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<title>Abstract</title> <p>Computational methods in history and heritage can transcend conventional analysis, enabling investigation of complex questions beyond the reach of traditional scholarship or digital approaches. Computational history and heritage are necessary because they provide the tools to analyse vast and multidimensional datasets from our past. The ‘computational’ aspect, i.e., through modelling and simulation, machine learning, and deep learning, can enable a deeper understanding of complex socio-cultural dynamics in periods of history that are largely textual. Through simulation, it can also enhance human-environment interactions by integrating data from objects, monuments, sites, and landscapes, as well as ancient genomic records and environmental proxies such as climate records from animal remains and pollen data. This synthesis, viewed through the scholastic lens, can lead to discoveries in the emergence of micro-, meso-, and macro-cultures, as well as the knowledge within those cultures, which shape societies and civilisations. Through computational methods, the evolution of cultural practices across the millennia, ancient thoughts, prehistoric migration patterns, the impact of changing resources and climate on civilisations, as well as the dynamics of social networks, technological innovation, and symbolic expression, can now be systematically modelled and analysed. Such approaches enable scholars not only to reconstruct past environments and human behaviours, but also to simulate alternative scenarios, test competing hypotheses, and explore the complex interplay between culture, environment, and agency in ways that were previously inaccessible through traditional methods. This interdisciplinary field is crucial for making sense of the “data deluge” from the volume, velocity and variety of all historical eras and unlocking a more holistic narrative of the human story. Ultimately, by systematically bridging quantitative data with humanistic inquiry, this evolving field not only offers new answers to old questions but also empowers us to ask entirely new ones about our collective human story.</p>

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computational from data methods history

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