The use of data, Artificial Intelligence (AI) and data science techniques are becoming increasingly pervasive in daily life and research activities, attracting many scholars to adopt them in historically oriented research with promising results. However, neither data nor computational techniques are neutral tools. Historical archives and datasets are themselves the products of selective curation reflecting underlying biases and power dynamics of the context of their creation and collection as well as inequities in access, infrastructure, and perspective. The datafication of historical sources risks to amplify these issues, introducing further challenges related to taxonomy, categorization, and conceptualization. This may lead, if not countered, to the standardisation of diverse historical experiences into rigid categories, further entrenching existing biases as well as the under-representation of marginalized genders, cultures, social groups and identities, thus erasing pluralities in historical narratives. Since archives and data repositories in Europe often originated within imperial or colonial frameworks, shaping both the content and the perspective of the historical records they contain, these challenges are especially prevalent within European historical research and demand specific attention and ethical responsibilities.
