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The Cost-of-Knowledge Characteristic Function: Display Evaluation for Direct-Walk Dynamic Information Visualizations

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The Cost-of-Knowledge Characteristic Function: Display Evaluation for Direct-Walk Dynamic Information Visualizations CHI 94 Card, Pirolli, & Mackinlay – PowerPoint PPT presentation

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Title: The Cost-of-Knowledge Characteristic Function: Display Evaluation for Direct-Walk Dynamic Information Visualizations


1
The Cost-of-Knowledge Characteristic
Function Display Evaluation for Direct-Walk
Dynamic Information Visualizations
  • CHI 94
  • Card, Pirolli, Mackinlay

2
Concepts
  • Information has cost structure
  • Objective maximize information benefits per unit
    cost (cost time)
  • Cost-of-Knowledge Characteristic Function
  • Characterizes the effect of a design of dynamic
    display/human-computer dialogue on informations
    cost structure

3
Cost-of-Knowledge Characteristic Function
  • Improve productivity Less time or more output

4
Case study
  • Direct-walk interactive infoviz
  • Navigate an information structure using mouse
    points/other direct manipulation methods
  • Analyze 2 calendar programs Spiral Calendar vs.
    Suns CM
  • Users 4 users for each study, 2 overlapping
  • Task navigate to another day in calendar

5
Steps To Construct Cost-of-Knowledge Function
  • Use tasks that take different amount of time to
    obtain different amount of information
  • Identify cost drivers for the tasks
  • In Spiral Calendar of cycles to go through
  • In CM of different steps
  • Measure time taken to perform each task as cost
  • Perform regression of time (cost) as dependent
    variable and cost drivers as independent
    variables
  • Plot cost vs. amount of information that can be
    obtained

6
Cost Drivers
  • Spiral Calendar Number of display cycles
    (Century, Decade, Year, Month, Week, Day)
    selected
  • Regression fn Time 3.3 3.5 Ncycles
  • CM
  • m point, menu pull-down, select
  • P point select
  • B press a button
  • Regression fn Time 1.3 3.9 m 1.4 P 0.36
    B

7
Spiral Calendar Result Computation
8
Sun CM Result Computation
9
Cost-of-Knowledge Functions
10
Value of Tasks
  • Values of tasks
  • Frequency
  • Importance
  • Etc.
  • Needs to weight tasks by their values
  • Ex. Use probability density function to weight
    tasks by frequency of use
  • PrneededD days ago0.34/(0.34D0.83)

11
Expected Probability-Weighted Costs
12
Summary
  • More measurable/computable method to evaluate a
    design
  • Know your priority/objective sometimes perceived
    speed is more important than actual speed
  • Issues
  • How to accurately identify and measure all cost
    drivers of a task, e.g. of items?
  • What if there are more than one way to perform a
    specific task?

13
The WebBook Web Forager An Information
Workspace for the World-Wide Web
  • CHI 96
  • Card, Robertson, and York

14
WebBook Web Forager
  • Two related designs
  • WebBook - 3D interactive book of HTML pages
  • Web Forager an application that puts WebBook
    and other objects in a 3D hierarchical workspace

15
Based On
  • Cost structure of information workspaces the
    web has a uniform cost structure
  • Information foraging theory users often seek
    strategies to increase the encounter rates of
    relevant information
  • Locality of reference users tend to interact
    repeatedly with small clusters of information,
    and therefore keeping the cost of accessing low

16
Problems At That Time
  • Hotlist still have to wait for slow access
    times, not tunable to a reasonably
    cost-structured workspace.
  • Multiple windows slow users down since they
    overlap.
  • Users can only be at one page while the way the
    users actually work with information is to have
    multiple pages simultaneously available at hand.

17
WebBook
  • Use book metaphor (animated 3D) next previous
    links analogous to books, familiar, effective
    display
  • Any collection of preload pages
  • Can be bookmarked, put on a shelf
  • Various way to collect URLs relative-URL, Topic,
    Hot List, Search Reports

18
Web Forager
  • Explore the potential for rapid interaction with
    large number of pages
  • Use gestures to increase speed with which objects
    can be moved around
  • Focus on the web
  • Use a structured model to design (CoKC Fn)
  • 3 levels book/page ? air desk ? bookcase

19
Web Forager
20
Cost of Knowledge Characteristic Function for Web
Forager
21
Comments
  • Metaphor do they really take advantage of the
    affordances of a physical book and workspace?
    What might you lose from using this metaphor?
  • Speed of retrieving a web page is becoming less
    an issue
  • Current browsers might already be able to solve
    the problems posed by the authors (and even work
    better, perhaps!)

22
Effective View Navigation
  • CHI 97
  • Furnas

23
Effective View Navigation
  • Context Navigate an information structure by
    selecting something in the current view of the
    structure
  • Problems
  • Large structures
  • Limited resources of space time
  • Proposed Requirements Effective View Navigation
    (EVN) Effective View Traversibility (EVT)
    View Navigability (VN)

24
Terms
  • View traversal iterative process of viewing,
    selecting, moving to it
  • View navigation decide where to go next
  • Logical graph logical structure of the
    information
  • Viewing graph contains nodes that users see in
    current view

25
EVT Requirements for Viewing Graphs
  • EVT1 Small Views space constraint of
    outgoing links of any node relative to
    structures size must be small ? small Maximal
    Out-Degree (MOD)
  • EVT2 Short paths time constraint
  • the longest connecting path relative to
    structures size must be small ? small Diameter
    (DIA)
  • EVT(G)(MOD(G),DIA(G))
  • G viewing graph

26
A Scrolling List
EVT(O(1), O(n))
27
A Balanced Tree
EVT(O(1), O(log n))
28
Improving EVT of a List
  • More dimensions - multi-column list EVT(O(1),
    O(sqrt(n)))

29
Improving EVT of a List
  • Fisheye sampling EVT(O(log n), O(log n))
    allow jumping further, but larger view

30
Improving EVT of a List
  • Adding a tree EVT(O(1), O(log n)) create
    categorization?

31
EVT Summary
  • Present information in a representation that
    naturally supports EVT - tree
  • To fix non-EVT logical structures
  • Add long-distance links
  • Glue with another complete EVT structure

32
View Navigability (VN)
  • Ability to find good paths to targets without
    error history-less

33
Terms
  • Outlink-info info associated with outlink of a
    node (enumeration or labeling)
  • To-set all possible targets a link actually
    leads to
  • Inferred-to-set targets that the outlink-info
    seem to indicate
  • Residue/scent remote indication of a node/target
  • Well-matched outlink info inferred-to-set
    implies to-set

34
Illustration
35
Strong Navigability Requirement
  1. Outlink-info must be everywhere well-matched
  2. Every node must have good residue at every other
    node
  3. Outlink-info must be small, but need to describe
    the whole to-set, not just the next node (e.g.
    highway signs)
  4. Semantic labeling that mirrors actual partition
    of to-sets

Targets share residue
36
Good Example
  • Systematic labeling of trees of hierarchy, i.e.
    biological taxonomy

37
Non-Navigable Structure
  • Completely unrelated/unstructured items
  • Only works with enumeration
  • Locally-related structure no good residue for
    things far away, e.g. WWW
  • Combine query navigation

38
Combining EVT VN
  • Large scale semantics (structure with larger
    groups) work!
  • Assume n nodes v links in the structure
  • Small view diameter v should be small compared
    to n
  • Average size of to-sets (n/v) should be large
  • Carve up the semantics of the domain efficiently
    due to Small Diameter req.
  • Small of intersections
  • Balanced hierarchy

39
Summary
  • Effective view navigation
  • Small views
  • Reasonable of steps to move around
  • Discoverable route to any target
  • Do navigability requirements guarantee users to
    always find shortest paths?
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