LECTURE 09:
INTERACTION PT. 2: COST
February 20, 2017
SDS235:
Visual Analytics
Note: slide deck adapted from R. Chang
Announcements
• 54/56 submitted A1
• Feedback should be out by the end of the week
• Remember to submit your labs; I’ll be updating the
gradebook later this afternoon
Recap: questions to ask yourself
1. What is the goal of the analysis?
2. What kinds of operations do we need to enable?
3. How can the visualization support those operations?
Recap: Yi, Kang, Stasko and Jacko (2007)
1.
Select: mark something as interesting
2.
Explore: show me something else
3.
Reconfigure: show me a different arrangement
4.
Encode: show me a different representation
5.
Abstract/Elaborate: show me more or less detail
6.
Filter: show me something conditionally
7.
Connect: show me related items
Yi, J. S., ah Kang, Y., Stasko, J. T., & Jacko, J. A. (2007). Toward a deeper understanding
of the role of interaction in information visualization. Visualization and Computer Graphics,
IEEE Transactions on, 13(6), 1224-1231.
Discussion
• Is this a taxonomy of interactions, or of visualizations?
• Are the two separable?
• How do we handle interaction on different visualization
types?
Recap: brushing and linking
Activity: interactive visualization with d3
Form groups of 2 to 4 people,
and go to
bit.ly/examples-d3
Choose an example that’s interesting to you,
and try to answer the following:
1.
2.
3.
4.
What questions do you want to ask about this data?
What high and low level interactions are available?
How do you ask your questions using those interactions?
Are there questions you can’t figure out how to ask?
Discussion
What did you find?
Interaction: Benefits and Costs
• So far, we’ve talked about interaction (at all levels) in
terms of what it enables
- Maintaining context
- Supporting hypothesis generation
- Etc.
• Question: are there any downsides? Costs?
• Put another way: how do we decide when it’s worth it?
Interaction Costs
Lam (2008) surveyed 484 papers, tried to break
down “cost” into logical parts:
Lam, Heidi. "A framework of interaction costs in information visualization."
IEEE transactions on visualization and computer graphics 14.6 (2008).
Decision costs ( goals)
• How hard is it to decide where to start?
• Human intuition: give me more choices!
• Caveat: decisions require effort
• As interfaces become more complex and display more
data points, users may need to decide to decide on
- a subset of data
- interface options
System-power costs ( system operations)
• Once a person has decide on a question they want
answered, how hard is it to translate it into logical
operations?
• Deciding on the correct operation sequences may be
difficult (especially for complex systems)
• When the set of available operations isn’t immediately
clear, users may have expectations based on previous
systems (!!)
Multiple input mode costs ( physical sequences)
• Given a sequence of logical actions, how hard is it to
figure out how to perform them?
• Translating system operations to device operations may be
difficult due to:
-
inconsistent mode operations on multiple views (e.g. zooming)
mode change with inadequate visual feedback (e.g. MS ribbons)
overloaded input controls (e.g. gesture-based interaction)
Physical-motion costs ( execute sequences)
• Once you’ve set a sequence of actions to perform, how
hard is it to physically execute them?
• Fitts’ Law can estimate actions performed with a mouse
MT = a+b*log2(A/W +1)
where
- MT is average movement time
- A is distance between the two targets,
- W is the width of the target
- and a and b are experiment constants
Visual-cluttering costs ( perceive state)
• Given a visual representation, how hard is it to perceive
the system state?
• Interaction such as mouse hovering can cause visual
cluttering that makes state perception difficult.
Image courtesy Lynn Cherny of GhostWeather R&D
View-change costs ( interpret perception)
• Given a sequence of two views, how hard is it to reorient
after changing between them?
• View changes require re-interpretation
• Interpretation requires association of:
- temporal objects, as in zooming
- spatial objects, as in view coordination
- local and global objects, as in navigation
State-change costs ( evaluate interpretation)
•
Given a sequence of two logical states, how hard is it to
reorient yourself (or get back to where you started)?
•
Data analysis often requires reflection on multiple data
views or analysis states
•
Lack of refinding support may inhibit exploration.
•
Fisheye vs. coordinated frames
Total Cost (according to Lam)
t_cost(…)=
cost(startup) +
cost(filtering) +
cost(decomposing_to_actions) +
cost(translating_to_logical_actions) +
cost(translating_to_physical_actions) +
cost(executing_physical_actions) +
cost(percieve_system_state) +
cost(reorient_after_view_change) +
cost(reorient_after_state_change)
Ouch.
Discussion: what of this can we control?
t_cost(…)=
cost(startup) +
cost(filtering) +
cost(decomposing_to_actions) +
cost(translating_to_logical_actions) +
cost(translating_to_physical_actions) +
cost(executing_physical_actions) +
cost(percieve_system_state) +
cost(reorient_after_view_change) +
cost(reorient_after_state_change)
Up next
• Wednesday’s lab:
• Recommendation: read through d3js.org/#introduction