The State-of-the-Art of Set Visualization

Research output: Contribution to journalArticle

Details

Original languageEnglish
Pages (from-to)234-260
Number of pages27
JournalCOMPUTER GRAPHICS FORUM
Volume35
Issue number1
StatePublished - 1 Feb 2016
MoE publication typeA1 Journal article-refereed

Researchers

  • Bilal Alsallakh
  • Luana Micallef

  • Wolfgang Aigner
  • Helwig Hauser
  • Silvia Miksch
  • Peter Rodgers

Research units

  • Vienna University of Technology
  • University of Kent
  • St. Pölten University of Applied Sciences
  • University of Bergen

Abstract

Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net. Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations.We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem.

    Research areas

  • information visualization, visualization

ID: 1729245