TY - JOUR
T1 - GenealogyVis
T2 - A System for Visual Analysis of Multidimensional Genealogical Data
AU - Liu, Yuhua
AU - Dai, Sicheng
AU - Wang, Changbo
AU - Zhou, Zhiguang
AU - Qu, Huamin
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2017/12
Y1 - 2017/12
N2 - The study of genealogy is an increasingly popular activity pursued by millions of people, ranging from hobbyists to professional researchers. Such genealogical datasets provide a great opportunity for social science analysts, historians, and the public to study a wide variety of topics in demography, family and household, kinship, stratification, and health. Nevertheless, the large scale and characteristics of the data such as hierarchical, spatiotemporal, and multidimensional also pose special challenges for effective data analysis. In this paper, we introduce GenealogyVis, a visual analytic system to analyze family history and evolution by using the China Multigenerational Panel Dataset-Liaoning, which has more than 1.5 million observations and provides socioeconomic, demographic, and other information for more than 260 000 residents, and further enable users to explore the correlation between the development of families and the social context of environments, economics, policies, and so on. This system includes five main linked views: the Scatter-plot View to provide an overview of the data and further explore the correlation analysis, the Tree View to show the family structure and details for individuals, the Migration View to present the genealogical migratory behaviors, the Matrix View to analyze the reproduction pattern between two generations, and the Stream View to show various statistical information such as demographic information and temporal information. A design study was conducted with a research group led by a domain expert of humanities and social sciences in an iterative manner over half a year. Several in-depth case studies, involving the research group, are described to demonstrate the usefulness of GenealogyVis and discuss new findings.
AB - The study of genealogy is an increasingly popular activity pursued by millions of people, ranging from hobbyists to professional researchers. Such genealogical datasets provide a great opportunity for social science analysts, historians, and the public to study a wide variety of topics in demography, family and household, kinship, stratification, and health. Nevertheless, the large scale and characteristics of the data such as hierarchical, spatiotemporal, and multidimensional also pose special challenges for effective data analysis. In this paper, we introduce GenealogyVis, a visual analytic system to analyze family history and evolution by using the China Multigenerational Panel Dataset-Liaoning, which has more than 1.5 million observations and provides socioeconomic, demographic, and other information for more than 260 000 residents, and further enable users to explore the correlation between the development of families and the social context of environments, economics, policies, and so on. This system includes five main linked views: the Scatter-plot View to provide an overview of the data and further explore the correlation analysis, the Tree View to show the family structure and details for individuals, the Migration View to present the genealogical migratory behaviors, the Matrix View to analyze the reproduction pattern between two generations, and the Stream View to show various statistical information such as demographic information and temporal information. A design study was conducted with a research group led by a domain expert of humanities and social sciences in an iterative manner over half a year. Several in-depth case studies, involving the research group, are described to demonstrate the usefulness of GenealogyVis and discuss new findings.
KW - Family trees
KW - genealogy visualization
KW - interaction
UR - https://www.scopus.com/pages/publications/85018962092
U2 - 10.1109/THMS.2017.2693236
DO - 10.1109/THMS.2017.2693236
M3 - 文章
AN - SCOPUS:85018962092
SN - 2168-2291
VL - 47
SP - 873
EP - 885
JO - IEEE Transactions on Human-Machine Systems
JF - IEEE Transactions on Human-Machine Systems
IS - 6
M1 - 7909028
ER -