  The advent of modern computers has added an increased emphasis on channeling
computational power and statistical methods into digital humanities. Including
increased statistical rigor in history poses unique challenges due to the
inherent uncertainties of word-of-mouth and poorly recorded data. African
genealogies form an important such example, both in terms of individual
ancestries and broader historical context in the absence of written records.
Our project aims to bridge the lack of accurate maps of Africa during the
trans-Atlantic slave trade with the personalized question of where within
Africa an individual slave may have hailed. We approach this question with a
two part mathematical model informed by two primary sets of data. We begin with
a conflict intensity surface which can generate capture locations of
theoretical slaves, and accompany this with a Markov decision process which
models the transport of these slaves through existing cities to the coastal
areas. Ultimately, we can use this two-step approach of providing capture
locations to a historical trade network in a simulative fashion to generate and
visualize the conditional probability of a slave coming from a certain spatial
region given they were sold at a certain port. This is a data-driven visual
answer to the research question of where the slaves departing these ports
originated.
