How Do Ancestral Traits Shape Family Trees Over Generations?

• Published in: IEEE transactions on visualization and computer graphics Vol. 24; no. 1; pp. 205 - 214
• Main Authors: Fu, Siwei, Dong, Hao, Cui, Weiwei, Zhao, Jian, Qu, Huamin
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Animation; Case depth; Complexity; Design study; Family trees; Historians; Iterative methods; Multiple tree visualization; Quantitative social science; Sankey diagram; Scalability; Sociology; Statistics; Visual analytics; Zooming
• ISSN: 1077-2626; 1941-0506
• DOI: 10.1109/TVCG.2017.2744080

Whether and how does the structure of family trees differ by ancestral traits over generations? This is a fundamental question regarding the structural heterogeneity of family trees for the multi-generational transmission research. However, previous work mostly focuses on parent-child scenarios due to the lack of proper tools to handle the complexity of extending the research to multi-generational processes. Through an iterative design study with social scientists and historians, we develop TreeEvo that assists users to generate and test empirical hypotheses for multi-generational research. TreeEvo summarizes and organizes family trees by structural features in a dynamic manner based on a traditional Sankey diagram. A pixel-based technique is further proposed to compactly encode trees with complex structures in each Sankey Node. Detailed information of trees is accessible through a space-efficient visualization with semantic zooming. Moreover, TreeEvo embeds Multinomial Logit Model (MLM) to examine statistical associations between tree structure and ancestral traits. We demonstrate the effectiveness and usefulness of TreeEvo through an in-depth case-study with domain experts using a real-world dataset (containing 54,128 family trees of 126,196 individuals).