ScagExplorer: Exploring scatterplots by their scagnostics

Tuan Nhon Dang, Leland Wilkinson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

60 Scopus citations


A scatter plot displays a relation between a pair of variables. Given a set of v variables, there are v(v -1)/2 pairs of variables, and thus the same number of possible pair wise scatter plots. Therefore for even small sets of variables, the number of scatter plots can be large. Scatter plot matrices (SPLOMs) can easily run out of pixels when presenting high-dimensional data. We introduce a theoretical method and a testbed for assessing whether our method can be used to guide interactive exploration of high-dimensional data. The method is based on nine characterizations of the 2D distributions of orthogonal pair wise projections on a set of points in multidimensional Euclidean space. Working directly with these characterizations, we can locate anomalies for further analysis or search for similar distributions in a large SPLOM with more than a hundred dimensions. Our testbed, ScagExplorer, is developed in order to evaluate the feasibility of handling huge collections of scatter plots.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE Pacific Visualization Symposium, PacificVis 2014
PublisherIEEE Computer Society
Number of pages8
ISBN (Print)9781479928736
StatePublished - 2014
Event2014 7th IEEE Pacific Visualization Symposium, PacificVis 2014 - Yokohama, Kanagawa, Japan
Duration: Mar 4 2014Mar 7 2014

Publication series

NameIEEE Pacific Visualization Symposium
ISSN (Print)2165-8765
ISSN (Electronic)2165-8773


Conference2014 7th IEEE Pacific Visualization Symposium, PacificVis 2014
CityYokohama, Kanagawa


  • Design Methodology-Pattern analysis
  • High-Dimensional Visual Analytics
  • Leader algorithm
  • Scagnostics
  • Scatterplot matrix
  • forced-directed layout


Dive into the research topics of 'ScagExplorer: Exploring scatterplots by their scagnostics'. Together they form a unique fingerprint.

Cite this