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Abstract

This article outlines the state of digital perspectives in historical research, some of the methods and tools in use by digital historians, and the possible or even necessary steps in the future development of the digital approach. We begin by describing three main computational approaches: digital databases and repositories, network analysis, and Machine Learning. We also address data models and ontologies in the larger context of the demand for sustainability and linked research data. The section is followed by a discussion of the (much needed) standards and policies concerning data quality and transparency. We conclude with a consideration of future scenarios and challenges for computational research.