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WOLFGANG AiGNER visualization of time-oriented data 1

Wolfgang Aigner

aigner@ifs.tuwien.ac.athttp://ieg.ifs.tuwien.ac.at/~aigner/

wolfgang.aigner@donau-uni.ac.athttp://ike.donau-uni.ac.at/~aigner/

Version 3.214.12.2009

visualization oftime-oriented data

introduction

WOLFGANG AiGNER visualization of time-oriented data 2

Data types

1-dimensional

2-dimensional

3-dimensional

Temporal

Multi-dimensional

Tree

Network

= 4D space“the world we are living in”

[Shneiderman, 1996]

WOLFGANG AiGNER visualization of time-oriented data 3

Spatial + temporaldimensionsEvery data element we measure is related and

often only meaningful in context ofspace + time

Example: price of a computerwhere?

when?

WOLFGANG AiGNER visualization of time-oriented data 4

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

WOLFGANG AiGNER visualization of time-oriented data 5

…travel in timevirtually.

InteractivevisualizationGives us the ability to…

WOLFGANG AiGNER visualization of time-oriented data 6

Time-oriented data?

Event calendar

Snow height & sunshine hours

Organizationchart

iPod price

next >

WOLFGANG AiGNER visualization of time-oriented data 7^ up

Event calendar

WOLFGANG AiGNER visualization of time-oriented data 8^ up

Snow height &sunshine hours

WOLFGANG AiGNER visualization of time-oriented data 9

Organization chart

^ up

time

1998 2000 2002

WOLFGANG AiGNER visualization of time-oriented data 10

iPod price

^ up

WOLFGANG AiGNER visualization of time-oriented data 11

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

WOLFGANG AiGNER visualization of time-oriented data 12

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.

WOLFGANG AiGNER visualization of time-oriented data 13

Visualization Design

data

task user

time domain

time-oriented data

visuali-zation

WOLFGANG AiGNER visualization of time-oriented data 14

Time domain overviewAdapted from [Frank, 1998]

WOLFGANG AiGNER visualization of time-oriented data 15

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

WOLFGANG AiGNER visualization of time-oriented data 16

Structure

linear

each element of time has aunique predecessor and aunique successor

cyclic

summer is before winter, butwinter is also before summer

WOLFGANG AiGNER visualization of time-oriented data 17

Viewpoints

ordered

multiple perspectives

branchingPast

Definite time - dataelement

assignment

PresentCurrently valid

state

FuturePlanning

Temporal uncertainty

Alternative scenarios

WOLFGANG AiGNER visualization of time-oriented data 18

Granularity

WOLFGANG AiGNER visualization of time-oriented data 19

Calendar

System of granularities and mappings between them

representational scheme

for human readability and usability

CalendarsGregorianAcademic (semester, trimester, ...)Financial (Quarters, Fiskal, ...)...

WOLFGANG AiGNER visualization of time-oriented data 20

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

WOLFGANG AiGNER visualization of time-oriented data 21

Time primitives

anchored

instant - single point in time

interval - duration between 2 instants

unanchored

span - duration of time

^ up

WOLFGANG AiGNER visualization of time-oriented data 22

Time-oriented data

WOLFGANG AiGNER visualization of time-oriented data 23

Visualization Design

data

task

visuali-zation

user

WOLFGANG AiGNER visualization of time-oriented data 24

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]

WOLFGANG AiGNER visualization of time-oriented data 25

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]

WOLFGANG AiGNER visualization of time-oriented data 26

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]

WOLFGANG AiGNER visualization of time-oriented data 27

Visualization Design

data

task

visuali-zation

user

WOLFGANG AiGNER visualization of time-oriented data 28

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

WOLFGANG AiGNER visualization of time-oriented data 29

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

WOLFGANG AiGNER visualization of time-oriented data 30

Visual variablesangle, slope

analog-clock-based visualizations

connectionconnecting arrows or lines

“before element” --> “after element”

text, labelsimple text labelling

often combined with “connection”

WOLFGANG AiGNER visualization of time-oriented data 31

Visual variables

line (thickness)Increasing or decreasing with time

color (brightness, saturation, hue)brightness most appropriate

“fading away” against the background

transparency

WOLFGANG AiGNER visualization of time-oriented data 32

Visual variables

area

enclosure

size

texture

shape

less suited

WOLFGANG AiGNER visualization of time-oriented data 33

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

WOLFGANG AiGNER visualization of time-oriented data 34

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

WOLFGANG AiGNER visualization of time-oriented data 35

Train schedule

Paris to Lyon (1880s)

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