A Data-Driven Introduction to Authors, Readings, and Techniques in Visualization for the Digital Humanities

Alejandro Benito-Santos, Roberto Therón Sánchez

View presentation:2020-10-28T17:15:00ZGMT-0600Change your timezone on the schedule page
2020-10-28T17:15:00Z
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In this paper, we conduct a bibliometric study to characterize the interdisciplinary nexus between visualization and digital humanities. The study consists of several analyses that depart from a representative sample of works in visualization for the digital humanities that were obtained from different sources: the VIS4DH workshop, the ADHO Digital Humanities Conference, and the journal Digital Humanities Quarterly.
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Keywords

Visualization, Data visualization, DH-HEMTs, Task analysis, Collaboration, Databases

Abstract

The newly rediscovered frontier between data visualization and the digital humanities has proven to be an exciting field of experimentation for scholars from both disciplines. This fruitful collaboration is attracting researchers from other areas of science who may be willing to create visual analysis tools that promote humanities research in its many forms. However, as the collaboration grows in complexity, it may become intimidating for these scholars to get engaged in the discipline. To facilitate this task, we have built an introduction to visualization for the digital humanities that sits on a data-driven stance adopted by the authors. In order to construct a dataset representative of the discipline, we analyze citations from a core corpus on 300 publications in visualization for the humanities obtained from recent editions of the InfoVis Vis4DH workshop, the ADHO Digital Humanities Conference, and the specialized digital humanities journal Digital Humanities Quarterly. From here, we extract referenced works and analyze more than 1900 publications in search of citation patterns, prominent authors in the field, and other interesting insights. Finally, following the path set by other researchers in the visualization and Human-Computer Interaction (HCI) communities, we analyze paper keywords to identify significant themes and research opportunities in the field.