Uncertainty in humanities network visualization

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

doi:10.3389/fcomm.2023.1305137

Sub Visualisation and Graphics

Research output: Contribution to journal › Article › Academic › peer-review

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/pinto 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.

Original language	English
Article number	1305137
Journal	Frontiers in Communication
Volume	8
DOIs	https://doi.org/10.3389/fcomm.2023.1305137
Publication status	Published - 2024

Bibliographical note

Publisher Copyright:
Copyright © 2024 Conroy, Gillmann, Harvey, Mchedlidze, Fabrikant, Windhager, Scheuermann, Tangherlini, Warren, Weingart, Rehbein, Börner, Elo, Jänicke, Kerren, Nöllenburg, Dwyer, Eide, Kobourov and Betz.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The author(s) acknowledge support from the German Research Foundation (DFG) and Universität Leipzig within the program of Open Access Publishing. The authors benefited from an open-access publication grant from the Division of Research and Innovation at the University of Memphis.

Funders
Division of Research and Innovation at the University of Memphis
California Department of Fish and Game
Deutsche Forschungsgemeinschaft
Universität Leipzig

Keywords

digital humanities
historical networks
mathematical uncertainty
network visualization
uncertainty in networks
visual variables

Access to Document

10.3389/fcomm.2023.1305137Licence: CC BY

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Cite this

Conroy, M., Gillmann, C., Harvey, F., Mchedlidze, T., Fabrikant, S. I., Windhager, F., Scheuermann, G., Tangherlini, T. R., Warren, C. N., Weingart, S. B., Rehbein, M., Börner, K., Elo, K., Jänicke, S., Kerren, A., Nöllenburg, M., Dwyer, T., Eide, Ø., Kobourov, S., & Betz, G. (2024). Uncertainty in humanities network visualization. Frontiers in Communication, 8, Article 1305137. https://doi.org/10.3389/fcomm.2023.1305137

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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/pinto 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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author = "Melanie Conroy and Christina Gillmann and Francis Harvey and Tamara Mchedlidze and Fabrikant, \{Sara Irina\} and Florian Windhager and Gerik Scheuermann and Tangherlini, \{Timothy R.\} and Warren, \{Christopher N.\} and Weingart, \{Scott B.\} and Malte Rehbein and Katy B{\"o}rner and Kimmo Elo and Stefan J{\"a}nicke and Andreas Kerren and Martin N{\"o}llenburg and Tim Dwyer and {\O}yvind Eide and Stephen Kobourov and Gregor Betz",

note = "Publisher Copyright: Copyright {\textcopyright} 2024 Conroy, Gillmann, Harvey, Mchedlidze, Fabrikant, Windhager, Scheuermann, Tangherlini, Warren, Weingart, Rehbein, B{\"o}rner, Elo, J{\"a}nicke, Kerren, N{\"o}llenburg, Dwyer, Eide, Kobourov and Betz.",

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Conroy, M, Gillmann, C, Harvey, F, Mchedlidze, T, Fabrikant, SI, Windhager, F, Scheuermann, G, Tangherlini, TR, Warren, CN, Weingart, SB, Rehbein, M, Börner, K, Elo, K, Jänicke, S, Kerren, A, Nöllenburg, M, Dwyer, T, Eide, Ø, Kobourov, S & Betz, G 2024, 'Uncertainty in humanities network visualization', Frontiers in Communication, vol. 8, 1305137. https://doi.org/10.3389/fcomm.2023.1305137

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AU - Conroy, Melanie

AU - Gillmann, Christina

AU - Harvey, Francis

AU - Mchedlidze, Tamara

AU - Fabrikant, Sara Irina

AU - Windhager, Florian

AU - Scheuermann, Gerik

AU - Tangherlini, Timothy R.

AU - Warren, Christopher N.

AU - Weingart, Scott B.

AU - Rehbein, Malte

AU - Börner, Katy

AU - Elo, Kimmo

AU - Jänicke, Stefan

AU - Kerren, Andreas

AU - Nöllenburg, Martin

AU - Dwyer, Tim

AU - Eide, Øyvind

AU - Kobourov, Stephen

AU - Betz, Gregor

N1 - Publisher Copyright: Copyright © 2024 Conroy, Gillmann, Harvey, Mchedlidze, Fabrikant, Windhager, Scheuermann, Tangherlini, Warren, Weingart, Rehbein, Börner, Elo, Jänicke, Kerren, Nöllenburg, Dwyer, Eide, Kobourov and Betz.

PY - 2024

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N2 - 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/pinto 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.

AB - 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/pinto 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.

KW - digital humanities

KW - historical networks

KW - mathematical uncertainty

KW - network visualization

KW - uncertainty in networks

KW - visual variables

UR - https://www.scopus.com/pages/publications/85183003480

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M1 - 1305137

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