening, and octilinearization forces. Temporal interpretability is further enhanced through age-aware color encodings, with uncertain or missing dates distinguished visually to guide genealogical research. We demonstrate the expressiveness of TLMs on a large real-world dataset, illustrating diverse family stories, lifespans, and relational structures. A comparative user study against Topographic Attribute Maps (TAMs) shows that, while task performance is similar, participants consistently find TLMs more helpful across all analysis tasks. Our results highlight how mathematical layout formulations can advance genealogical visualization and suggest broader applicability to temporal-relational data beyond genealogy.Attribution 4.0 International LicenseCCS Concepts: Human-centered computing → Information visualization; Graph drawingsHuman centered computing → Information visualizationGraph drawings10.2312/stag.2025132012 pages