In the current context of the Digital Humanities, it is each time more necessary to investigate and advance in the generation of knowledge through the analysis of large volumes of data and visualizations. On the other hand, as in many academic fields, the value of different perspectives in the research process is progressively recognized, integrating not only diverse disciplines but also the knowledge from non-academic roles. At the confluence of these two emerging paradigms, the uncertainty surrounding the data, information and knowledge generated by data visualization and transdisciplinarity approaches represents a methodological and a technical challenge. Through complementary methods of participatory design and a survey to DH scholars, we propose the prototype of a participatory material for working sessions that can help to reflect a collaborative visualization of types of uncertainty in the field of DH, especially for early phases of awareness and familiarization with the topic. As a result of a first cycle of iterations with 14 participants in a workshop, and the inputs of 50 survey respondents, we propose a canvas model adapting the Johari window which allows to visualize and share examples of knowledge uncertainty around research datasets, integrating diverse emerging taxonomies in this field of study.
Reference: Senabre Hidalgo, E., Wandl-Vogt, E., Dorn, A., & Souza, R. R. (2019, October). Mapping uncertainty around research data: a Digital Humanities transdisciplinary perspective adopting the Johari window. In Proceedings of the Seventh International Conference on Technological Ecosystems for Enhancing Multiculturality (pp. 804-809). ACM. https://doi.org/10.1145/3362789.3362931