Introduction: ‘dirty data’ and creative quantification

Historical research has changed in the age of big data. But the articles in this special issue take inspiration from the quantitative approaches of Claire Lemercier and Claire Zalc. Rather than seeing the goal as ‘clean’ datasets, Lemercier and Zalc have championed approaches that linger on the work that historians do to transform the past into ‘data’, arguing that these operations are not just preparatory: they are where new findings and approaches emerge. The articles in this special issue all celebrate and interrogate ‘dirty data’, thinking with absence, confusion, mess and uncertainty. The introduction to the special issue sets Lemercier and Zalc’s work in the context of the historiography of France and the current state of quantitative and computing histories, including so-called ‘artificial intelligence’ (AI) and introduces the research articles and afterword by Zalc and Lemercier.