In this article, I argue that the computational history of chemistry offers a new way of engaging with the past: one that integrates narrative inquiry with algorithmic analysis, mathematical modelling, and large-scale data processing. I demonstrate how computational methods - distinguished by their digital foundations, algorithmic procedures, and computational purpose - can reveal patterns, model transformations, and test historical hypotheses across the social, semiotic, and material dimensions of chemistry. Crucially, I show how these methods allow historians to explore the interplay between history at different scales, from the micro to the macro: linking individual actors, local practices, and contested narratives with the longue durée of chemical knowledge. Yet I also reflect on the challenges that arise - particularly the need for historically meaningful categories, the risk of decontextualising data, and the persistence of bias in both sources and algorithms. By integrating historical narrative with computational analysis, I argue that the computational history of chemistry offers a critical and pluralist framework to reassess the unfolding of chemistry and to enrich its historiography for the digital age.

This article documents the creation of EMLAP (Early Modern Latin Alchemical Prints), a machine-readable corpus of one hundred Latin alchemical printed works produced within the TOME (The Origins of Modern Encyclopaedism, 2023–2025) project. It first situates the corpus within both the digital humanities landscape and the historiography of alchemy, where the availability of reliable machine-readable texts remains limited. It then addresses the challenges of converting early modern Latin printed text into machine-readable format with a high standard of quality. The article argues that producing a high-quality transcribed corpus at scale still requires human scholarly intervention, and that a transcription project must balance the ideal of digital edition standards against the practical constraints of time and resources. The article describes the practical experience of building EMLAP: the selection of the Transkribus platform for AI-powered automatic text recognition, the choice of transcription models, the development of human quality standards to complement automated metrics, and the construction of a computational pipeline to process and enrich the transcriptions. The EMLAP corpus has been made publicly available in open access (Zenodo repository) as well as in the form of a website that offers different search opportunities for researchers.

This article discusses how quantitative approaches to the history of chemistry gradually emerged in the first three decades of the postwar era, within the broader context of quantitative social and economic history, historical sociology of science, and quantitative science indicators. I suggest that influential publications in the 1960s, postulating logistic curves in the exponential growth of science and the role of a broad scientific community in producing and distributing scientific knowledge, stimulated subsequent quantitative research in the history of chemistry. With mainframe computers presenting technical difficulties in the foundational period to the mid-1980s, initial quantitative research usually involved sets of non-computerised data cards developed ad hoc for specific projects – here exemplified by databases including German and British chemists. Shifting to computerised databases during the 1980s and 1990s, as they confronted increasingly large amounts of data. Fortunately, simultaneous technological improvements, leading to more powerful desktop computers and more user-friendly software, greatly facilitated this transition. Early computerised databases may have been neither designed for wider use online, nor mutually compatible; without external support, they might not survive the careers of their creators. Preserving, integrating, and broadening access to such valuable raw data remains a crucial challenge for future scholarship.