Magic Lenses for Interactive Database Visualization - PowerPoint PPT Presentation

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Magic Lenses for Interactive Database Visualization

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Title: Magic Lenses for Interactive Database Visualization


1
Magic Lenses for Interactive Database
Visualization
  • Ken Fishkin
  • SoftBook Press, Inc.

2
Standard WIMP
  • all windows are opaque, self-contained
  • exception zoom lenses are nice

3
Magic Lenses
  • Magic Lenses are Windows which know about whats
    below them, and/or whats above them.
  • They can alter input, output, or both.
  • They can be composed

4
Magic Lenses - click through
  • wouldnt it be nice if I could click through a
    zoom lens?

5
Magic Lenses - composable
  • and even nicer if they could compose?

6
Magic Lenses - semantic
  • and even nicer if they could be non-graphical?

7
Magic Lenses - inter-app
  • And even nicer if semantics were F(other windows)?

8
To Recap
  • Magic Lenses are Windows which know about whats
    below them, and/or whats above them.
  • They can alter input, output, or both.
  • They can be composed
  • 3D possible

9
Overall flow
(many)
10
How do you implement it?
  • Purely graphical lenses
  • trap calls to event manager (input), graphics
    engine (output)
  • Semantic lenses
  • shared data, and/or protocol for passing objects
  • Speed a big issue
  • lots and lots of caching

11
What This Buys You
  • Multiple foci context

12
Reify modes into objects
13
Composability gives you spatial Unix pipes.
  • Lets use it for data visualization...

14
Traditional Database Queries
  • Use a Special Language
  • select title from movies where lead_actorConnery
    , Sean and (year lt 1960 or year gt 1975)
  • Batch, non-visual

15
Visual Representation of Databases
  • Map each record to a point on the plane
  • Since 1854 (at least)

16
Dynamic Queries (example 1)
  • One selector per attribute

17
Dynamic Queries (example 2)
  • Selectors filter the display

18
Dynamic Queries (limitations)
  • designed for a small number of attributes
  • only global filters
  • cant screen on an attribute more than once
  • no disjunctions
  • limited query set

19
Hybrid Techniques
  • language for leaves of the query,
  • visual interface for compound queries
  • Still not all queries supported

Content Date Content
Contains is before contains
Document Management 05/01/94 Visual Recall OS
And
Or
20
Magic Lenses
  • Movable local filters, which transform the data
    underneath them in some way, be it visual
    (magnifying lens), semantic (misspelled words),
    or other

21
Merging Lenses into Queries
  • Put one attribute selector on a lens.

22
Free Wins(1) - local filters
23
2 - repeated attributes
24
3 - arbitrary number of attrs.
  • Just stack em up.

25
Consistent UI
26
Query Power
  • 2.5D order of windows implies a
    composition/evaluation order
  • Put an AND/OR toggle on the lens to indicate how
    it should compose
  • A AND B --gt ltA,ANDgt above ltBgt
  • A OR B --gt ltA,ORgt above ltBgt

27
And/or in action
28
Query Power(2)
  • NOT gets its own lens
  • A AND NOT (B OR C)
  • ltA,ANDgt
  • ltNOTgt
  • ltB,ORgt
  • ltCgt

29
Grouping
  • Introduce compound (grouped) lenses
  • Allows parenthesizing
  • allows macros
  • Conjunction Negation Grouping gt support for
    arbitrary Boolean queries

30
Extensions
  • No need to have just AND and OR - could have
    any/all of the 16 possible combinations.
  • Could just have a NAND mode, but that would be
    non-intuitive. And/Or/Not are most common.

31
Fuzzy Selectors
  • Selectors need not be pass/fail.

True
1
False
0
1
True
False
0
32
Selectors over 0..1
33
Numerical Operators
34
Fuzzy Composition
  • Selectors on 0..1 implies composition on 0..1
  • Replace AND by MIN, OR by MAX, NOT by complement
  • Presently, have implemented arithmetic (DIFF),
    statistical (SQRT), and fuzzy (VERY)
  • Many others possible

35
Fuzzy example
36
Missing Data - display
37
Missing Data - example
38
Missing Data - composition
  • How do composition operators handle it? We treat
    it like IEEE NaN

39
Meta-Functions
  • Click through the window to send a command to
    the data underneath.

40
Conclusion (1995)
  • by merging Dynamic Queries with Magic Lenses, we
    keep the interactive, visual nature of queries,
    but add more functionality.
  • Future work a slicker UI, user studies.

41
Conclusion (2000)
  • If this is so great, why doesnt everyone use it?
  • Inter-app. Requires lots of plumbing, Xerox
    licensing. OS X?
  • Intra-app. Requires Xerox licensing. So far SGI
    only one determined enough to do it.
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