Transcript VizDB - People

VizDB
A tool to support
Exploration of large databases
By using
Human Visual System
To analyze mid-size to large data
Data Mining Techniques
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Implements several data mining techniques
 Pixel-oriented Techniques
(Spiral, Axes, and
Grouping Techniques)
 Parallel Coordinates
 Stick Figures
Exploration of unto a million data values
Concept
The basic idea for visualizing the data is
to map the distances to colors and
represent each data value by one or
multiple colored pixels.
 Interactivity is the key !
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Requirement

Feedback required when query returns
unexpected results
 Interactivity allows immediate feedback
from a modified query
 Configurable tool, that allows various forms
of data visualization techniques
 Using the human vision system for pattern
recognition
Basic Technique
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Sort query data w.r.t. the relevance and map
relevance factors to colors
Highest relevance factor in the center
Yellow-Green-Blue-Red-Black in decreasing order
of relevance.
Separate window for each selection predicate in
the query
Multiple windows make multi-dimensional
visualization
Mapping 2-D To The Axes

Visualization of inherently 2D or 3D data is
not dealt with in VizDB
 Where no inherent 2D semantics of data
exist, VizDB is a valuable tool. Use of two
axes for two dimensions. Positive as well as
negative values displayed.
 Some space may be wasted .. (Why?)
Grouping

Each area is arranged in a rectangular spiral
shape according to relevance factors
 Coloring is similar to the previous method
 Grouping allows data similar in one
dimension to be grouped together. Data in
multiple dimensions are represented as
clusters of pixels
 Good for larger dimensionality
Interactive Data Exploration
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Dynamic Query Modification Techniques
 Feedback on the results
– Change in color means change in values that are
“relevant”
– Change in structure means overall distribution of data
has changed
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Sliders for discrete as well as continuous values
 Initial Query is SQL or “Gradi”
Calibrations
Calculation of “relevance” factor can be
calibrated by the user
 Starting and ending values for various
numeric data
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– Eg: Blood samples count
What about complex queries?
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Multiple layers of windows for complex
queries using nested AND and OR operators
 Data that satisfies ALL joins is yellow. The
rest is colored according to number of
criteria met
 Works well with the relational databases
Implementations
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C++ with Motif using X Windows on HP
7xx
 Currently being ported to Linux (I couldn’t
get this working! )
Adding new techniques
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More Info Viz. Techniques can be integrated
with the system.
New
 Latest version supports Parallel coordinates, Stick Figures, Pan and zoom Stuff !!
techniques
Applications
Molecular Biology - to find possible
docking regions by identifying sets
surface points with distinct
characteristics.
 Database of geographical data
 Environmental Data
 NASA Earth observation data
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Future Work
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Automatic generation of queries that
Cool !!
correspond to data in specific regions
(Select some data, and the SQL query that
matches that data will get generated..
 Time series visualization
Thank You
The presentation slides are available at
http://filebox.vt.edu/users/adatey/research/Viz
DB.ppt
A small color picture that shows different
techniques
http://filebox.vt.edu/users/adatey/research/Vis
DBHandout.eps