ChronoView: Visualization technique for many temporal data

Satoko Shiroi*, Kazuo Misue, Jiro Tanaka

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

This paper presents a method of visualizing data that contains temporal information, such as a human's behavior and the time at which it occurs. A feature of the data is that each event may have one or more time-stamps. By analyzing this kind of data, we are able to find some behavioral patterns and obtain knowledge applicable to many fields, such as marketing research and security. We develop ChronoView, a visualization technique to support the analysis of data with temporal information. ChronoView represents an event with a set of time-stamps as a position inside a circle, similar to the dial of an analog clock. By representing each event as a position on a two-dimensional plane, we can simultaneously visualize many events and easily compare their occurrence patterns. We implement a tool based on ChronoView, which is enriched with additional functions and overcomes the drawbacks of the original system. A use case involving tweet data from Twitter illustrates the use and practicality of ChronoView.

Original languageEnglish
Title of host publication2012 16th International Conference on Information Visualisation, IV 2012
Pages112-117
Number of pages6
DOIs
Publication statusPublished - 2012 Oct 31
Externally publishedYes
Event2012 16th International Conference on Information Visualisation, IV 2012 - Montpellier, France
Duration: 2012 Jul 112012 Jul 13

Publication series

NameProceedings of the International Conference on Information Visualisation
ISSN (Print)1093-9547

Other

Other2012 16th International Conference on Information Visualisation, IV 2012
Country/TerritoryFrance
CityMontpellier
Period12/7/1112/7/13

Keywords

  • event
  • periodicity
  • temporal information
  • time-stamp

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition

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