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Enhancing data visualisation to capture the simulator sickness phenomenon: On the usefulness of radar charts
The data presented in this article are related to the research article entitled “The use of transdermal scopolamine to solve methodological issues raised by gender differences in susceptibility to simulator sickness” (Chaumillon et al., 2017) [1]. In an outstanding first demonstration, Kennedy et al...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470601/ https://www.ncbi.nlm.nih.gov/pubmed/28649590 http://dx.doi.org/10.1016/j.dib.2017.05.051 |
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author | Chaumillon, Romain Romeas, Thomas Paillard, Charles Bernardin, Delphine Giraudet, Guillaume Bouchard, Jean-François Faubert, Jocelyn |
author_facet | Chaumillon, Romain Romeas, Thomas Paillard, Charles Bernardin, Delphine Giraudet, Guillaume Bouchard, Jean-François Faubert, Jocelyn |
author_sort | Chaumillon, Romain |
collection | PubMed |
description | The data presented in this article are related to the research article entitled “The use of transdermal scopolamine to solve methodological issues raised by gender differences in susceptibility to simulator sickness” (Chaumillon et al., 2017) [1]. In an outstanding first demonstration, Kennedy et al. [2] showed that the Simulator Sickness Questionnaire (SSQ) is an appropriate tool to suit the purposes of characterizing motion sickness experienced in virtual environments. This questionnaire has since been used in many scientific studies. Recently, Balk et al. [3] suggested that the proposed segregation of SSQ scores into three subclasses of symptoms might limit the accuracy of simulator sickness assessment. These authors performed a factor analysis based on SSQ scores obtained from nine studies on driving simulators. Although their factor analysis resulted in the same three orthogonal classes of symptoms as Kennedy et al. [2], unlike this pioneering study, no items were attributed to more than one factor and five items were not attributed to any class of symptoms. As a result, they claimed that an exploration of each item score should give additional cues on individual profiles. To gain a better characterization of such item-by-item exploration, data utilised in this research are shown using a radar chart visualisation. |
format | Online Article Text |
id | pubmed-5470601 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-54706012017-06-23 Enhancing data visualisation to capture the simulator sickness phenomenon: On the usefulness of radar charts Chaumillon, Romain Romeas, Thomas Paillard, Charles Bernardin, Delphine Giraudet, Guillaume Bouchard, Jean-François Faubert, Jocelyn Data Brief Data Article The data presented in this article are related to the research article entitled “The use of transdermal scopolamine to solve methodological issues raised by gender differences in susceptibility to simulator sickness” (Chaumillon et al., 2017) [1]. In an outstanding first demonstration, Kennedy et al. [2] showed that the Simulator Sickness Questionnaire (SSQ) is an appropriate tool to suit the purposes of characterizing motion sickness experienced in virtual environments. This questionnaire has since been used in many scientific studies. Recently, Balk et al. [3] suggested that the proposed segregation of SSQ scores into three subclasses of symptoms might limit the accuracy of simulator sickness assessment. These authors performed a factor analysis based on SSQ scores obtained from nine studies on driving simulators. Although their factor analysis resulted in the same three orthogonal classes of symptoms as Kennedy et al. [2], unlike this pioneering study, no items were attributed to more than one factor and five items were not attributed to any class of symptoms. As a result, they claimed that an exploration of each item score should give additional cues on individual profiles. To gain a better characterization of such item-by-item exploration, data utilised in this research are shown using a radar chart visualisation. Elsevier 2017-05-31 /pmc/articles/PMC5470601/ /pubmed/28649590 http://dx.doi.org/10.1016/j.dib.2017.05.051 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Chaumillon, Romain Romeas, Thomas Paillard, Charles Bernardin, Delphine Giraudet, Guillaume Bouchard, Jean-François Faubert, Jocelyn Enhancing data visualisation to capture the simulator sickness phenomenon: On the usefulness of radar charts |
title | Enhancing data visualisation to capture the simulator sickness phenomenon: On the usefulness of radar charts |
title_full | Enhancing data visualisation to capture the simulator sickness phenomenon: On the usefulness of radar charts |
title_fullStr | Enhancing data visualisation to capture the simulator sickness phenomenon: On the usefulness of radar charts |
title_full_unstemmed | Enhancing data visualisation to capture the simulator sickness phenomenon: On the usefulness of radar charts |
title_short | Enhancing data visualisation to capture the simulator sickness phenomenon: On the usefulness of radar charts |
title_sort | enhancing data visualisation to capture the simulator sickness phenomenon: on the usefulness of radar charts |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470601/ https://www.ncbi.nlm.nih.gov/pubmed/28649590 http://dx.doi.org/10.1016/j.dib.2017.05.051 |
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