Living with Machines was five year project which experimented with the power of cutting edge data science methods for leveraging digitised historical collections at scale. The project made a series of interventions, developing new datasets, new software, generating historical research, as well as exploring new paradigms for interdisciplinary collaborative research. Our challenge, now the project is ‘complete’, is to think about the afterlife of the assets from this project, and specifically how to build user and developer communities around our data and software. This paper will explore the opportunities for the community as well as the major hurdles we need to surmount - not just within the project team but in the wider research culture in the UK.

Presenters
Ruth Ahnert is Professor of Literary History and Digital Humanities, Queen Mary University of London. Her research sits at the intersection of early modern literary history, archival studies, and data science. Her books include Tudor Networks of Power (co-authored with Sebastian E. Ahnert, Oxford 2023), Collaborative Historical Research in the Age of Big Data (co-authored with Emma Griffin, Mia Ridge and Giogia Tolfo, Cambridge 2023), The Network Turn (co-authored with Sebastian E. Ahnert, Catherine N. Coleman, and Scott B. Weingart, Cambridge 2020), and The Rise of Prison Literature in the Sixteenth Century (Cambridge 2014). She was PI of the Living with Machines Project for five years until August 2023, and is now Co-I on the new Data/Culture project at The Alan Turing Institute.

Daniel Wilson is a historian of science and technology working on the politics and provenance of data and machines in the nineteenth, twentieth and twenty-first centuries. His work combines traditional close-reading and archival study with computational techniques. Current projects include using language models and other critical methods to explore historical datasets, including the internationally important collections of the British Library. Prior to being appointed a Turing Research Fellow, Daniel was Senior Research Associate on the Living with Machines project: a radical collaboration between historians, curators, data scientists and computational linguists. The project explored the industrial revolution in Britain using digital methods, including computer vision on historical map collections.