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If someone learns Tableau and is interested, Prof. Schneiderman would appreciate a 10-15 min presentation about it.

Goals for the application project:

  • Deep experience with a particular tool
  • Learning thought patterns of an analyst
  • 3 "juicy" headlines and 500-1000 words

It's ok to use more than one tool (compare and contrast them).

Some groups already on team website.

Help was solicited for various projects:

  • Undergraduate class scheduling
  • Versioning machine
  • Geospatial accident visualization w/ filtering
  • Temporal visualization of medical or weblog data


  • Initial project proposal is due 26 Feb.
  • Next deliverable will be an annotated bibliography.

There was also a brief discussion of the midterm exam. There will be at least one question of the form "design a visualization for this data set."

Observation: it's difficult to detect patterns when all the data are categorical.

Question: what is the definition of "interesting" in a temporal data set?

Paper Presentation

Lin, J., Keogh, E., Lonardi, S., Visualizing and discovering non-trivial patterns in large time series databases, Information Visualization 2005, Vol 4, No 2 http://www.palgrave-journals.com/ivs/journal/v4/n2/pdf/9500089a.pdf

Two papers using other methods for time series visualization are:

What are we looking for?

  • Motif - frequently occurring pattern
  • Anomaly - infrequently occurring pattern


  • Semantic representation - SAX (Semantic Aggregate approXimation):
    • Turns a time series into a series of letters
    • Number of letters is manually chosen
    • All letters are equally probable
    • Each period categorized as a letter
  • Sequence trees
    • Each item in a sequence is encoded as a path in the tree
    • Easy to see motifs and anomalies
  • Numerosity reduction
    • Non-overlapping windows
    • Recording only different patterns
  • Series comparison metrics
    • Support
    • Confidence
    • "Surprisingness"

Demo of Viztree.

Viztree features:

  • Tree structure visualization
  • Mapping using color and thickness
  • Automatic pattern identification (speed and generality)
  • Simultaneous view of subsequence matches
  • Level/section zooming

Viztree wishlist:

  • Dynamic parameter response
  • Automatic suggestion for parameter
  • Individual subsequence selection in time-zoom panel
  • HCIL-style selectors for tree focus

Related work:

  • Calendar clusters
  • Spirals

Future work:

  • Automatic periodicity detection


  • Better motif recognition with smaller parameters (ie. more data compression)
  • Conversion to character strings results in great increases in processing speed

State of the Union

Looking for term usage spikes with Spotfire.

Changes in control panel.

Interesting terms:

  • drops: "budget" and "weapons"
  • highly variable: "world" and "social"
  • spike: "security" and "sadaam"
  • low variance: "cheney" and "bless"

Future work on this topic is possible.