Density Displays for Data Stream Monitoring
Ming Hao, Daniel A. Keim, Umeshwar Dayal, Daniela Oelke, Chantal Tremblay
In Computer Graphics Forum, 27(3), 2008.
Abstract: In many business applications, large data workloads such as sales figures or process performance measures need to be monitored in real-time. The data analysts want to catch problems in flight to reveal the root cause of anomalies. Immediate actions need to be taken before the problems become too expensive or consume too many resources. In the meantime, analysts need to have the "big picture" of what the information is about. In this paper, we derive and analyze two real-time visualization techniques for managing density displays: (1) circular overlay d isplays which visualize large volumes of data without data shift movements after the display is full, thus freeing the analyst from adjusting the mental picture of the data after each data shift; and (2) variable resolution density displays which allow users to get the entire view without cluttering. We evaluate these techniques with respect to a number of evaluation measures, such as constancy of the display and usage of display space, and compare them to conventional d isplays with periodic shifts. Our real time data monitoring system also provides advanced interactions such as a local root cause analysis for further exploration. The applications using a number of real-world data sets show the wide applicability and usefulness of our ideas.
Article URL: http://dx.doi.org/10.1111/j.1467-8659.2008.01222.x
BibTeX format:
@article{Hao:2008:DDF,
  author = {Ming Hao and Daniel A. Keim and Umeshwar Dayal and Daniela Oelke and Chantal Tremblay},
  title = {Density Displays for Data Stream Monitoring},
  journal = {Computer Graphics Forum},
  volume = {27},
  number = {3},
  pages = {895--902},
  year = {2008},
}
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