  User-generated family trees are invaluable for constructing population-scale
family networks and studying population dynamics over many generations and far
into the past. Family trees contain information on individuals such as birth
and death places and years, and kinship ties, e.g., parent-child, spouse, and
sibling relationships. Such information about individuals in family trees makes
it possible to extract migration networks over time. Despite the recent
advances, existing spatial and temporal abstraction techniques for time-variant
flow data have limitations due to the lack of knowledge on the effect of
temporal partitioning on flow patterns. In this study, we extracted
state-to-state migration patterns over a period of 150 years between 1776 and
1926 from a cleaned, geocoded and connected family trees from Rootsweb.com. We
used birthplaces and birthyears of parents and children to extract
intergenerational migration flows between states. To reveal the temporal trends
of migration patterns, we evaluated three temporal partitioning strategies: (1)
predefined periods in American history, (2) overlapping time periods with fixed
length, and (3) time periods with variable length, which have approximately
equal volume of moves per time period. To account for the effect of geographic
proximity and flow volumes in migration flows, we transformed the raw flows
into modularity flows using a double-constrained a gravity model. Our
preliminary results revealed longitudinal population mobility in the U.S. on
such a large spatial and temporal scale.
