PROgressive VIsual DEcision-Making in Digital Humanities (PROVIDEDH)

The PROgressive VIsual DEcision-Making in Digital Humanities (PROVIDEDH) project is a four-year project funded within the CHIST-ERA call 2016 for the topic “Visual Analytics for Decision Making under Uncertainty – VADMU.”  The project aims to give Digital Humanities (DH) scholars a space to explore and assess the completeness and evolution of digital research objects, the degree of uncertainty that the models applied to the data incorporate, and to share their perspectives and insights with the project’s broad range of stakeholders.

The project’s goal is realisable through the development of a wide spectrum of outcomes, ranging from recommendations and reports, to a multimodal collaborative platform for the progressive visual analysis of different DH collections, both for scholars and citizen humanists.  The project brings technical experts together with leading digital humanists with a range of expertise and is supported by Winnovation, one of the leading European consulting agencies on Open Innovation. The developed systems will be available for external stakeholders to use and our open-source approach will promote their collaboration with the project and its partners.

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

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.