http://hdl.handle.net/2451/43461 2026-04-05T12:03:54Z http://hdl.handle.net/2451/75614 Title: Medieval Manuscripts and the Computational Humanities Big Data, Scribes, and the “Paris Bible” Authors: Wrisley, David Joseph; Guéville, Estelle Abstract: This book examines the transformations in medieval studies—and the humanities more broadly—enabled by decades of digitization and advances in computational methods. Centring on the Paris Bible, a widely copied thirteenth- and fourteenth-century manuscript genre, we demonstrate how automated transcription produces scribal data at a scale once inaccessible, and how automation can support new approaches to localizing, dating, and contextualizing manuscripts. We argue that bringing machine learning and artificial intelligence to medieval studies not only requires re-centring expert human intelligence within computational systems, but also raises the question of the infrastructures needed for equitable, collaborative scholarship across the field. The book models how medieval studies might rethink interpretation, highlighting both the promise and risks of computational methods in manuscript research. 2026-02-01T00:00:00Z http://hdl.handle.net/2451/75159 Title: AI and Digital Humanities in the Arabian Gulf: Interdisciplinary Perspectives on Infrastructure, Cultural Heritage, and Community Building Authors: Catelan, Nicolas; Fresquet, Xavier; Moura, Sabrina; Svard, Proscovia; Wrisley, David Joseph Abstract: This article examines the integration of artificial intelligence (AI) in digital humanities and cultural heritage preservation across the Arabian Gulf region. It highlights the ethical, legal, and community-centered challenges raised by AI in archives, museums, and libraries, while showcasing local initiatives that adopt inclusive and culturally grounded approaches. The paper calls for an interdisciplinary governance of AI, anchored in shared infrastructures, context-sensitive regulation, and active community participation. 2025-05-13T00:00:00Z http://hdl.handle.net/2451/74851 Title: Everyone Leaves a Trace: Exploring Transcriptions of Medieval Manuscripts with Computational Methods Authors: Guéville, Estelle; Wrisley, David Joseph Abstract: The topic of this paper is a thirteenth-century manuscript from the French National Library (Paris, BnF français 24428) containing three popular texts: an encyclopedic work, a bestiary and a collection of animal fables. We have automatically transcribed the manuscript using a custom handwritten text recognition (HTR) model for old French. Rather than a content-based analysis of the manuscript’s transcription, we adapt quantitative methods normally used for authorship attribution and clustering to the analysis of scribal contribution in the manuscript. Furthermore, we explore the traces that are left when texts are copied, transcribed and/or edited, and the importance of that trace for computational textual analysis with orthographically unstable historical languages. We argue that the method of transcription is fundamental for being able to think about complex modes of authorship which are so important for understanding medieval textual transmission. The paper is inspired by trends in digital scholarship in the mid-2020s, such as public transcribe-a-thons in the GLAM (Galleries, Libraries, Archives and Museums) sector, the opening up of digitized archival collections with methods such as HTR, and computational textual analysis of the transcriptions. 2024-11-29T00:00:00Z http://hdl.handle.net/2451/74850 Title: Exploring Gulf Manumission Documents with Word Vectors Authors: Kirmizialtin, Suphan; Wrisley, David Joseph Abstract: In this article we analyze a corpus related to manumission and slavery in the Arabian Gulf in the late nineteenth- and early twentieth-century that we created using Handwritten Text Recognition (HTR). The corpus comes from India Office Records (IOR) R/15/1/199 File 5. Spanning the period from the 1890s to the early 1940s and composed of 977K words, it contains a variety of perspectives on manumission and slavery in the region from manumission requests to administrative documents relevant to colonial approaches to the institution of slavery. We use word2Vec with the WordVectors package in R to highlight how the method can uncover semantic relationships within historical texts, demonstrating some exploratory semantic queries, investigation of word analogies, and vector operations using the corpus content. We argue that advances in applied computer vision such as HTR are promising for historians working in colonial archives and that while our method is reproducible, there are still issues related to language representation and limitations of scale within smaller datasets. Even though HTR corpus creation is labor intensive, word vector analysis remains a powerful tool of computational analysis for corpora where HTR error is present. 2024-12-27T00:00:00Z