Dynamic Queries for Visual Information Seeking Ben Shneiderman Jin Tong Hyunmo Kang Cmsc838 Sep. 28, 1999

Outline Dynamic Queries Examples of DQ Applications Advantages of DQ Disadvantages of DQ Enhance DQ via Movable Filters (Magic Lens) Video Clip of Magic Lens Boolean Queries by Composition Example of Query Composition Conclusion and Critique

Favorite Sentence “Visualization offers a method for seeing the unseen”

Dynamic Queries Interactive user control Visual query parameters adjustment Animated visual display of query results

Why They Are Good For novices: For power users: - Don't have to learn SQL - Avoid syntax errors - Natural, aid comprehension For power users: - Helpful in finding patterns - Explore and discover

Home Finder

Home Finder (Text)

UNIX - Ls

Chemical Table

Dynamaps

Filmfinder

Global Change Master Directory

User Study Results

Advantages Visual presentation of query components Visual presentation of results Rapid, incremental and reversible actions Selection by pointing (user interface improvement: what about voice command) Immediate and continuous feedback (related: tight-coupling of DQ filters)

Disadvantages and Research Directions DBMS and display related performance problems * Data accessing algorithms * Display/screen management User interface (domain dependent)

Disadvantages and Research Directions (Cont.) GUI issues (widgets, representations, etc) Input methods Novel user interface for complex queries

Filter/flow Map

Enhanced Dynamic Queries Via Movable Filters Ken Fishkin Maureen C. Stone

Restrictions of Dynamic Queries (Motivation) The number of attributes is limited by the number of selectors The effect of combining slider filters is strictly conjunctive The effects of the selectors are global The number of selectors is fixed in advance

Enhanced Dynamic Queries Via Movable Filters Combining the two techniques : The starfield display, the movable filter Enhancing the starfileld display by augmenting it with the flexibility and the functionality of the movable filter

Boolean Queries By Composition Lens L=(F, M) - F : filter Describing the output calculation for the filter on some datum - M : boolean operator Describing how that output is combined with the output from lower filters

Example of Composition L1=(F1, OR), L2=(F2, AND) - L1 over L2  (F1 OR F2) - L2 over L1  (F2 AND F1) N=(NULL, NOT) : inverting lens Compound lens - (F1 AND F2) OR (F3 AND F4)

Examples :. - Database : US Census Data Examples : - Database : US Census Data - Lens Manager Server : X Window System

Example of Composition

Example of Composition

Alternate Views

Simultaneous Multiple Views

Boolean Filter

Extensions : Real-valued Filter

Extensions : Real-valued Filter

Missing Data

Missing Data

Conclusion Expressive yet easy to understand Powerful queries(boolean and real-valued) Visual and semantic transformation of the data (callout, magnification, missing data, sorting, and so forth) Wide range of interface operations (click-through tools)

Critique No statistics on the usability tests Need rapid search & rapid graphical display Application specific programming

Favorite Sentence “There is a tension in the database query systems between providing expressive power and ease of use”