Paper Info
Title
Pargnostics: screen-space metrics for parallel coordinates.
Abstract
Interactive visualization requires the translation of data into a screen space of limited resolution. While currently ignored by most visualization models, this translation entails a loss of information and the introduction of a number of artifacts that can be useful, (e.g., aggregation, structures) or distracting (e.g., over-plotting, clutter) for the analysis. This phenomenon is observed in parallel coordinates, where overlapping lines between adjacent axes form distinct patterns, representing the relation between variables they connect. However, even for a small number of dimensions, the challenge is to effectively convey the relationships for all combinations of dimensions. The size of the dataset and a large number of dimensions only add to the complexity of this problem. To address these issues, we propose Pargnostics, parallel coordinates diagnostics, a model based on screen-space metrics that quantify the different visual structures. Pargnostics metrics are calculated for pairs of axes and take into account the resolution of the display as well as potential axis inversions. Metrics include the number of line crossings, crossing angles, convergence, overplotting, etc. To construct a visualization view, the user can pick from a ranked display showing pairs of coordinate axes and the structures between them, or examine all possible combinations of axes at once in a matrix display. Picking the best axes layout is an NP-complete problem in general, but we provide a way of automatically optimizing the display according to the user’s preferences based on our metrics and model.
Year
DOI
Venue
2010
10.1109/TVCG.2010.184
IEEE Trans. Vis. Comput. Graph.
Keywords
Field
DocType
computational complexity,data visualisation,interactive programming,matrix algebra,parallel programming,program diagnostics,NP-complete problem,interactive visualization,matrix display,parallel coordinates diagnostics,pargnostics,screen space,screen-space metrics,Parallel Coordinates,display optimization,metrics,visualization models.
Computer vision,Histogram,Data visualization,Ranking,Visualization,Computer science,Theoretical computer science,Interactive visualization,Parallel coordinates,Pixel,Artificial intelligence,Computational complexity theory
Journal
Volume
Issue
ISSN
16
6
1077-2626
Citations 
PageRank 
References 
30
1.08
22
Authors
2
Name
Order
Citations
PageRank
Aritra Dasgupta117512.02
Robert Kosara2102567.46