Transcript Interaction in Information Visualization

Interaction &
Dynamic Queries 1
CS 7450 - Information Visualization
February 3, 2005
John Stasko
Interaction
• How do you define “interactive”?
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Response Times
• .1 sec - animation, visual continuity,
sliders
• 1 sec - system response, conversation
break
• 10 sec - cognitive response
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Interaction - 3 Transformations
• Data
(Primary Focus)
 Selecting cases to show
• Visual
 Selecting a different representation
 UI controls for chart/graph/vis
• View
 Selecting the perspective
 Zoom, pan, ...
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Data Transformation
• Selecting what you want to see
• What are some techniques?
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Example
www.digitalhistory.uh.edu/timeline/timeline.cfm
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Data Transformation
• Interaction forms:
 Pop-up tooltips (bubble help)
 Direct walk
 (General) Brushing
 Details-on-demand
 Dynamic query
 Histogram brushing
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Pop-up tooltips
• Hovering mouse
cursor brings up
details of item
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Direct Walk
• Linkages between
cases
• Exploring one may
lead to another
• Example:
 Following hyperlinks
on web pages
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Brushing
• Applies when you have multiple views of
the same data
• Selecting or highlighting a case in one
view generates highlighting the case in
the other views
• Very common technique in InfoVis
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Brushing
Same
item
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Details-on-Demand
• May not be showing all the data due to
scale problem
 May be showing some abstraction of groups
of elements
• Expand set of data to show more details,
perhaps individual cases
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Dynamic Query
• Probably most common technique
• Let’s explore more details...
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DB Queries
• Query language
 Select house-address
From atl-realty-db
Where price >= 200,000 and
price <= 400,000 and
bathrooms >= 3 and
garage == 2 and
bedrooms >= 4
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DB Queries
• Pluses?
• Minuses?
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Typical Query Response
• 124 hits found
 1. 748 Oak St. - a beautiful …
 2. 623 Pine Ave. …
• 0 hits found
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Problems
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Must learn language
Only shows exact matches
Don’t know magnitude of results
No helpful context is shown
Reformulating to a new query can be slow
...
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Dynamic Query
• Specifying a query brings immediate
display of results
• Responsive interaction (< .1 sec) with
data, concurrent presentation of solution
• “Fly through the data”, promote
exploration, make it a much more “live”
experience
 Timesharing vs. batch
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Dynamic Query Constituents
• Visual representation of world of action
including both the objects and actions
• Rapid, incremental and reversible actions
• Selection by pointing (not typing)
• Immediate and continuous display of
results
From: Ahlberg &
Shneiderman,
CHI ‘94
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Imperfection
• Idea at heart of Dynamic Query
 There often simply isn’t one perfect response
to a query
 Want to understand a set of tradeoffs and
choose some “best” compromise
 You may learn more about your problem as
you explore
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Software Demo
• HomeFinder - Univ. of Maryland
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What Did We See?
• Interface
 buttons
 sliders (nominal --> ordinal)
 alphasliders
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Query Controls
• Variable types
 Binary nominal - Buttons
 Nominal with low cardinality - Radio buttons
 Ordinal, quantitative - sliders
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Alphaslider
Goldfinger
A B C DEF G HI J K L M N OP QR S T UVW XYZ
Current
selection
Slider thumb
Slider area
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Index
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Rangeslider
0
100
Low selection
thumb
Real data range
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High selection
thumb
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FilmFinder
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Spotfire
Current
assignment
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Spotfire Features
• Starfield display
• Tight coupling
 features to guide the user
 rapid, incremental, reversible interactions
 display invariants
 continuous display
 progressive refinement
 details on demand
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Nice Application
www.myrateplan.com/cellphones
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Another Example
www.bluenile.com/diamond_search.asp?track=dss
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DQ Strengths
•?
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DQ Strengths
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Work is faster
Promote reversing, undo, exploration
Very natural interaction
Shows the data
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DQ Weaknesses
•?
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DQ Weakness
• Can you formulate an arbitrary boolean
expression?
 !(A1 V A2) ^ A3 V (A4 V A5 ^ A6) V …
• But do people really do this often?
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DQ Weakness
• Controls take space!
 How much in Spotfire?
• Put data in controls...
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Data Visualization Sliders
Low selection
thumb
High selection
thumb
Data distribution
From: Eick, UIST ‘94
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DQ Weakness
• As data set gets larger, real-time
interaction becomes increasingly difficult
• Storage - Data structures
 linear array
 grid file
 quad, k-d trees
 bit vectors
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Brushing Histograms
• Special case of brushing
• Data values represented in histograms
that can be clicked on and selected
(controls region)
• When items selected there, the
corresponding item(s) are highlighted in
main view windows
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BH Example
DataMaps
Maryland
&
Va Tech
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Demo
DQ vs. BH
• Empirical Study
 Use DataMaps, a geographic (US states) data
visualization tool
 Have participants do different tasks with both
methods
How many states have pop between x and y in 1970?
Given 3 states, which has the lowest median income?
What’s the relationship between education and income?
List states with pops. 0->x and y->z.
What kind of a state is Florida?
Q. Li & C. North, InfoVis ‘03
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Functioned more as its own
infovis tool
Findings
• Brushing histograms better and more
highly rated for more complex discovery
tasks
 Attribute correlation, compare, and trend
evaluation
• Dynamic queries better for more simple
range specification tasks
 Single range, multiple ranges, multiple criteria
Functioned more as auxiliary control for other vizs
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Case Study
Attribute Explorer
Video
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Fundamental Idea
• Show all the data, use different displays
for different variables
• Use brushing so that interaction with one
view highlights selections in others
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DQ vs. BH
• Fundamental Differences:
 BH highlights data of interest;
DQ filters unwanted data
 DQ does single range query;
BH allows multiple ranges
 DQ users interact with the query (low,hi);
BH users interact directly with data
 DQ visualizes query formulation (1 way);
BH displays query results too (I/O)
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Li & North, ‘03
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Interaction
• More to come...
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Upcoming
• Interaction and Dynamic Queries 2
 Reading
Chapter 5 again
Fishkin & Stone
• Overview and Detail
• HW4 due in 1.5 weeks
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Sources Used
• Spence, CMS books
• Shneiderman; Ahlberg et al; Tweedie et al
articles
• Chiu & Wang F99 slides
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Extras
• Additional information
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SDM Components
• Object-centered selection
• Dynamic and flexible operations
• SDM handles
• Objects constraints and feedback techniques
• Context persistence
• Set-wide operations
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Advantages
•?
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Advantages
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Focus and context
View occluded objects
View different object sets in different scales
Visualization is not part of the underlying data
Compare the widths and heights of objects at a
distance
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Disadvantages
•?
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Disadvantages
• Object manipulation causes occlusion
• Users cannot operate on parts of objects
• With limited scope, certain objects are occluded
by the focus of objects
• Changing the width/height can blur the linear
relationships between objects
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