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The development of methods to make it easier for scholars to research historical records, with a focus on 17th century notary records from Argentina. 

We propose to develop a software tool that will enable scholars to expeditiously read and analyze seventeenth century Spanish American notary records and quickly find relevant content in these document collections. Since these records were written in a type of script that was intentionally cryptic, it takes years of training in Spanish American paleography to become proficient in reading and analyzing them. Digital collections contain large amounts of information that can be modeled as a knowledge graph by applying deep learning and knowledge management techniques. The development of such a tool will make notarial scripts accessible to a larger community of researchers without requiring extensive paleography training. By modeling the content in the notary records as a knowledge graph, graph queries will facilitate the identification of legal formulae that characterize types of notarized documents and allow researchers to more efficiently mine the information relevant to their projects.