visualization of time-oriented...
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WOLFGANG AiGNER visualization of time-oriented data 1
Wolfgang Aigner
[email protected]://ieg.ifs.tuwien.ac.at/~aigner/
[email protected]://ike.donau-uni.ac.at/~aigner/
Version 3.214.12.2009
visualization oftime-oriented data
introduction
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Data types
1-dimensional
2-dimensional
3-dimensional
Temporal
Multi-dimensional
Tree
Network
= 4D space“the world we are living in”
[Shneiderman, 1996]
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Spatial + temporaldimensionsEvery data element we measure is related and
often only meaningful in context ofspace + time
Example: price of a computerwhere?
when?
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Differences betweenspace and timeSpace can be traversered “arbitrarily”
we can move back to where we came from
Time is unidirectionalwe can’t go back or forward in time
Humans have senses for perceiving spacevisually, touch
Humans don’t have senses for perceiving time
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…travel in timevirtually.
InteractivevisualizationGives us the ability to…
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Time-oriented data?
Event calendar
Snow height & sunshine hours
Organizationchart
iPod price
next >
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Event calendar
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WOLFGANG AiGNER visualization of time-oriented data 8^ up
Snow height &sunshine hours
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Organization chart
^ up
time
1998 2000 2002
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iPod price
^ up
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What is time?
“If no one asks me, I know.But if I wanted to explain it to one who asks me, I plainly donot know.”-- Augustinus (AD 354-430, The Confessions)
”Die Empfindung der Zeit hängt davon ab, auf welcher Seite
der geschlossenen Klotür man sich befindet.”-- Albert Einstein
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What is time-orienteddata?
no formal definition
what is considered as time-oriented data depends onthe intended task
a possible definition:
Data, where changes over time or
temporal aspects play a central role or are of interest.
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Visualization Design
data
task user
time domain
time-oriented data
visuali-zation
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Time domain overviewAdapted from [Frank, 1998]
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Scale
ordinalonly order is known
discreteevery element of time has a unique predecessor and successorcomparable to Integer
continuousbetween any two elements in time there might be another one
in betweendense timecomparable to Float
A B C
D
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Structure
linear
each element of time has aunique predecessor and aunique successor
cyclic
summer is before winter, butwinter is also before summer
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Viewpoints
ordered
multiple perspectives
branchingPast
Definite time - dataelement
assignment
PresentCurrently valid
state
FuturePlanning
Temporal uncertainty
Alternative scenarios
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Granularity
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Calendar
System of granularities and mappings between them
representational scheme
for human readability and usability
CalendarsGregorianAcademic (semester, trimester, ...)Financial (Quarters, Fiskal, ...)...
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Determinacy
determinatecomplete knowledge of temporal attributes
indeterminateincomplete knowledge of temporal attributes
no exact knowledge
i.e. “time when the earth was formed”
future planning
i.e. “it will take 2-3 weeks”
imprecise event times
i.e. “one or two days ago”
multiple granularities
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Time primitives
anchored
instant - single point in time
interval - duration between 2 instants
unanchored
span - duration of time
^ up
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Time-oriented data
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Visualization Design
data
task
visuali-zation
user
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Low-level TaskTaxonomy 1/2
Existence of a data elementDoes a data element exist at a specific time?Example: Was a measurement made in July, 1960?
Temporal locationWhen does a data element exist in time?Example: Is there a lecture taking place on November 24, 2005?
Time intervalHow long is the time span from beginning to end of the data element?Example: How long was the processing time for data set A?
Temporal textureHow often does a data element occur?Example: How often was Jane sick last year?
[McEachren, 1995]
[McEachren, 1995]
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Low-level TaskTaxonomy 2/2Rate of change
How fast is a data element changing or how much difference is there fromdata element to data element over time?
Example: How much did the price of gasoline change since last September?
SequenceIn what order do data elements appear?
Example: Did the explosion happen before or after the car accident?
SynchronizationDo data elements exist together?
Example: Is Jill’s birthday on Easter Monday this year?
[McEachren, 1995]
[McEachren, 1995]
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High-level TaskTaxonomy
Navigational Tasksnavigation in time or temporal datasearch (implies a specific user-defined target); browse
Observational Tasksdifferent characteristics of a single temporal historysearching for patterns; detecting disruptions and discontinuities; studying thedistribution of the data to identify concentrations of data (or classes of values)
Comparison Tasksrelating multiple temporal historiescomparing of two elements; rearranging; overlaying; studying correlation;searching for effects of causality; comparing evolution relative to a reference value
Manipulation Tasksmanipulation of data valuesvalue aggregation and segmentation
[Daassi, 2003]
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Visualization Design
data
task
visuali-zation
user
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Visual mapping of timeTime → Time (Animation)
probably the most natural form of mappingno “conversion” of concepts needed in betweenwell suited for
keeping track of changes
following trends and movements
not well suited for
analytic and explorative tasks
no direct comparison of parameters between different points in
time is possible
Time → Spacemapping of time to visual featuresdirect comparison of parameters between different points in time is
possible
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Visual variables
positionmost common mapping
the most accurately perceived visual feature
lengthsecond most accurate attribute
typically, the length of an object denotes the duration, asfor example in timelines
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Visual variablesangle, slope
analog-clock-based visualizations
connectionconnecting arrows or lines
“before element” --> “after element”
text, labelsimple text labelling
often combined with “connection”
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Visual variables
line (thickness)Increasing or decreasing with time
color (brightness, saturation, hue)brightness most appropriate
“fading away” against the background
transparency
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Visual variables
area
enclosure
size
texture
shape
less suited
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Visualization rootsStatistics
Visualization of time-series.
The time-series plot is the most frequently usedform of graphic design. [Tufte, 1983]
Mostly one parameter over time.
t
y
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Early time-series plot
Part of a text for monastery schools10th or 11th century (!)Inclinations of the planetary orbits over time800 years before other time-series plots appeared
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Train schedule
Paris to Lyon (1880s)