Visualizing Missing Data: Graph Interpretation User Study
- Cite this paper as:
- Eaton C., Plaisant C., Drizd T. (2005) Visualizing Missing Data: Graph Interpretation User Study. In: Costabile M.F., Paternò F. (eds) Human-Computer Interaction - INTERACT 2005. INTERACT 2005. Lecture Notes in Computer Science, vol 3585. Springer, Berlin, Heidelberg
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.