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Uncertainty in humanities network visualization

Authors :
Conroy, Melanie
Gillmann, Christina
Harvey, Francis
Mchedlidze, Tamara
Fabrikant, Sara Irina
Windhager, Florian
Scheuermann, Gerik
Tangherlini, Timothy R.
Warren, Christopher N.
Weingart, Scott B.
Rehbein, Malte
Börner, Katy
Elo, Kimmo
Jänicke, Stefan
Kerren, Andreas
Nöllenburg, Martin
Dwyer, Tim
Eide, Øyvind
Kobourov, Stephen
Betz, Gregor
Conroy, Melanie
Gillmann, Christina
Harvey, Francis
Mchedlidze, Tamara
Fabrikant, Sara Irina
Windhager, Florian
Scheuermann, Gerik
Tangherlini, Timothy R.
Warren, Christopher N.
Weingart, Scott B.
Rehbein, Malte
Börner, Katy
Elo, Kimmo
Jänicke, Stefan
Kerren, Andreas
Nöllenburg, Martin
Dwyer, Tim
Eide, Øyvind
Kobourov, Stephen
Betz, Gregor
Publication Year :
2024

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.<br />Funding: University of Memphis10.13039/100011518

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1442970098
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.3389.fcomm.2023.1305137