An efficient framework for generating storyline visualizations from streaming data

Yuzuru Tanahashi, Chien Hsin Hsueh, Kwan-Liu Ma

Research output: Contribution to journalArticlepeer-review

41 Scopus citations


This paper presents a novel framework for applying storyline visualizations to streaming data. The framework includes three components: a new data management scheme for processing and storing the incoming data, a layout construction algorithm specifically designed for incrementally generating storylines from streaming data, and a layout refinement algorithm for improving the legibility of the visualization. By dividing the layout computation to two separate components, one for constructing and another for refining, our framework effectively provides the users with the ability to follow and reason dynamic data. The evaluation studies of our storyline visualization framework demonstrate its efficacy to present streaming data as well as its superior performance over existing methods in terms of both computational efficiency and visual clarity.

Original languageEnglish (US)
Article number7015617
Pages (from-to)730-742
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number6
StatePublished - Jun 1 2015


  • layout algorithms
  • Storyline visualization
  • streaming data
  • time-varying data

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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