1. Lecture 09: Interaction pt. 2: Cost
February 20, 2017
SDS235:
Visual Analytics
Note: slide deck adapted from R. Chang

2. 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

3. Recap: questions to ask yourself
What is the goal of the analysis?
What kinds of operations do we need to enable?
How can the visualization support those operations?

4. Recap: Yi, Kang, Stasko and Jacko (2007)
Select: mark something as interesting
Explore: show me something else
Reconfigure: show me a different arrangement
Encode: show me a different representation
Abstract/Elaborate: show me more or less detail
Filter: show me something conditionally
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),

5. Discussion Is this a taxonomy of interactions, or of visualizations?
Are the two separable?
How do we handle interaction on different visualization types?

6. Recap: brushing and linking
Brushing and linking is the linchpin in most visualizations that utilize coordinated multiple views.
Rather than just relaying a change in the data being displayed, this is a relaying of interaction behavior:
Interaction on one view immediately propagates to the other views.
What’s the goal here?
Hypothesis: the nature of Brushing and Linking is to coordinate between different perspectives of the same data elements, especially for data of high dimensionality.

7. 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:
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?

8. Discussion
What did you find?

9. 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?

10. 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).

11. 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

12. 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 (!!)

13. 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)

14. 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

15. 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

16. 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

17. 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

18. 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.

19. 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)

20. Up next Wednesday’s lab:
Recommendation: read through d3js.org/#introduction