| 1. |
- Conroy, Melanie, et al.
(författare)
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Uncertainty in humanities network visualization
- 2024
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Ingår i: Frontiers in Communication. - : Frontiers Media S.A.. - 2297-900X. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Network visualization is one of the most widely used tools in digital humanities research. The idea of uncertain or “fuzzy” data is also a core notion in digital humanities research. Yet network visualizations in digital humanities do not always prominently represent uncertainty. In this article, we present a mathematical and logical model of uncertainty as a range of values which can be used in network visualizations. We review some of the principles for visualizing uncertainty of different kinds, visual variables that can be used for representing uncertainty, and how these variables have been used to represent different data types in visualizations drawn from a range of non-humanities fields like climate science and bioinformatics. We then provide examples of two diagrams: one in which the variables displaying degrees of uncertainty are integrated into the graph and one in which glyphs are added to represent data certainty and uncertainty. Finally, we discuss how probabilistic data and what-if scenarios could be used to expand the representation of uncertainty in humanities network visualizations.
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| 2. |
- Kübler, Isabella, et al.
(författare)
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Against All Odds : Multicriteria Decision Making with Hazard Prediction Maps Depicting Uncertainty
- 2020
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Ingår i: Annals of the Association of American Geographers. - : Taylor & Francis. - 0004-5608 .- 1467-8306. ; 110:3, s. 661-683
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Tidskriftsartikel (refereegranskat)abstract
- We report on a multicriteria decision-making study where participants were asked to purchase a house shown on maps that include hazard prediction information. We find that participants decided to buy different houses, depending on whether uncertainty is shown on the map display and on the type of uncertainty visualization (i.e., varying color value, focus, or texture). We also find that participants’ individual differences with respect to their assessed risk-taking behavior influences their spatial decision making with maps. Risk-takers seem to underestimate the dangers of natural hazards when prediction uncertainties are depicted. We are thus able to shed additional light on how people use visualized uncertainty information to make complex map-based decisions. We can demonstrate that not only are design characteristics relevant for map-based reasoning and decision-making outcomes but so are the decision makers’ individual background and the map-based decision-making context.
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