The role of experience and culture in computer graphing and graph interpretive processes
SIGDOC '99 Proceedings of the 17th annual international conference on Computer documentation
Visualizing gridded datasets with large number of missing values (case study)
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Knowing what we don't know: how to visualize an imperfect world
ACM SIGGRAPH Computer Graphics
Communications of the ACM
Procedural annotation of uncertain information
Proceedings of the conference on Visualization '00
Analysis of visualisation requirements for fuzzy systems
Proceedings of the 1st international conference on Computer graphics and interactive techniques in Australasia and South East Asia
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
A Taxonomy of Visualization Techniques Using the Data State Reference Model
INFOVIS '00 Proceedings of the IEEE Symposium on Information Vizualization 2000
Visualizing Data with Bounded Uncertainty
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
APPROACHES TO UNCERTAINTY VISUALIZATION
APPROACHES TO UNCERTAINTY VISUALIZATION
Restorer: a visualization technique for handling missing data
VIS '94 Proceedings of the conference on Visualization '94
The Challenge of Missing and Uncertain Data
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Discussion: Interacting with parallel coordinates
Interacting with Computers
CandidTree: visualizing structural uncertainty in similar hierarchies
Information Visualization
CandidTree: visualizing structural uncertainty in similar hierarchies
INTERACT'07 Proceedings of the 11th IFIP TC 13 international conference on Human-computer interaction - Volume Part II
Exploring incomplete data using visualization techniques
Advances in Data Analysis and Classification
Comparing averages in time series data
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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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.