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Dynamic Queries –presented by Bhaskar Chatterjee Visual Alternative to SQL for Querying databases Depending on data types and the values decides the input.

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Presentation on theme: "Dynamic Queries –presented by Bhaskar Chatterjee Visual Alternative to SQL for Querying databases Depending on data types and the values decides the input."— Presentation transcript:

1 Dynamic Queries –presented by Bhaskar Chatterjee Visual Alternative to SQL for Querying databases Depending on data types and the values decides the input controls for the search Examples are Buttons, Ratio Buttons, Simple sliders and Range Sliders etc Two papers: deals with the rationale for dynamic queries and also go over two Applications: Home Finder, Film Finder

2 Dynamic Queries Constantly need to update queries as users adjust sliders or select buttons Visual representation of query Visual representation of results Rapid and incremental control of query Immediate and continuous feedback

3 Advantages Users can “fly through data” by adjusting sliders Novice: formulating query at command line leads to errors in syntax and understanding Experts: interpretation of results can be easier-air traffic controllers, demographers, statisticians

4 Examples: Geographic applications

5 Response of 18 Subjects using HomeFinder

6 Example: Cancer Rates in US

7 Example (Education Application)

8 Alphanumeric tabular display: directory display in UNIX This lets users explore UNIX directory by size and age Three versions developed Highlighting matches with color Highlighting matches with asterisk Displaying only the matching lines and hiding the rest

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12 Disadvantages observed The dynamic query is poorly matched with the current hardware and software systems Current database tools cannot satisfy the requirements for rapid searches Application specific programming is required to take advantage of the dynamic query methods. Standardized input output software are required to integrate to existing system Visually handicapped find it more difficult

13 Research Directions Database and display algorithms To handle rapid display updates Special data structures kept in rapid storage can handle rapid algorithms Data organized in buckets, for example 1 to 50000 can be organized in 100 buckets (each having 500 data points) Use of parallel hardware and algorithms, data compression to store large amounts of data

14 Research (Contd.) User interface design People should be able to grasp the content of the picture Questions: How to allow user to use Boolean combination of slider settings Choose among highlighting among color, points of light etc. Allow varying degrees of intensity, large points/zooming

15 Other Research Issues Display Issues: What color, size and shape to use ? How to represent overlapping data on a map? Input Issues: Widget design is a central issue: Limits and display of Current Values, number of boxes Multidimensional input ( currently they are clumsy) – research is in 3D mouse: 6 degree of freedom.

16 Examples of 2-Dimensional input

17 Visual Information Seeking: Tight coupling with dynamic queries and Starfield Display Dynamic Queries Filter: query parameters rapidly adjusted with slider, buttons etc. Starfield Display: result sets are continuously available and support viewing of hundreds or thousands of items Tight Coupling: query components are interrelated in ways that preserve display invariants and support progressive refinement.

18 Tight Coupling Tight coupling reveals the software state and constrains the user from making erroneous actions For example: if a user wants films before 1935 then only certain actors and directors are further selectable. Tight coupling aspect: every output of query is a candidate for input of a another query Helps in reducing screen clutter

19 Tight Coupling (Contd.) Other Aspects : Progressive refinement of query Details on demand : idea of hypermedia Click on the data points to get further information

20 FilmFinder

21 FilmFinder (Contd.)

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