Glyphboard: Visual Exploration of High-Dimensional Data Combining Glyphs with Dimensionality Reduction

Rigorous data science is interdisciplinary at its core. In order to make sense of high-dimensional data, data scientists need to enter into a dialogue with domain experts. We present Glyphboard, a visualization tool that aims to support this dialogue. Glyphboard is a zoomable user interface that com...

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Bibliographic Details
Published in:	IEEE transactions on visualization and computer graphics Vol. 26; no. 4; pp. 1661 - 1671
Main Authors:	Kammer, Dietrich, Keck, Mandy, Grunder, Thomas, Maasch, Alexander, Thom, Thomas, Kleinsteuber, Martin, Groh, Rainer
Format:	Journal Article
Language:	English
Published:	United States IEEE 01-04-2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Core making Data analytics Domains Empirical studies in interaction design Estimating techniques Human-centered computing Reduction Scientists Subject specialists Visualization Visualization systems and tools
Online Access:	Get full text
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Summary:	Rigorous data science is interdisciplinary at its core. In order to make sense of high-dimensional data, data scientists need to enter into a dialogue with domain experts. We present Glyphboard, a visualization tool that aims to support this dialogue. Glyphboard is a zoomable user interface that combines well-known methods such as dimensionality reduction and glyph-based visualizations in a novel, seamless, and integrated tool. While the dimensionality reduction affords a quick overview over the data, glyph-based visualizations are able to show the most relevant dimensions in the data set at one glance. We contribute an open-source prototype of Glyphboard, a general exchange format for high-dimensional data, and a case study with nine data scientists and domain experts from four exemplary domains in order to evaluate how the different visualization and interaction features of Glyphboard are used.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1077-2626 1941-0506
DOI:	10.1109/TVCG.2020.2969060