Visualizing Missing Data: Graph Interpretation User Study

  • Cyntrica Eaton
  • Catherine Plaisant
  • Terence Drizd
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3585)

Abstract

Most visualization tools fail to provide support for missing data. In this paper, we identify sources of missing data and describe three levels of impact missing data can have on the visualization: perceivable, invisible or propagating. We then report on a user study with 30 participants that compared three design variants. A between-subject graph interpretation study provides strong evidence for the need of indicating the presence of missing information, and some direction for addressing the problem.

Copyright information

© IFIP International Federation for Information Processing 2005

Authors and Affiliations

  • Cyntrica Eaton
    • 1
  • Catherine Plaisant
    • 1
  • Terence Drizd
    • 1
  1. 1.Human-Computer Interaction LaboratoryUniversity of MarylandCollege ParkUSA

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