In this talk, I extend arguments for archival decolonization to the age of big data by offering a definition of restorative data justice and presenting two methods by which we may begin this work. The few extant fragments of knowledge from Ottoman Algeria emerge from French and Algerian chronicles of the governors, travel narratives, and consular records. Through close reading, structured notes, and context-informed classification, I reconstructed data sets on the governors of Ottoman Algeria (1518-1837) for prosopographical study. This reconstruction does not simply reconstitute imperial classification schemas but rather seeks to describe these men and women (in the social network study) with categories that they themselves would have likely employed. Similarly, we can use data mining approaches, which by their very definition are extractive, to address voids in the archive. Through text mining to identify named and unnamed entities and social network analysis to illustrate and study their relationships, unnamed women’s spectral presence may be recovered and represented despite their absence in the archival record. Hand-in-hand, these techniques allow us to reassemble data lost in the violence of colonial conquest and to resurrect the stories, if not the voices, of men and women long silenced. In this way, we subvert colonial weapons of quantification and convert them into tools for restitution.
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