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Depicting uncertainty in 2.5D treemaps

Published: 08 December 2020 Publication History

Abstract

A truthful and unbiased display of data using information visualization requires detecting and communicating uncertainty. Uncertainty is often inherent in data or is introduced by data processing and visualization (e.g., visual display of accumulated data) but frequently not accounted for. This paper discusses the suitability of advanced visual variables such as sketchiness, noise, nesting-level contouring, and color weaving for communicating uncertainty.

References

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Alexandre Coninx, Georges-Pierre Bonneau, Jacques Droulez, and Guillaume Thibault. 2011. Visualization of uncertain scalar data fields using color scales and perceptually adapted noise. In ACM SIGGRAPH Symposium on Applied Perception in Graphics and Visualization (APGV). 59--66.
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Suzana Djurcilov, Kwansik Kim, Pierre Lermusiaux, and Alex Pang. 2002. Visualizing Scalar Volumetric Data with Uncertainty. Computers and Graphics 26 (2002), 239--248.
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Niklas Elmqvist and Jean-Daniel Fekete. 2010. Hierarchical Aggregation for Information Visualization: Overview, Techniques, and Design Guidelines. IEEE TVCG 16, 3 (2010), 439--454.
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Robert B. Haber and David A. McNabb. 1990. Visualization idioms: a conceptual model for scientific visualization systems.
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Haleh Hagh-Shenas, Sunghee Kim, Victoria Interrante, and Christopher G. Healey. 2007. Weaving Versus Blending: a quantitative assessment of the information carrying capacities of two alternative methods for conveying multivariate data with color. IEEE TVCG 13, 6 (2007), 1270--1277.
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Daniel Limberger, Carolin Fiedler, Sebastian Hahn, Matthias Trapp, and Jürgen Döllner. 2016. Evaluation of Sketchiness as a Visual Variable for 2.5 D Treemaps. In Proc. IEEE iV. 183--189.
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A. G. Soares, D. H. dos Santos, C. L. Barbosa, A. S. Goncalves, C. G. dos Santos, B. S. Meiguins, and E. T. Miranda. 2018. Visualizing Multidimensional Data in Treemaps with Adaptive Glyphs. In Proc. IEEE iV. 58--63.

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  • (2022)Visual variables and configuration of software mapsJournal of Visualization10.1007/s12650-022-00868-126:1(249-274)Online publication date: 16-Sep-2022

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VINCI '20: Proceedings of the 13th International Symposium on Visual Information Communication and Interaction
December 2020
205 pages
ISBN:9781450387507
DOI:10.1145/3430036
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 December 2020

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  • This work is part of the ?Software-DNA? project, which is funded by the European Regional Development Fund (ERDF ? or EFRE in German) and the State of Brandenburg (ILB).
  • This work has been supported by the German Federal Ministry of Education and Research (BMBF) through grant 01IS19006 (KI-Labor ITSE).

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VINCI 2020

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Overall Acceptance Rate 71 of 193 submissions, 37%

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Cited By

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  • (2022)Visual variables and configuration of software mapsJournal of Visualization10.1007/s12650-022-00868-126:1(249-274)Online publication date: 16-Sep-2022

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