The Pattern is in the Details: An Evaluation of Interaction Techniques for Locating, Searching, and Contextualizing Details in Multivariate Matrix Visualizations

dc.contributor.authorYang, Yalongen
dc.contributor.authorXia, Wenyuen
dc.contributor.authorLekschas, Fritzen
dc.contributor.authorNobre, Carolinaen
dc.contributor.authorKrüger, Roberten
dc.contributor.authorPfister, Hanspeteren
dc.date.accessioned2022-10-19T16:58:08Zen
dc.date.available2022-10-19T16:58:08Zen
dc.date.issued2022-04-27en
dc.date.updated2022-10-19T15:08:29Zen
dc.description.abstractMatrix visualizations are widely used to display large-scale network, tabular, set, or sequential data. They typically only encode a single value per cell, e.g., through color. However, this can greatly limit the visualizations’ utility when exploring multivariate data, where each cell represents a data point with multiple values (referred to as details). Three well-established interaction approaches can be applicable in multivariate matrix visualizations (or MMV): focus+context, pan&zoom, and overview+detail. However, there is little empirical knowledge of how these approaches compare in exploring MMV. We report on two studies comparing them for locating, searching, and contextualizing details in MMV. We first compared four focus+context techniques and found that the fisheye lens overall outperformed the others. We then compared the fisheye lens, to pan&zoom and overview+detail. We found that pan&zoom was faster in locating and searching details, and as good as overview+detail in contextualizing details.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1145/3491102.3517673en
dc.identifier.urihttp://hdl.handle.net/10919/112225en
dc.language.isoenen
dc.publisherACMen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.holderThe author(s)en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0en
dc.titleThe Pattern is in the Details: An Evaluation of Interaction Techniques for Locating, Searching, and Contextualizing Details in Multivariate Matrix Visualizationsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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