The project addresses an unsolved problem in the domain of diplomatics, i.e., the historical auxiliary science, studying medieval and early modern single sheet legal documents: With pure human intellectual capacity, the empirical part of this research had to focus on local, regional, or chancery level in the face of overwhelming quantities of charters (Hlavacek 2006). While earlier approaches to applying digital methods to the field focussed on digital representation of individual descriptions (Ambrosio et al. 2014, Vogeler 2009, Bradley et al 2019), the large-scale “distant reading” approach has been scarce. This changed only recently: In the field of computer vision, Handwritten Text Recognition (HTR) has provided the first results in changing this (Hodel 2017). In addition, Computer Vision (CV) can provide quantified stylistic attributes of all graphical features of a charter. Leifert et al. 2020 and Christlein 2018 extracted graphical elements from charters (e.g., decorations, notarial signs). There are indications that CV can infer the date of a historical document (Cloppet 2017, Seuret 2021) and can classify the handwriting style from a paleographical perspective.