Above image: a page from the Register of Liberated Africans, c. 1837
Creating a visual language of marks: approaching African identities through data visualization
Co-investigators: Martha Ladly, Ph.D. (OCAD University) and Katrina Keefer, Ph.D. (Adjunct Professor of History, Trent University, Katrinakeefer@trentu.ca)
Project Manager and Research Assistant: Kartikay Chadha (email@example.com)
Collaborators: Paul Lovejoy (York University), Dean Rehberger (Michigan State University), Mohammed Salau (University of Mississippi), and Abubakar Babajo Sani (Umaru Musa Yar'adua University, Katsina).
Research Assistants: Eric Lehman, Michael McGill, Maria Yala, Georgina Yeboah
Past Research Assistants: Ma Qianyi
The trans-Atlantic slave trade was a centuries-long trauma that saw approximately 12.5 million Africans forcibly taken from their homes and transported to work in the emerging plantation societies of the Americas. The trauma of enslavement and sustained repression of language, culture and beliefs blurred memories of origins and birthplaces. Previous attempts at analyzing large datasets of names recorded in manumission records to unearth individuals and personal histories have been challenged by practices of slave renaming. Drs. Ladly and Keefer will work with their collaborators to develop a searchable visual database using the entries from the 19th century Registers of Liberated Africans to reveal individual identities and origins. Their research includes appropriate methods for collection, analysis and presentation of the sensitive personal information within these datasets. They will design and train an AI model to work in conjunction with ethno-linguistic and visual models, so that researchers and members of the public may extract meaningful information from the data. Working in the Visual Analytics Lab, the OCAD U design team will construct computational architectures for the visual/linguistic database, develop a mathematical model for data analysis, and design dynamic 2D and 3D visual models and user interfaces.
For more information, please visit http://decodingorigins.org
This research is supported by the Social Sciences and Humanities Research Council of Canada.