CoSi: Visual Comparison of Similarities in High-Dimensional Data Ensembles

Anja Heim, Eduard Gröller, Christoph Heinzl

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

Comparative analysis of multivariate datasets, e.g. of advanced materials regarding the characteristics of internal structures (fibers, pores, etc.), is of crucial importance in various scientific disciplines. Currently domain experts in materials science mostly rely on sequential comparison of data using juxtaposition. Our work assists domain experts to perform detailed comparative analyses of large ensemble data in materials science applications. For this purpose, we developed a comparative visualization framework, that includes a tabular overview and three detailed visualization techniques to provide a holistic view on the similarities in the ensemble. We demonstrate the applicability of our framework on two specific usage scenarios and verify its techniques using a qualitative user study with 12 material experts. The insights gained from our work represent a significant advancement in the field of comparative material analysis of high-dimensional data. Our framework provides experts with a novel perspective on the data and eliminates the need for time-consuming sequential exploration of numerical data.
Original languageEnglish
Title of host publicationVision, Modeling, and Visualization
EditorsBjoern Andres, Marcel Campen, Michael Sedlmair
PublisherThe Eurographics Association
Pages117-124
Number of pages8
ISBN (Print)978-3-03868-161-8
DOIs
Publication statusPublished - 2021

Keywords

  • Visual Analytics

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