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Parallel Chords: an audio-visual analytics design for parallel coordinates
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. (iVis, INV)ORCID iD: 0000-0001-5874-6356
St. Pölten University of Applied Sciences, St. Pölten, Austria; University of Music and Performing Arts Graz, Graz, Austria.ORCID iD: 0000-0002-5456-1140
t. Pölten University of Applied Sciences, St. Pölten, Austria.ORCID iD: 0000-0001-8788-4600
Linköping University, Department of Thematic Studies, Tema Environmental Change. Linköping University, Faculty of Arts and Sciences.ORCID iD: 0000-0001-9892-8875
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2024 (English)In: Personal and Ubiquitous Computing, ISSN 1617-4909, E-ISSN 1617-4917Article in journal (Refereed) Epub ahead of print
Abstract [en]

One of the commonly used visualization techniques for multivariate data is the parallel coordinates plot. It provides users with a visual overview of multivariate data and the possibility to interactively explore it. While pattern recognition is a strength of the human visual system, it is also a strength of the auditory system. Inspired by the integration of the visual and auditory perception in everyday life, we introduce an audio-visual analytics design named Parallel Chords combining both visual and auditory displays. Parallel Chords lets users explore multivariate data using both visualization and sonification through the interaction with the axes of a parallel coordinates plot. To illustrate the potential of the design, we present (1) prototypical data patterns where the sonification helps with the identification of correlations, clusters, and outliers, (2) a usage scenario showing the sonification of data from non-adjacent axes, and (3) a controlled experiment on the sensitivity thresholds of participants when distinguishing the strength of correlations. During this controlled experiment, 35 participants used three different display types, the visualization, the sonification, and the combination of these, to identify the strongest out of three correlations. The results show that all three display types enabled the participants to identify the strongest correlation — with visualization resulting in the best sensitivity. The sonification resulted in sensitivities that were independent from the type of displayed correlation, and the combination resulted in increased enjoyability during usage.

Place, publisher, year, edition, pages
Springer, 2024.
National Category
Media Engineering
Identifiers
URN: urn:nbn:se:liu:diva-203454DOI: 10.1007/s00779-024-01795-8OAI: oai:DiVA.org:liu-203454DiVA, id: diva2:1857376
Funder
Knut and Alice Wallenberg Foundation, 2019.0024Available from: 2024-05-13 Created: 2024-05-13 Last updated: 2024-05-28

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Elmquist, EliasNavarra, CarloBock, AlexanderYnnerman, AndersRönnberg, Niklas

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Elmquist, EliasEnge, KajetanRind, AlexanderNavarra, CarloHöldrich, RobertIber, MichaelBock, AlexanderYnnerman, AndersAigner, WolfgangRönnberg, Niklas
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Media and Information TechnologyFaculty of Science & EngineeringTema Environmental ChangeFaculty of Arts and Sciences
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