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Human-Computer Interaction - INTERACT 2005

Volume 3585 of the series Lecture Notes in Computer Science pp 861-872

Visualizing Missing Data: Graph Interpretation User Study

  • Cyntrica EatonAffiliated withHuman-Computer Interaction Laboratory, University of Maryland
  • , Catherine PlaisantAffiliated withHuman-Computer Interaction Laboratory, University of Maryland
  • , Terence DrizdAffiliated withHuman-Computer Interaction Laboratory, University of Maryland

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.