SumUp : statistical visual query of multivariate data with parallel-coordinate geometry

Phi Giang Pham, Mao Lin Huang, Quang Vinh Nguyen

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

1 Citation (Scopus)

Abstract

One of the most noticeable issues of parallel coordinate visualization is how to quantitatively analyze density caused by polyline growth in a limited space on axes. The existing visualization tools only support the comparison among single dimensions and single ranges of polylines, which could face limitation in cases of complicated analytics. This paper proposes a new visual-query technique, named SumUp, for statistical analysis of multiple attributes of dimensions and multiple ranges of polylines. The methodology of SumUp is primarily based on developing dynamic queries using brushing operations to deliver summary stacked bars adaptive with parallel coordinates. Users can easily observe quantitative information from data patterns and compare multiple attributes over the density of polylines in the parallel coordinate visualization. Early experiments show that our proposed technique could potentially enhance the manipulation on parallel coordinates, showing by a typical case study.
Original languageEnglish
Title of host publicationCooperative Design, Visualization, and Engineering: 13th International Conference, CDVE 2016, Sydney, NSW, Australia, 24-27 October 2016, Proceedings
PublisherSpringer
Pages386-393
Number of pages8
ISBN (Print)9783319467702
DOIs
Publication statusPublished - 2016
EventCDVE (Conference) -
Duration: 24 Oct 2016 → …

Publication series

Name
ISSN (Print)0302-9743

Conference

ConferenceCDVE (Conference)
Period24/10/16 → …

Keywords

  • computer networks
  • information visualization
  • multivariate analysis
  • security measures

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