visdb: database exploration using multidimensional visualization maithili narasimha 4/24/2001
TRANSCRIPT
![Page 1: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/1.jpg)
VisDB: Database Exploration VisDB: Database Exploration Using Multidimensional Using Multidimensional
VisualizationVisualization
Maithili Narasimha
4/24/2001
![Page 2: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/2.jpg)
VisDBVisDB
Scientific and Geographic databases tend to have large amounts of data.
Some of the challenges in dealing with these databases are:
Mining these databases for useful information is a difficult task due to the sheer volume of data
![Page 3: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/3.jpg)
VisDBVisDB Users do not know what they are looking for
exactly.
With traditional query specification languages, it is not possible to specify vague queries and thus not possible to get approximate results.
There is no feedback. Result set may contain too few or too many points.
![Page 4: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/4.jpg)
VisDB
Requirements for a good Visualization System to explore large databases:
Flexible Query Specification Good Query Feedback Interactive system
![Page 5: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/5.jpg)
VisDBVisDB Also, the users should be able to
view as many data points as possible to see the patterns and clusters.
Display size and resolution are limiting factors
Also necessary to display the interdependencies between data attributes, Hotspots(anomalies).
![Page 6: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/6.jpg)
VisDBVisDB The goal of the VisDB system is to
address the tasks of visualization of the results , and that of incrementally refining the query to provide an effective way to find interesting data properties.
![Page 7: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/7.jpg)
VisDBVisDB The approach.
Use each pixel of the screen to visualize the results.
Provide data items not only fulfilling the result exactly , but also those that match approximately.
![Page 8: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/8.jpg)
VisDBVisDB Approximate results are
determined by a relevance factor. The relevance factor of a data item
is obtained by calculating distances for each selection predicate and combining them.
The more the combined distance, the less the relevance of the data point.
![Page 9: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/9.jpg)
Calculating the Relevance FactorCalculating the Relevance Factor Calculate the distance.
Simple for Quantitative data. Nominal and Ordinal?
Combining distances. User and Query dependent. Weighting Factor for each attribute. Normalizing. Arithmetic Mean for AND and Geometric mean
for OR for combining different condition parts. Relevance Factor is the inverse of the
Combined distance.
![Page 10: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/10.jpg)
VisDBVisDB Basic Visualization Technique
Sort the data points according to their relevance, with respect to the query.
Assign colors depending on the relevance.
Plot the sorted, colored points starting from the center of the screen moving outwards in a rectangular spiral fashion.
![Page 11: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/11.jpg)
Overall Result Plotting
![Page 12: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/12.jpg)
VisDBVisDB To relate the visualization of the overall
result to the visualization of different selection predicates, separate windows for each selected predicate of the query are created and shown along with the result window.
The position of the data items in all the other windows is determined by their position in the overall result window.
![Page 13: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/13.jpg)
Arrangement of Windows for 5D
Data
![Page 14: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/14.jpg)
VisDBVisDB Mapping two dimensions to the axes
It is possible for the user to assign two attributes to the axes and the system will arrange the relevance factors according to the directions of the distance of the data point from the selection predicate.
With this method it is possible to provide better feedback to the user.
However, we may not be able to use the display efficiently in some cases (I.e. some quadrants may not be used fully, while others are saturated)
![Page 15: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/15.jpg)
2D Representation
![Page 16: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/16.jpg)
VisDBVisDB Grouping the dimensions
The pixels corresponding to the different dimensions of one data item are placed in one area instead of distributing them in different windows.
Will require more pixels per dimension per data item.
May provide more useful visualizations for data sets with larger dimensionality.
![Page 17: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/17.jpg)
Grouping multi dimensional data
![Page 18: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/18.jpg)
VisDBVisDB Interactive data exploration
Users initially specify their queries, using some query language.
Inside the VisDB interactive query and visualization interface, it is possible to view the visualizations and perform query modifications.
System provides sliders for modifying selection predicates, weight factors and other options.
![Page 19: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/19.jpg)
VisDBVisDB
![Page 20: VisDB: Database Exploration Using Multidimensional Visualization Maithili Narasimha 4/24/2001](https://reader036.vdocuments.us/reader036/viewer/2022062313/56649f455503460f94c66faa/html5/thumbnails/20.jpg)
VisDBVisDB
Conclusion Useful for identifying and isolating
clusters, correlations and hotspots in large databases.
Good Query specification system. No Zoom or pan for the visualizations.