Digital Perspectives in History

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.

CorDeep and the Sacrobosco Dataset: Detection of Visual Elements in Historical Documents

“…The accessibility of this web-service, along with its historically oriented model, allow historians to investigate the content of large historical corpora by extracting their visual elements in distinct classes; a task that would otherwise require countless hours. The fact that the field of Digital Humanities is developing at lightning speed only emphasizes the importance of the above contributions and highlights the need to better disseminate historical datasets, as well as to provide easy-to-use computational models for general use [ 53 ]. These contributions are envisioned to be the first of many, while the next steps will focus on adding new classes to Cor Deep , allowing historians to detect not only visual elements, but also for instance numerical tables.…”

Dura-Europos Stories: Developing interactive storytelling applications using knowledge graphs for cultural heritage exploration

“…A diverse range of topics are covered under the term 'digital humanities', and researchers have reused data from Wikidata in many digital humanities projects [21]. Our project contains some features of digital databases described in [14].…”

“…We used a PostgreSQL database to store configuration information related to the presentation metadata of each story. We use Redis 14 to cache Wikidata SPARQL query results.…”