Publikation: Uncertainty visualization : Fundamentals and recent developments
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Datum
2022
Autor:innen
Hägele, David
Schulz, Christoph
Beschle, Cedric
Barth, Andrea
Weiskopf, Daniel
Herausgeber:innen
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Deutsche Forschungsgemeinschaft (DFG): 251654672
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it - Information Technology. De Gruyter Oldenbourg. 2022, 64(4-5), pp. 121-132. ISSN 1611-2776. eISSN 2196-7032. Available under: doi: 10.1515/itit-2022-0033
Zusammenfassung
This paper provides a brief overview of uncertainty visualization along with some fundamental considerations on uncertainty propagation and modeling. Starting from the visualization pipeline, we discuss how the different stages along this pipeline can be affected by uncertainty and how they can deal with this and propagate uncertainty information to subsequent processing steps. We illustrate recent advances in the field with a number of examples from a wide range of applications: uncertainty visualization of hierarchical data, multivariate time series, stochastic partial differential equations, and data from linguistic annotation.
Zusammenfassung in einer weiteren Sprache
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HÄGELE, David, Christoph SCHULZ, Cedric BESCHLE, Hannah BOOTH, Miriam BUTT, Andrea BARTH, Oliver DEUSSEN, Daniel WEISKOPF, 2022. Uncertainty visualization : Fundamentals and recent developments. In: it - Information Technology. De Gruyter Oldenbourg. 2022, 64(4-5), pp. 121-132. ISSN 1611-2776. eISSN 2196-7032. Available under: doi: 10.1515/itit-2022-0033BibTex
@article{Hagele2022-08-31Uncer-58489,
year={2022},
doi={10.1515/itit-2022-0033},
title={Uncertainty visualization : Fundamentals and recent developments},
number={4-5},
volume={64},
issn={1611-2776},
journal={it - Information Technology},
pages={121--132},
author={Hägele, David and Schulz, Christoph and Beschle, Cedric and Booth, Hannah and Butt, Miriam and Barth, Andrea and Deussen, Oliver and Weiskopf, Daniel}
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