Toward supporting decision-making under uncertainty in digital humanities with progressive visualization

Digital Humanities (DH) research and practice is subject to uncertainty during the life cycle of any project. Even in non data-oriented cases, analysts and other stakeholders need to make decisions without being aware of the level of uncertainty associated to the data being transformed by the computational tools used to enable the kind of novel work of humanists pursued within DH. We examine in this paper the literature that have characterized the types and sources of uncertainty in other fields, with the intent of establishing a foundation upon which build novel computational tools supporting the decision-making under uncertainty processes that DH is currently facing. We propose the use of progressive visual analytics as a feasible means to manage decision-making under uncertainty, which may help tackling some challenges related to the elimination or mitigation of uncertainty in DH, that otherwise would tamper the quality of the yielded results.

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