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

Information

• Publication Type: Journal Paper (without talk)
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: October 2021
• DOI: CoSi: Visual Comparison of Similarities in High-Dimensional Data Ensembles
• Journal: VMV: Vision, Modeling, and Visualization
• Open Access: yes
• Pages: 1 – 8

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.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• DOI: CoSi: Visual Comparison of Similarities in High-Dimensional Data Ensembles

BibTeX

@article{Heim_2021,
  title =      "CoSi: Visual Comparison of Similarities in High-Dimensional
               Data Ensembles",
  author =     "Anja Heim and Eduard Gr\"{o}ller and Christoph Heinzl",
  year =       "2021",
  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.",
  month =      oct,
  doi =        "CoSi: Visual Comparison of Similarities in High-Dimensional
               Data Ensembles",
  journal =    "VMV: Vision, Modeling, and Visualization",
  pages =      "1--8",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2021/Heim_2021/",
}