Dynamic Queries –presented by Bhaskar Chatterjee

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

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.)

22. FilmFinder (Contd.)

23. FilmFinder (Contd.)