VizDBVizDB

A tool to support

Exploration of large databases

By using

Human Visual System

To analyze mid-size to large data

Data Mining TechniquesData Mining Techniques

Implements several data mining techniques Pixel-oriented Techniques (Spiral, Axes, and

Grouping Techniques) Parallel Coordinates Stick Figures

Exploration of unto a million data values

ConceptConcept

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 !

RequirementRequirement

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 TechniqueBasic Technique

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 AxesMapping 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?)

GroupingGrouping

Each area is arranged in a rectangular spiral shape according to relevance factors

Coloring is similar to the previous methodGrouping 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 ExplorationInteractive Data Exploration

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

Sliders for discrete as well as continuous values Initial Query is SQL or “Gradi”

CalibrationsCalibrations

Calculation of “relevance” factor can be calibrated by the user

Starting and ending values for various numeric data – Eg: Blood samples count

What about complex queries?What about complex queries?

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

ImplementationsImplementations

C++ with Motif using X Windows on HP 7xx

Currently being ported to Linux (I couldn’t get this working! )

Adding new techniquesAdding new techniques

More Info Viz. Techniques can be integrated with the system.

Latest version supports Parallel co-ordinates, Stick Figures, Pan and zoom techniques

New Stuff !!

ApplicationsApplications

Molecular Biology - to find possible docking regions by identifying sets surface points with distinct characteristics.

Database of geographical dataEnvironmental DataNASA Earth observation data

Future WorkFuture Work

Automatic generation of queries that correspond to data in specific regions (Select some data, and the SQL query that matches that data will get generated..

Time series visualization

Cool !!

Thank You Thank You

The presentation slides are available at

http://filebox.vt.edu/users/adatey/research/VizDB.

ppt

A small color picture that shows different techniques

http://filebox.vt.edu/users/adatey/research/VisDBHandout.eps