This project explores how machine learning and artificial intelligence can transform the scholarly digital editing process, not only by potentially automating and enhancing editorial workflows, but also by helping to reimagine digital editions beyond the constraints of print-based models. In particular, it researches and analyses how computational and AI-driven methods, including but not limited to machine learning, Natural Language Processing, large language models, data visualisations, and linked open data, can help streamline and improve editorial workflows. At the same time, it considers how digital editions can break away from static, book-like representations of historical texts, to take full advantage of digital medium—incorporating interactive, multimodal, and networked elements, and experimenting with new ways of engaging and digitally re-presenting historical and cultural texts. PhD applicants will be expected to advance the state of the art in digital editing, using their own case study (historical/cultural texts) within their own subject expertise. Historical/literary texts in any language, of any genre are welcome.
Principal Investigator: Dr Isabella Magni (Digital Humanities Institute)
Apply for a PhD on this project
We welcome research proposals from PhD candidates that address this project. Successful candidates will have academic experience in textual cultural data, editing historical texts, scholarly digital editing, text encoding, or machine learning and AI, or will be able to show how their interests and experience align with the project.