Navigating High-Dimensional Backstage: A Guide for Exploring Literature for the Reliable Use of Dimensionality Reduction

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dc.contributor.authorJeon, Hyeonen_US
dc.contributor.authorLee, Hyunwooken_US
dc.contributor.authorKuo, Yun-Hsinen_US
dc.contributor.authorYang, Taehyunen_US
dc.contributor.authorArchambault, Danielen_US
dc.contributor.authorKo, Sungahnen_US
dc.contributor.authorFujiwara, Takanorien_US
dc.contributor.authorMa, Kwan-Liuen_US
dc.contributor.authorSeo, Jinwooken_US
dc.contributor.editorEl-Assady, Mennatallahen_US
dc.contributor.editorOttley, Alvittaen_US
dc.contributor.editorTominski, Christianen_US
dc.date.accessioned2025-05-26T06:58:59Z
dc.date.available2025-05-26T06:58:59Z
dc.date.issued2025
dc.description.abstractVisual analytics using dimensionality reduction (DR) can easily be unreliable for various reasons, e.g., inherent distortions in representing the original data. The literature has thus proposed a wide range of methodologies to make DR-based visual analytics reliable. However, the diversity and extensiveness of the literature can leave novice analysts and researchers uncertain about where to begin and proceed. To address this problem, we propose a guide for reading papers for reliable visual analytics with DR. Relying on the previous classification of the relevant literature, our guide helps both practitioners to (1) assess their current DR expertise and (2) identify papers that will further enhance their understanding. Interview studies with three experts in DR and data visualizations validate the significance, comprehensiveness, and usefulness of our guide.en_US
dc.description.sectionheadersSystems and Applications
dc.description.seriesinformationEuroVis 2025 - Short Papers
dc.identifier.doi10.2312/evs.20251087
dc.identifier.isbn978-3-03868-282-0
dc.identifier.pages5 pages
dc.identifier.urihttps://doi.org/10.2312/evs.20251087
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/evs20251087
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing → Visual analytics; Mathematics of computing → Dimensionality reduction
dc.subjectHuman centered computing → Visual analytics
dc.subjectMathematics of computing → Dimensionality reduction
dc.titleNavigating High-Dimensional Backstage: A Guide for Exploring Literature for the Reliable Use of Dimensionality Reductionen_US
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