InfoVis:Wiki - User contributions [en]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 4

2009-01-07T11:25:01Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe4.html Beschreibung der Aufgabe 4]

=== Gegebene Daten ===

'''Homer Simpson's Trinkverhalten in Abhängigkeit von seinen Lebensumständen''' 

...Visualisierung von Homer's Lebensabschnitten bzw. Ereignissen mit Einfluss auf sein
Trinkverhalten (zB.: Kindheit, Pubertät, Arbeitslosigkeit, Beziehungen, Hochzeit, Geburt
der Kinder, Liebeskummer, Alltag, etc.) von seiner Geburt bis Jetzt + mögliche
Zukunftsszenarien (mind. 3).
 
*Die Menge folgender Getränke soll für die jeweiligen Lebensumstände ablesbar sein
(ml oder Liter - je nachdem - pro Tag, Monat, Jahr (z.B.: Fokus+Kontext Methoden):
a) Wasser 
b) Milch 
c) Fruchtsaft 
d) Cola 
e) Kaffee (Würfelzucker?) 
f) Bier
(vereinfacht angenommen, Homer trinkt ausschließlich diese Getränke)
 
*Die folgenden Werte sollen abhängig von den konsumierten Getränken ablesbar sein:
1) g oder kg konsumierter Zucker (aus Getränken) + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 50g; enthaltener Zucker: 10g/100 ml Cola; 10g/100 ml Fruchtsaft; 3g/Würfelzucker). 
2) mg konsumiertes Coffein + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 600mg; enthaltenes Coffein: 10 mg/100 ml Cola; 80 mg/100 ml Kaffee). 
3) g konsumierter Alkohol + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 20g; enthaltener Alkohol: 3,6 g/100ml Bier)
 
*Die Daten sollen zur medizinischen/psychologischen Analyse visualisiert werden. 
*Die bisher erlernten Design-Prinzipien sollen umgesetzt werden (z.B.: Optimierung der Data-ink ratio). 
*Die Mockups sollten zumindest 1) Homer's Leben im Überblick 2) und eine Detailansicht wiedergeben. 
*Alle nicht angeführten Daten können frei erfunden werden.

==Description of the application area, data, users and goals ==

=== Application area ===
The data shown in the following parts of this work descripe medical data (health and psycholocical) of a single person. Our visualisation should show how the drinking behaviour is inflecting homers life. Because it should be used for a medical analysis it must be precise on the one side (for doctors, experts, ...) and easy to understand on the other side (sick people). It determines not only the behaviour all over his lifetime but also shows us some special events in his life (childhood, adolescence, unemployment, connections, marriage, birth of his children, lovesickness, allday, ...). With these special events visualized medical experts can find out why homer has his drinking problem.

=== Data ===
For the visualisation of these different effects of drinking in all life circumstances we are displaying the ingredients of them. The three ingredients we check are:

*sugar
maximum dosage per day : 50 g
description: Excessive consumption of sugar has been associated with increased incidences of type 2 diabetes, obesity and tooth decay.
further informations: http://en.wikipedia.org/wiki/Sugar

*coffeine
maximum dosage per day : 600 mg
description: Caffeine is a bitter white crystalline xanthine that acts as a psychoactive stimulant drug and a mild diuretic in humans and other animals.
further informations: http://en.wikipedia.org/wiki/Coffein

*alcohol
maximum dosage per day : 20 g
description: Alcohol intoxication affects the brain, causing slurred speech, clumsiness, and delayed reflexes (drunkenness). Chronic effects include effects of in the liver, brain and addiction.
further informations: http://en.wikipedia.org/wiki/Alcohol
further informations: http://en.wikipedia.org/wiki/Alcoholic_beverage

The six drinks (milk, beer, water, wine, coke, coffee) we are checking contain these 3 ingredients as followed:

[[Image:Indi1.jpg]]

Ingredients in g/100 ml, sugar added extra to coffee (*).

The maximum dosage of them are:
* sugar: 50 g
* coffeine: 600 mg
* alcohol: 20 g

=== Users ===
* Homer Simpson
* Moe
* Medical experts
* Psychologist

Users of our application should be Homer Simpson on the one side (with it he can see how problems in his life affect his alcohol consum) and on the other side our visualisation should be used by medical experts and psychologist to help him solve this problems.

=== Goals ===
Our visualisation should show the drinking behaviour in homers life with some special points (problems). Further it will show us the maximum consument values per day for the descripted ingredients and how homer crosses this line.

== Concept ==
=== Graph with linked in hierarchical list ===
We decided to show the result in two visualization. The first part is a dynamic graph. The main message of it is the drinking behaviour in liter per day over the life of Homer Simpson. It includes the different types of drinks (water, coke, coffee, beer,...) and the maxium dose of sugar, alcohol or coffein which should be consumend. Further are some links and regions in this graph. The regions descripe longer events in homers life like his relationship with marge or his childhood and links discripe day events like the birthday of bart or his marriage with marge. The second part is a hierarchical list which is linked with the graph above. There everybody can check the selected values and compare them with important time-regions of homers life. The third part of our application is a options part were the behaviour of the graph can be influenced.

[[Image:App01.jpg]]

=== Graph ===
In the graph view we can see how the drinking behaviour changes in Homers life. The lines descripe how much of the drink the color depends to Homer consument on this day. With the options box on the bottom-right of the application every drink can be enabeled in the view or can be hiden. Further an option to see the maxium consumed sugar, coffein or alcohol per selected drink has been integrated. With the checkboxes under the graph some different events in Homers life can be enabled in the scene. There are two different types of events:
* Region 
A region is a longer part of Homers life like his childhood or his relationsship to marge. These are represented in the graph as a nearly transparent color bar in an unique color for every event.
* Day Events 
Day events are for example the marriage of Homer and Marge or the Birthday of Bart or Lisa.
An other part of the options box is the time-area in which the graph is displayed and the detail in drinking volumes. With this two options it is possible to analyse every small part of homers life.

[[Image:Graph1.jpg]]

To analyse the events in this graph there is the possibility to select a specific region in the graph. With a mouse click in the graph the region start is selected an with another click on another point the endpoint will be fixed for the hierarchical list.

=== Hierarchical list ===

In the hierarchical list there are two parts for a deeper analysis of our data. The first one is the dynamic part which is activated when the user has selected a region in the graph. The other part is the static list which contains the important life times of homer like his relationsship or his childhood.
In the detail view of the list the user of our application can see details for the groups sugar, coffein and alcohol. There he sees the maximum values of for example sugar which homer should consume on one day and beside this the average value per day homer has really consumed in this time region. Further everybody can see the data calculated for the howle selected region.
The single parts of the hierarchical list can be opened and closed so we can compare the values we want. Further the categories can be rearanged for a better view on it.

[[Image:Hierarch.jpg]]

=== How to use it===
Our application is easy to use for experts and for normal people. Experts can use both visualisation the get detailed information about homer. They can select exact regions in the graph and so it is easy to analyse when homer has the biggest problem with his drinking.
Normal people can see in the graph that Homers drinking consum is higher when a special event happens. With the pre defined selections in the hierarchical view the can easy compare this values with a free selected region.

=== Pro / Contra ===
'''pro''' 
* all data is in one screen
* data can be selected very easy
* regions can be taken from a whole life down to a single day
* important events in homers life are always visible and can be compared very easily
* the graph is easy to understand for "normal" people
* experts can get exact data from the hierarchical list

'''contra''' 
* not all data is in one graph
* one data is graphical and one in numbers

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 4

2009-01-07T11:17:20Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe4.html Beschreibung der Aufgabe 4]

=== Gegebene Daten ===

'''Homer Simpson's Trinkverhalten in Abhängigkeit von seinen Lebensumständen''' 

...Visualisierung von Homer's Lebensabschnitten bzw. Ereignissen mit Einfluss auf sein
Trinkverhalten (zB.: Kindheit, Pubertät, Arbeitslosigkeit, Beziehungen, Hochzeit, Geburt
der Kinder, Liebeskummer, Alltag, etc.) von seiner Geburt bis Jetzt + mögliche
Zukunftsszenarien (mind. 3).
 
*Die Menge folgender Getränke soll für die jeweiligen Lebensumstände ablesbar sein
(ml oder Liter - je nachdem - pro Tag, Monat, Jahr (z.B.: Fokus+Kontext Methoden):
a) Wasser 
b) Milch 
c) Fruchtsaft 
d) Cola 
e) Kaffee (Würfelzucker?) 
f) Bier
(vereinfacht angenommen, Homer trinkt ausschließlich diese Getränke)
 
*Die folgenden Werte sollen abhängig von den konsumierten Getränken ablesbar sein:
1) g oder kg konsumierter Zucker (aus Getränken) + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 50g; enthaltener Zucker: 10g/100 ml Cola; 10g/100 ml Fruchtsaft; 3g/Würfelzucker). 
2) mg konsumiertes Coffein + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 600mg; enthaltenes Coffein: 10 mg/100 ml Cola; 80 mg/100 ml Kaffee). 
3) g konsumierter Alkohol + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 20g; enthaltener Alkohol: 3,6 g/100ml Bier)
 
*Die Daten sollen zur medizinischen/psychologischen Analyse visualisiert werden. 
*Die bisher erlernten Design-Prinzipien sollen umgesetzt werden (z.B.: Optimierung der Data-ink ratio). 
*Die Mockups sollten zumindest 1) Homer's Leben im Überblick 2) und eine Detailansicht wiedergeben. 
*Alle nicht angeführten Daten können frei erfunden werden.

==Description of the application area, data, users and goals ==
=== Application area ===
The data shown in the following parts of this work descripe medical data (health and psycholocical) of a single person. Our visualisation should show how the drinking behaviour is inflecting homers life. Because it should be used for a medical analysis it must be precise on the one side (for doctors, experts, ...) and easy to understand on the other side (sick people). It determines not only the behaviour all over his lifetime but also shows us some special events in his life (childhood, adolescence, unemployment, connections, marriage, birth of his children, lovesickness, allday, ...). With these special events visualized medical experts can find out why homer has his drinking problem.

=== Data ===
For the visualisation of these different effects of drinking in all life circumstances we are displaying the ingredients of them. The three ingredients we check are:

*sugar
maximum dosage per day : 50 g
description: Excessive consumption of sugar has been associated with increased incidences of type 2 diabetes, obesity and tooth decay.
further informations: http://en.wikipedia.org/wiki/Sugar

*coffeine
maximum dosage per day : 600 mg
description: Caffeine is a bitter white crystalline xanthine that acts as a psychoactive stimulant drug and a mild diuretic in humans and other animals.
further informations: http://en.wikipedia.org/wiki/Coffein

*alcohol
maximum dosage per day : 20 g
description: Alcohol intoxication affects the brain, causing slurred speech, clumsiness, and delayed reflexes (drunkenness). Chronic effects include effects of in the liver, brain and addiction.
further informations: http://en.wikipedia.org/wiki/Alcohol
further informations: http://en.wikipedia.org/wiki/Alcoholic_beverage

The six drinks (milk, beer, water, wine, coke, coffee) we are checking contain these 3 ingredients as followed:

[[Image:Indi1.jpg]]

Ingredients in g/100 ml, sugar added extra to coffee (*).

The maximum dosage of them are:
* sugar: 50 g
* coffeine: 600 mg
* alcohol: 20 g

=== Users ===
* Homer Simpson
* Moe
* Medical experts
* Psychologist

Users of our application should be Homer Simpson on the one side (with it he can see how problems in his life affect his alcohol consum) and on the other side our visualisation should be used by medical experts and psychologist to help him solve this problems.

=== Goals ===
Our visualisation should show the drinking behaviour in homers life with some special points (problems). Further it will show us the maximum consument values per day for the descripted ingredients and how homer crosses this line.

== Concept ==
=== Graph with linked in hierarchical list ===
We decided to show the result in two visualization. The first part is a dynamic graph. The main message of it is the drinking behaviour in liter per day over the life of Homer Simpson. It includes the different types of drinks (water, coke, coffee, beer,...) and the maxium dose of sugar, alcohol or coffein which should be consumend. Further are some links and regions in this graph. The regions descripe longer events in homers life like his relationship with marge or his childhood and links discripe day events like the birthday of bart or his marriage with marge. The second part is a hierarchical list which is linked with the graph above. There everybody can check the selected values and compare them with important time-regions of homers life. The third part of our application is a options part were the behaviour of the graph can be influenced.

[[Image:App01.jpg]]

=== Graph ===
In the graph view we can see how the drinking behaviour changes in Homers life. The lines descripe how much of the drink the color depends to Homer consument on this day. With the options box on the bottom-right of the application every drink can be enabeled in the view or can be hiden. Further an option to see the maxium consumed sugar, coffein or alcohol per selected drink has been integrated. With the checkboxes under the graph some different events in Homers life can be enabled in the scene. There are two different types of events:
* Region 
A region is a longer part of Homers life like his childhood or his relationsship to marge. These are represented in the graph as a nearly transparent color bar in an unique color for every event.
* Day Events 
Day events are for example the marriage of Homer and Marge or the Birthday of Bart or Lisa.
An other part of the options box is the time-area in which the graph is displayed and the detail in drinking volumes. With this two options it is possible to analyse every small part of homers life.

[[Image:Graph1.jpg]]

To analyse the events in this graph there is the possibility to select a specific region in the graph. With a mouse click in the graph the region start is selected an with another click on another point the endpoint will be fixed for the hierarchical list.

=== Hierarchical list ===

In the hierarchical list there are two parts for a deeper analysis of our data. The first one is the dynamic part which is activated when the user has selected a region in the graph. The other part is the static list which contains the important life times of homer like his relationsship or his childhood.
In the detail view of the list the user of our application can see details for the groups sugar, coffein and alcohol. There he sees the maximum values of for example sugar which homer should consume on one day and beside this the average value per day homer has really consumed in this time region. Further everybody can see the data calculated for the howle selected region.
The single parts of the hierarchical list can be opened and closed so we can compare the values we want. Further the categories can be rearanged for a better view on it.

[[Image:Hierarch.jpg]]

=== How to use it===
Our application is easy to use for experts and for normal people. Experts can use both visualisation the get detailed information about homer. They can select exact regions in the graph and so it is easy to analyse when homer has the biggest problem with his drinking.
Normal people can see in the graph that Homers drinking consum is higher when a special event happens. With the pre defined selections in the hierarchical view the can easy compare this values with a free selected region.

=== Pro / Contra ===
'''pro''' 
* all data is in one screen
* data can be selected very easy
* regions can be taken from a whole life down to a single day
* important events in homers life are always visible and can be compared very easily
* the graph is easy to understand for "normal" people
* experts can get exact data from the hierarchical list

'''contra''' 
* not all data is in one graph
* one data is graphical and one in numbers

===References===
*[Few, 2004]: Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Appendix A - Table and Graph Design at a Glance.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 4

2009-01-07T11:13:49Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe4.html Beschreibung der Aufgabe 4]

=== Gegebene Daten ===

'''Homer Simpson's Trinkverhalten in Abhängigkeit von seinen Lebensumständen''' 

...Visualisierung von Homer's Lebensabschnitten bzw. Ereignissen mit Einfluss auf sein
Trinkverhalten (zB.: Kindheit, Pubertät, Arbeitslosigkeit, Beziehungen, Hochzeit, Geburt
der Kinder, Liebeskummer, Alltag, etc.) von seiner Geburt bis Jetzt + mögliche
Zukunftsszenarien (mind. 3).
 
*Die Menge folgender Getränke soll für die jeweiligen Lebensumstände ablesbar sein
(ml oder Liter - je nachdem - pro Tag, Monat, Jahr (z.B.: Fokus+Kontext Methoden):
a) Wasser 
b) Milch 
c) Fruchtsaft 
d) Cola 
e) Kaffee (Würfelzucker?) 
f) Bier
(vereinfacht angenommen, Homer trinkt ausschließlich diese Getränke)
 
*Die folgenden Werte sollen abhängig von den konsumierten Getränken ablesbar sein:
1) g oder kg konsumierter Zucker (aus Getränken) + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 50g; enthaltener Zucker: 10g/100 ml Cola; 10g/100 ml Fruchtsaft; 3g/Würfelzucker). 
2) mg konsumiertes Coffein + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 600mg; enthaltenes Coffein: 10 mg/100 ml Cola; 80 mg/100 ml Kaffee). 
3) g konsumierter Alkohol + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 20g; enthaltener Alkohol: 3,6 g/100ml Bier)
 
*Die Daten sollen zur medizinischen/psychologischen Analyse visualisiert werden. 
*Die bisher erlernten Design-Prinzipien sollen umgesetzt werden (z.B.: Optimierung der Data-ink ratio). 
*Die Mockups sollten zumindest 1) Homer's Leben im Überblick 2) und eine Detailansicht wiedergeben. 
*Alle nicht angeführten Daten können frei erfunden werden.

==Description of the application area, data, users and goals ==
=== Application area ===
The data shown in the following parts of this work descripe medical data (health and psycholocical) of a single person. Our visualisation should show how the drinking behaviour is inflecting homers life. Because it should be used for a medical analysis it must be precise on the one side (for doctors, experts, ...) and easy to understand on the other side (sick people). It determines not only the behaviour all over his lifetime but also shows us some special events in his life (childhood, adolescence, unemployment, connections, marriage, birth of his children, lovesickness, allday, ...). With these special events visualized medical experts can find out why homer has his drinking problem.

=== Data ===
For the visualisation of these different effects of drinking in all life circumstances we are displaying the ingredients of them. The three ingredients we check are:

*sugar
maximum dosage per day : 50 g
description: Excessive consumption of sugar has been associated with increased incidences of type 2 diabetes, obesity and tooth decay.
further informations: http://en.wikipedia.org/wiki/Sugar

*coffeine
maximum dosage per day : 600 mg
description: Caffeine is a bitter white crystalline xanthine that acts as a psychoactive stimulant drug and a mild diuretic in humans and other animals.
further informations: http://en.wikipedia.org/wiki/Coffein

*alcohol
maximum dosage per day : 20 g
description: Alcohol intoxication affects the brain, causing slurred speech, clumsiness, and delayed reflexes (drunkenness). Chronic effects include effects of in the liver, brain and addiction.
further informations: http://en.wikipedia.org/wiki/Alcohol
further informations: http://en.wikipedia.org/wiki/Alcoholic_beverage

The six drinks (milk, beer, water, wine, coke, coffee) we are checking contain these 3 ingredients as followed:

[[Image:Indi1.jpg]]

Ingredients in g/100 ml, sugar added extra to coffee (*).
 
The maximum dosage of them are:

* sugar: 50 g
* coffeine: 600 mg
* alcohol: 20 g

=== Users ===
* Homer Simpson
* Moe
* Medical experts
* Psychologist

Users of our application should be Homer Simpson on the one side (with it he can see how problems in his life affect his alcohol consum) and on the other side our visualisation should be used by medical experts and psychologist to help him solve this problems.

=== Goals ===
Our visualisation should show the drinking behaviour in homers life with some special points (problems). Further it will show us the maximum consument values per day for the descripted ingredients and how homer crosses this line.

== Concept ==
=== Graph with linked in hierarchical list ===
We decided to show the result in two visualization. The first part is a dynamic graph. The main message of it is the drinking behaviour in liter per day over the life of Homer Simpson. It includes the different types of drinks (water, coke, coffee, beer,...) and the maxium dose of sugar, alcohol or coffein which should be consumend. Further are some links and regions in this graph. The regions descripe longer events in homers life like his relationship with marge or his childhood and links discripe day events like the birthday of bart or his marriage with marge. The second part is a hierarchical list which is linked with the graph above. There everybody can check the selected values and compare them with important time-regions of homers life. The third part of our application is a options part were the behaviour of the graph can be influenced.

[[Image:App01.jpg]]

=== Graph ===
In the graph view we can see how the drinking behaviour changes in Homers life. The lines descripe how much of the drink the color depends to Homer consument on this day. With the options box on the bottom-right of the application every drink can be enabeled in the view or can be hiden. Further an option to see the maxium consumed sugar, coffein or alcohol per selected drink has been integrated. With the checkboxes under the graph some different events in Homers life can be enabled in the scene. There are two different types of events:
* Region 
A region is a longer part of Homers life like his childhood or his relationsship to marge. These are represented in the graph as a nearly transparent color bar in an unique color for every event.
* Day Events 
Day events are for example the marriage of Homer and Marge or the Birthday of Bart or Lisa.
An other part of the options box is the time-area in which the graph is displayed and the detail in drinking volumes. With this two options it is possible to analyse every small part of homers life.

[[Image:Graph1.jpg]]

To analyse the events in this graph there is the possibility to select a specific region in the graph. With a mouse click in the graph the region start is selected an with another click on another point the endpoint will be fixed for the hierarchical list.

=== Hierarchical list ===

In the hierarchical list there are two parts for a deeper analysis of our data. The first one is the dynamic part which is activated when the user has selected a region in the graph. The other part is the static list which contains the important life times of homer like his relationsship or his childhood.
In the detail view of the list the user of our application can see details for the groups sugar, coffein and alcohol. There he sees the maximum values of for example sugar which homer should consume on one day and beside this the average value per day homer has really consumed in this time region. Further everybody can see the data calculated for the howle selected region.
The single parts of the hierarchical list can be opened and closed so we can compare the values we want. Further the categories can be rearanged for a better view on it.

[[Image:Hierarch.jpg]]

=== How to use it===
Our application is easy to use for experts and for normal people. Experts can use both visualisation the get detailed information about homer. They can select exact regions in the graph and so it is easy to analyse when homer has the biggest problem with his drinking.
Normal people can see in the graph that Homers drinking consum is higher when a special event happens. With the pre defined selections in the hierarchical view the can easy compare this values with a free selected region.

=== Pro / Contra ===
'''pro''' 
* all data is in one screen
* data can be selected very easy
* regions can be taken from a whole life down to a single day
* important events in homers life are always visible and can be compared very easily
* the graph is easy to understand for "normal" people
* experts can get exact data from the hierarchical list

'''contra''' 
* not all data is in one graph
* one data is graphical and one in numbers

===References===
*[Few, 2004]:Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Appendix A - Table and Graph Design at a Glance.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 4

2009-01-07T11:11:54Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe4.html Beschreibung der Aufgabe 4]

=== Gegebene Daten ===

'''Homer Simpson's Trinkverhalten in Abhängigkeit von seinen Lebensumständen''' 

...Visualisierung von Homer's Lebensabschnitten bzw. Ereignissen mit Einfluss auf sein
Trinkverhalten (zB.: Kindheit, Pubertät, Arbeitslosigkeit, Beziehungen, Hochzeit, Geburt
der Kinder, Liebeskummer, Alltag, etc.) von seiner Geburt bis Jetzt + mögliche
Zukunftsszenarien (mind. 3).
 
*Die Menge folgender Getränke soll für die jeweiligen Lebensumstände ablesbar sein
(ml oder Liter - je nachdem - pro Tag, Monat, Jahr (z.B.: Fokus+Kontext Methoden):
a) Wasser 
b) Milch 
c) Fruchtsaft 
d) Cola 
e) Kaffee (Würfelzucker?) 
f) Bier
(vereinfacht angenommen, Homer trinkt ausschließlich diese Getränke)
 
*Die folgenden Werte sollen abhängig von den konsumierten Getränken ablesbar sein:
1) g oder kg konsumierter Zucker (aus Getränken) + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 50g; enthaltener Zucker: 10g/100 ml Cola; 10g/100 ml Fruchtsaft; 3g/Würfelzucker). 
2) mg konsumiertes Coffein + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 600mg; enthaltenes Coffein: 10 mg/100 ml Cola; 80 mg/100 ml Kaffee). 
3) g konsumierter Alkohol + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 20g; enthaltener Alkohol: 3,6 g/100ml Bier)
 
*Die Daten sollen zur medizinischen/psychologischen Analyse visualisiert werden. 
*Die bisher erlernten Design-Prinzipien sollen umgesetzt werden (z.B.: Optimierung der Data-ink ratio). 
*Die Mockups sollten zumindest 1) Homer's Leben im Überblick 2) und eine Detailansicht wiedergeben. 
*Alle nicht angeführten Daten können frei erfunden werden.

==Description of the application area, data, users and goals ==
=== Application area ===
The data shown in the following parts of this work descripe medical data (health and psycholocical) of a single person. Our visualisation should show how the drinking behaviour is inflecting homers life. Because it should be used for a medical analysis it must be precise on the one side (for doctors, experts, ...) and easy to understand on the other side (sick people). It determines not only the behaviour all over his lifetime but also shows us some special events in his life (childhood, adolescence, unemployment, connections, marriage, birth of his children, lovesickness, allday, ...). With these special events visualized medical experts can find out why homer has his drinking problem.

=== Data ===
For the visualisation of these different effects of drinking in all life circumstances we are displaying the ingredients of them. The three ingredients we check are:

*sugar
maximum dosage per day : 50 g
description: Excessive consumption of sugar has been associated with increased incidences of type 2 diabetes, obesity and tooth decay.
further informations: http://en.wikipedia.org/wiki/Sugar

*coffeine
maximum dosage per day : 600 mg
description: Caffeine is a bitter white crystalline xanthine that acts as a psychoactive stimulant drug and a mild diuretic in humans and other animals.
further informations: http://en.wikipedia.org/wiki/Coffein

*alcohol
maximum dosage per day : 20 g
description: Alcohol intoxication affects the brain, causing slurred speech, clumsiness, and delayed reflexes (drunkenness). Chronic effects include effects of in the liver, brain and addiction.
further informations: http://en.wikipedia.org/wiki/Alcohol
further informations: http://en.wikipedia.org/wiki/Alcoholic_beverage

The six drinks (milk, beer, water, wine, coke, coffee) we are checking contain these 3 ingredients as followed:

[[Image:Indi1.jpg]]

Ingredients in g/100 ml, sugar added extra to coffee (*).

The maximum dosage of them are:

* sugar: 50 g
* coffeine: 600 mg
* alcohol: 20 g

=== Users ===
* Homer Simpson
* Moe
* Medical experts
* Psychologist

Users of our application should be Homer Simpson on the one side (with it he can see how problems in his life affect his alcohol consum) and on the other side our visualisation should be used by medical experts and psychologist to help him solve this problems.

=== Goals ===
Our visualisation should show the drinking behaviour in homers life with some special points (problems). Further it will show us the maximum consument values per day for the descripted ingredients and how homer crosses this line.

== Concept ==
=== Graph with linked in hierarchical list ===
We decided to show the result in two visualization. The first part is a dynamic graph. The main message of it is the drinking behaviour in liter per day over the life of Homer Simpson. It includes the different types of drinks (water, coke, coffee, beer,...) and the maxium dose of sugar, alcohol or coffein which should be consumend. Further are some links and regions in this graph. The regions descripe longer events in homers life like his relationship with marge or his childhood and links discripe day events like the birthday of bart or his marriage with marge. The second part is a hierarchical list which is linked with the graph above. There everybody can check the selected values and compare them with important time-regions of homers life. The third part of our application is a options part were the behaviour of the graph can be influenced.

[[Image:App01.jpg]]

=== Graph ===
In the graph view we can see how the drinking behaviour changes in Homers life. The lines descripe how much of the drink the color depends to Homer consument on this day. With the options box on the bottom-right of the application every drink can be enabeled in the view or can be hiden. Further an option to see the maxium consumed sugar, coffein or alcohol per selected drink has been integrated. With the checkboxes under the graph some different events in Homers life can be enabled in the scene. There are two different types of events:
* Region 
A region is a longer part of Homers life like his childhood or his relationsship to marge. These are represented in the graph as a nearly transparent color bar in an unique color for every event.
* Day Events 
Day events are for example the marriage of Homer and Marge or the Birthday of Bart or Lisa.
An other part of the options box is the time-area in which the graph is displayed and the detail in drinking volumes. With this two options it is possible to analyse every small part of homers life.

[[Image:Graph1.jpg]]

To analyse the events in this graph there is the possibility to select a specific region in the graph. With a mouse click in the graph the region start is selected an with another click on another point the endpoint will be fixed for the hierarchical list.

=== Hierarchical list ===

In the hierarchical list there are two parts for a deeper analysis of our data. The first one is the dynamic part which is activated when the user has selected a region in the graph. The other part is the static list which contains the important life times of homer like his relationsship or his childhood.
In the detail view of the list the user of our application can see details for the groups sugar, coffein and alcohol. There he sees the maximum values of for example sugar which homer should consume on one day and beside this the average value per day homer has really consumed in this time region. Further everybody can see the data calculated for the howle selected region.
The single parts of the hierarchical list can be opened and closed so we can compare the values we want. Further the categories can be rearanged for a better view on it.

[[Image:Hierarch.jpg]]

=== How to use it===
Our application is easy to use for experts and for normal people. Experts can use both visualisation the get detailed information about homer. They can select exact regions in the graph and so it is easy to analyse when homer has the biggest problem with his drinking.
Normal people can see in the graph that Homers drinking consum is higher when a special event happens. With the pre defined selections in the hierarchical view the can easy compare this values with a free selected region.

=== Pro / Contra ===
'''pro''' 
* all data is in one screen
* data can be selected very easy
* regions can be taken from a whole life down to a single day
* important events in homers life are always visible and can be compared very easily
* the graph is easy to understand for "normal" people
* experts can get exact data from the hierarchical list

'''contra''' 
* not all data is in one graph
* one data is graphical and one in numbers

===References===
*[Few, 2004]:Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Appendix A - Table and Graph Design at a Glance.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 4

2009-01-07T11:06:37Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe4.html Beschreibung der Aufgabe 4]

=== Gegebene Daten ===

'''Homer Simpson's Trinkverhalten in Abhängigkeit von seinen Lebensumständen''' 

...Visualisierung von Homer's Lebensabschnitten bzw. Ereignissen mit Einfluss auf sein
Trinkverhalten (zB.: Kindheit, Pubertät, Arbeitslosigkeit, Beziehungen, Hochzeit, Geburt
der Kinder, Liebeskummer, Alltag, etc.) von seiner Geburt bis Jetzt + mögliche
Zukunftsszenarien (mind. 3).
 
*Die Menge folgender Getränke soll für die jeweiligen Lebensumstände ablesbar sein
(ml oder Liter - je nachdem - pro Tag, Monat, Jahr (z.B.: Fokus+Kontext Methoden):
a) Wasser 
b) Milch 
c) Fruchtsaft 
d) Cola 
e) Kaffee (Würfelzucker?) 
f) Bier
(vereinfacht angenommen, Homer trinkt ausschließlich diese Getränke)
 
*Die folgenden Werte sollen abhängig von den konsumierten Getränken ablesbar sein:
1) g oder kg konsumierter Zucker (aus Getränken) + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 50g; enthaltener Zucker: 10g/100 ml Cola; 10g/100 ml Fruchtsaft; 3g/Würfelzucker). 
2) mg konsumiertes Coffein + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 600mg; enthaltenes Coffein: 10 mg/100 ml Cola; 80 mg/100 ml Kaffee). 
3) g konsumierter Alkohol + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 20g; enthaltener Alkohol: 3,6 g/100ml Bier)
 
*Die Daten sollen zur medizinischen/psychologischen Analyse visualisiert werden. 
*Die bisher erlernten Design-Prinzipien sollen umgesetzt werden (z.B.: Optimierung der Data-ink ratio). 
*Die Mockups sollten zumindest 1) Homer's Leben im Überblick 2) und eine Detailansicht wiedergeben. 
*Alle nicht angeführten Daten können frei erfunden werden.

==Description of the application area, data, users and goals ==
=== Application area ===
The data shown in the following parts of this work descripe medical data (health and psycholocical) of a single person. Our visualisation should show how the drinking behaviour is inflecting homers life. Because it should be used for a medical analysis it must be precise on the one side (for doctors, experts, ...) and easy to understand on the other side (sick people). It determines not only the behaviour all over his lifetime but also shows us some special events in his life (childhood, adolescence, unemployment, connections, marriage, birth of his children, lovesickness, allday, ...). With these special events visualized medical experts can find out why homer has his drinking problem.

=== Data ===
For the visualisation of these different effects of drinking in all life circumstances we are displaying the ingredients of them. The three ingredients we check are:

*sugar
maximum dosage per day : 50 g
description: Excessive consumption of sugar has been associated with increased incidences of type 2 diabetes, obesity and tooth decay.
further informations: http://en.wikipedia.org/wiki/Sugar

*Coffeine
maximum dosage per day : 600 mg
description: Caffeine is a bitter white crystalline xanthine that acts as a psychoactive stimulant drug and a mild diuretic in humans and other animals.
further informations: http://en.wikipedia.org/wiki/Coffein

*Alcohol
maximum dosage per day : 20 g
description: Alcohol intoxication affects the brain, causing slurred speech, clumsiness, and delayed reflexes (drunkenness). Chronic effects include effects of in the liver, brain and addiction.
further informations: http://en.wikipedia.org/wiki/Alcohol
further informations: http://en.wikipedia.org/wiki/Alcoholic_beverage

The six drinks (milk, beer, water, wine, coke, coffee) we are checking contain these 3 ingredients as followed:

[[Image:Indi1.jpg]]

Ingredients in g/100 ml, sugar added extra to coffee (*).

The maximum dosage of them are:

* sugar: 50 g
* coffeine: 600 mg
* alcohol: 20 g

=== Users ===
* Homer Simpson
* Moe
* Medical experts
* Psychologist

Users of our application should be Homer Simpson on the one side (with it he can see how problems in his life affect his alcohol consum) and on the other side our visualisation should be used by medical experts and psychologist to help him solve this problems.

=== Goals ===
Our visualisation should show the drinking behaviour in homers life with some special points (problems). Further it will show us the maximum consument values per day for the descripted ingredients and how homer crosses this line.

== Concept ==
=== Graph with linked in hierarchical list ===
We decided to show the result in two visualization. The first part is a dynamic graph. The main message of it is the drinking behaviour in liter per day over the life of Homer Simpson. It includes the different types of drinks (water, coke, coffee, beer,...) and the maxium dose of sugar, alcohol or coffein which should be consumend. Further are some links and regions in this graph. The regions descripe longer events in homers life like his relationship with marge or his childhood and links discripe day events like the birthday of bart or his marriage with marge. The second part is a hierarchical list which is linked with the graph above. There everybody can check the selected values and compare them with important time-regions of homers life. The third part of our application is a options part were the behaviour of the graph can be influenced.

[[Image:App01.jpg]]

=== Graph ===
In the graph view we can see how the drinking behaviour changes in Homers life. The lines descripe how much of the drink the color depends to Homer consument on this day. With the options box on the bottom-right of the application every drink can be enabeled in the view or can be hiden. Further an option to see the maxium consumed sugar, coffein or alcohol per selected drink has been integrated. With the checkboxes under the graph some different events in Homers life can be enabled in the scene. There are two different types of events:
* Region 
A region is a longer part of Homers life like his childhood or his relationsship to marge. These are represented in the graph as a nearly transparent color bar in an unique color for every event.
* Day Events 
Day events are for example the marriage of Homer and Marge or the Birthday of Bart or Lisa.
An other part of the options box is the time-area in which the graph is displayed and the detail in drinking volumes. With this two options it is possible to analyse every small part of homers life.

[[Image:Graph1.jpg]]

To analyse the events in this graph there is the possibility to select a specific region in the graph. With a mouse click in the graph the region start is selected an with another click on another point the endpoint will be fixed for the hierarchical list.

=== Hierarchical list ===

In the hierarchical list there are two parts for a deeper analysis of our data. The first one is the dynamic part which is activated when the user has selected a region in the graph. The other part is the static list which contains the important life times of homer like his relationsship or his childhood.
In the detail view of the list the user of our application can see details for the groups sugar, coffein and alcohol. There he sees the maximum values of for example sugar which homer should consume on one day and beside this the average value per day homer has really consumed in this time region. Further everybody can see the data calculated for the howle selected region.
The single parts of the hierarchical list can be opened and closed so we can compare the values we want. Further the categories can be rearanged for a better view on it.

[[Image:Hierarch.jpg]]

=== How to use it===
Our application is easy to use for experts and for normal people. Experts can use both visualisation the get detailed information about homer. They can select exact regions in the graph and so it is easy to analyse when homer has the biggest problem with his drinking.
Normal people can see in the graph that Homers drinking consum is higher when a special event happens. With the pre defined selections in the hierarchical view the can easy compare this values with a free selected region.

=== Pro / Contra ===
'''pro''' 
* all data is in one screen
* data can be selected very easy
* regions can be taken from a whole life down to a single day
* important events in homers life are always visible and can be compared very easily
* the graph is easy to understand for "normal" people
* experts can get exact data from the hierarchical list

'''contra''' 
* not all data is in one graph
* one data is graphical and one in numbers

===References===
*[Few, 2004]:Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Appendix A - Table and Graph Design at a Glance.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 4

2009-01-07T11:04:35Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe4.html Beschreibung der Aufgabe 4]

=== Gegebene Daten ===

'''Homer Simpson's Trinkverhalten in Abhängigkeit von seinen Lebensumständen''' 

...Visualisierung von Homer's Lebensabschnitten bzw. Ereignissen mit Einfluss auf sein
Trinkverhalten (zB.: Kindheit, Pubertät, Arbeitslosigkeit, Beziehungen, Hochzeit, Geburt
der Kinder, Liebeskummer, Alltag, etc.) von seiner Geburt bis Jetzt + mögliche
Zukunftsszenarien (mind. 3).
 
*Die Menge folgender Getränke soll für die jeweiligen Lebensumstände ablesbar sein
(ml oder Liter - je nachdem - pro Tag, Monat, Jahr (z.B.: Fokus+Kontext Methoden):
a) Wasser 
b) Milch 
c) Fruchtsaft 
d) Cola 
e) Kaffee (Würfelzucker?) 
f) Bier
(vereinfacht angenommen, Homer trinkt ausschließlich diese Getränke)
 
*Die folgenden Werte sollen abhängig von den konsumierten Getränken ablesbar sein:
1) g oder kg konsumierter Zucker (aus Getränken) + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 50g; enthaltener Zucker: 10g/100 ml Cola; 10g/100 ml Fruchtsaft; 3g/Würfelzucker). 
2) mg konsumiertes Coffein + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 600mg; enthaltenes Coffein: 10 mg/100 ml Cola; 80 mg/100 ml Kaffee). 
3) g konsumierter Alkohol + empfohlene Maximaldosis pro Tag, Monat, Jahr
(empfohlene Maximaldosis/Tag: 20g; enthaltener Alkohol: 3,6 g/100ml Bier)
 
*Die Daten sollen zur medizinischen/psychologischen Analyse visualisiert werden. 
*Die bisher erlernten Design-Prinzipien sollen umgesetzt werden (z.B.: Optimierung der Data-ink ratio). 
*Die Mockups sollten zumindest 1) Homer's Leben im Überblick 2) und eine Detailansicht wiedergeben. 
*Alle nicht angeführten Daten können frei erfunden werden.

==Description of the application area, data, users and goals ==
=== Application area ===
The data shown in the following parts of this work descripe medical data (health and psycholocical) of a single person. Our visualisation should show how the drinking behaviour is inflecting homers life. Because it should be used for a medical analysis it must be precise on the one side (for doctors, experts, ...) and easy to understand on the other side (sick people). It determines not only the behaviour all over his lifetime but also shows us some special events in his life (childhood, adolescence, unemployment, connections, marriage, birth of his children, lovesickness, allday, ...). With these special events visualized medical experts can find out why homer has his drinking problem.

=== Data ===
For the visualisation of these different effects of drinking in all life circumstances we are displaying the ingredients of them. The three ingredients we check are:

*sugar
maximum dosage per day : 50 g
description: Excessive consumption of sugar has been associated with increased incidences of type 2 diabetes, obesity and tooth decay.
further informations: http://en.wikipedia.org/wiki/Sugar

*Coffeine
maximum dosage per day : 600 mg
description: Caffeine is a bitter white crystalline xanthine that acts as a psychoactive stimulant drug and a mild diuretic in humans and other animals.
further informations: http://en.wikipedia.org/wiki/Coffein

*Alcohol
maximum dosage per day : 20 g
description: Alcohol intoxication affects the brain, causing slurred speech, clumsiness, and delayed reflexes (drunkenness). Chronic effects include effects of in the liver, brain and addiction.
further informations: http://en.wikipedia.org/wiki/Alcohol
further informations: http://en.wikipedia.org/wiki/Alcoholic_beverage

The six drinks (milk, beer, water, wine, coke, coffee) we are checking contain these 3 ingredients as followed:

[[Image:Indi1.jpg]]

Ingredients in g/100 ml, sugar added extra to coffee (*).

The maximum dosage of them are:

* sugar: 50 g
* coffeine: 600 mg
* alcohol: 20 g

=== Users ===
* Homer Simpson
* Moe
* Medical experts
* Psychologist

Users of our application should be Homer Simpson on the one side (with it he can see how problems in his life affect his alcohol consum) and on the other side our visualisation should be used by medical experts and psychologist to help him solve this problems.

=== Goals ===
Our visualisation should show the drinking behaviour in homers life with some special points (problems). Further it will show us the maximum consument values per day for the descripted ingredients and how homer crosses this line.

== Concept ==
=== Graph with linked in hierarchical list ===
We decided to show the result in two visualization. The first part is a dynamic graph. The main message of it is the drinking behaviour in liter per day over the life of Homer Simpson. It includes the different types of drinks (water, coke, coffee, beer,...) and the maxium dose of sugar, alcohol or coffein which should be consumend. Further are some links and regions in this graph. The regions descripe longer events in homers life like his relationship with marge or his childhood and links discripe day events like the birthday of bart or his marriage with marge. The second part is a hierarchical list which is linked with the graph above. There everybody can check the selected values and compare them with important time-regions of homers life. The third part of our application is a options part were the behaviour of the graph can be influenced.

[[Image:App01.jpg]]

=== Graph ===
In the graph view we can see how the drinking behaviour changes in Homers life. The lines descripe how much of the drink the color depends to Homer consument on this day. With the options box on the bottom-right of the application every drink can be enabeled in the view or can be hiden. Further an option to see the maxium consumed sugar, coffein or alcohol per selected drink has been integrated. With the checkboxes under the graph some different events in Homers life can be enabled in the scene. There are two different types of events:
* Region 
A region is a longer part of Homers life like his childhood or his relationsship to marge. These are represented in the graph as a nearly transparent color bar in an unique color for every event.
* Day Events 
Day events are for example the marriage of Homer and Marge or the Birthday of Bart or Lisa.
An other part of the options box is the time-area in which the graph is displayed and the detail in drinking volumes. With this two options it is possible to analyse every small part of homers life.

[[Image:Graph1.jpg]]

To analyse the events in this graph there is the possibility to select a specific region in the graph. With a mouse click in the graph the region start is selected an with another click on another point the endpoint will be fixed for the hierarchical list.

=== Hierarchical list ===

In the hierarchical list there are two parts for a deeper analysis of our data. The first one is the dynamic part which is activated when the user has selected a region in the graph. The other part is the static list which contains the important life times of homer like his relationsship or his childhood.
In the detail view of the list the user of our application can see details for the groups sugar, coffein and alcohol. There he sees the maximum values of for example sugar which homer should consume on one day and beside this the average value per day homer has really consumed in this time region. Further everybody can see the data calculated for the howle selected region.
The single parts of the hierarchical list can be opened and closed so we can compare the values we want. Further the categories can be rearanged for a better view on it.

[[Image:Hierarch.jpg]]

=== How to use it===
Our application is easy to use for experts and for normal people. Experts can use both visualisation the get detailed information about homer. They can select exact regions in the graph and so it is easy to analyse when homer has the biggest problem with his drinking.
Normal people can see in the graph that Homers drinking consum is higher when a special event happens. With the pre defined selections in the hierarchical view the can easy compare this values with a free selected region.

=== Pro / Contra ===
'''pro''' 
* all data is in one screen
* data can be selected very easy
* regions can be taken from a whole life down to a single day
* important events in homers life are always visible and can be compared very easily
* the graph is easy to understand for "normal" people
* experts can get exact data from the hierarchical list

'''contra''' 
* not all data is in one graph
* one data is graphical and one in numbers

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-12-15T19:45:29Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
==Exercise 2==

=== Table to evaluate ===

[[Image:Top25newspapers.gif]]

===Critics on the table===
In a first step the table was evaluated on the table design guidelines of Few [2004]:

* The titel doesn´t contain of which year(s) the Top 25 is and you don´t know which period of the year is used. Because the reference source is from March 2007 and it is not possible that the "whole" years 2006 and 2007 are compared.
* The table shows the Top 25, the data is sorted in descending order. Because of the failure of a colum included the ranking, it is not possible to jump to Top 7 - it is necessary to count the lines.
* It´s not easy to follow the horizontal line, because there are no grids and rules. Further it is difficult to track across the rows with this spacing (distance between lines).
* The mean of the colum "Increase/Decrease" is not clear: the relationship of the data in the column to the whole context is not clear. Apart from that the way the numbers are written makes them difficult to explain (center alignment, only minus sign).
* In the colum "Percent" after every data the symbol % is missing and only in some cases a decimal place is published.
* The column "2006" and "2007" is not in chronological order.
* The subtitle electronic editions is used two times.
* A comma is placed to the left of every three digits of numbers, but because of the way numbers are written(aligned to the center) makes them difficult to interpret. So the direct comparison with the other lines is not possible - you can get a false impression of the size of the number.
* The column “Frequency” is not important because there is only one exception.
* The name of the district is just published in some cases. It is placed with parenthesis in the title.

===Correction on the table ===

[[Image:Tablenewspaper04.jpg]]

===Changes on the table===
* Title should point on the year and the country in which the evaluation takes places. Our new title is: „Top 25 - USA Newspapers with electronic editions 2006/2007“. With this title you know exactly what’s the topic of the table, where the data comes from and in which time period it takes place.
* We insert a first new column, called „Rank“. In this column the rank of the Top 25 is registered, so you can easy go to row of the Top 8.
* Percent Numbers should have a + or – in front and a % behind the number to make the it easier to read. Place a percentage sign (i.e., %) immediately to the right of every percentage value (e.g., 8.75%). Numbers should have the same size of decimal place. If they have they have the same size it is easier to see which data is bigger and which is smaller. With a % sign afterwards you know with the first look at the row that every line means a percental number.
* If a header is used for two columns there can be just one header instead of one for every column (i.e. subheader 2006/2007). It is easier to see the dependency of the two rows if the header is used for both of them.
* Because we don’t want to suggest that the columns are more important than the rows data, we’ve used a row fill color the highlight them.
* The Columns are not in chronological order. We have exchanged the rows 2007 and 2006 because the reading direction is from the left to the right.
* Numbers have to be right-aligned with a comma for a thousands digit and a point for a decimal place. Further they should have the same number of decimal place. With the points and commas it is easier to read the numbers and with the same size of the decimal place and the right-alignment it’s a lot easier to see which data is bigger then an other one.
* In some cases the name of the origin of the newspaper is in the title. Sometimes left, right or in the name. We changed this by making a new row with the district of every newspaper. Now you can read this information if you are interested in or just leave it out.
* The value Frequency is for every row except of one the same. We have deleted this row and made a legend under the table, which descripes the behavior. With this step we saved much place with information that is not that important.
* The "***" are replaced by the term n/a - n/a stands for not available.

===References===
*[Few, 2004]:Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 8 - Table Design.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-12-15T19:37:09Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
==Exercise 2==

=== Table to evaluate ===

[[Image:Top25newspapers.gif]]

===Critics on the table===
In a first step the table was evaluated on the table design guidelines of Few [2004]:

* The titel doesn´t contain of which year(s) the Top 25 is and you don´t know which period of the year is used. Because the reference source is from March 2007 and it is not possible that the "whole" years 2006 and 2007 are compared.
* The table shows the Top 25, but from the the way the lines are ordered its not easy to get the rank for example the Top 7. Further it´s not easy to follow the horizontal line, because there are no grids and rules .
* The mean of the colum "Increase/Decrease" is not clear: the relationship of the data in the column to the whole context is not clear. Apart from that the way the numbers are written makes them difficult to explain (center alignment, only minus sign).
* In the colum "Percent" after every data the symbol % is missing and only in some cases a decimal place is published.
* The column "2006" and "2007" is not in chronological order.
* The subtitle electronic editions is used two times.
* A comma is placed to the left of every three digits of numbers, but because of the way numbers are written(aligned to the center) makes them difficult to interpret. So the direct comparison with the other lines is not possible - you can get a false impression of the size of the number.
* The column “Frequency” is not important because there is only one exception.
* It is difficult to track across the rows with this spacing.
* The name of the district is just published in some cases. It is placed with parenthesis in the title.

===Correction on the table ===

[[Image:Tablenewspaper04.jpg]]

===Changes on the table===
* Title should point on the year and the country in which the evaluation takes places. Our new title is: „Top 25 - USA Newspapers with electronic editions 2006/2007“. With this title you know exactly what’s the topic of the table, where the data comes from and in which time period it takes place.
* We insert a first new column, called „Rank“. In this column the rank of the Top 25 is registered, so you can easy go to row of the Top 8.
* Percent Numbers should have a + or – in front and a % behind the number to make the it easier to read. Place a percentage sign (i.e., %) immediately to the right of every percentage value (e.g., 8.75%). Numbers should have the same size of decimal place. If they have they have the same size it is easier to see which data is bigger and which is smaller. With a % sign afterwards you know with the first look at the row that every line means a percental number.
* If a header is used for two columns there can be just one header instead of one for every column (i.e. subheader 2006/2007). It is easier to see the dependency of the two rows if the header is used for both of them.
* Because we don’t want to suggest that the columns are more important than the rows data, we’ve used a row fill color the highlight them.
* The Columns are not in chronological order. We have exchanged the rows 2007 and 2006 because the reading direction is from the left to the right.
* Numbers have to be right-aligned with a comma for a thousands digit and a point for a decimal place. Further they should have the same number of decimal place. With the points and commas it is easier to read the numbers and with the same size of the decimal place and the right-alignment it’s a lot easier to see which data is bigger then an other one.
* In some cases the name of the origin of the newspaper is in the title. Sometimes left, right or in the name. We changed this by making a new row with the district of every newspaper. Now you can read this information if you are interested in or just leave it out.
* The value Frequency is for every row except of one the same. We have deleted this row and made a legend under the table, which descripes the behavior. With this step we saved much place with information that is not that important.
* The "***" are replaced by the term n/a - n/a stands for not available.

===References===
*[Few, 2004]:Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 8 - Table Design.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-12-14T10:04:36Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
==Exercise 2==

=== Table to evaluate ===

[[Image:Top25newspapers.gif]]

===Critics on the table===
In a first step the table was evaluated on the table design guidelines of Few [2004]:

* The titel doesn´t contain of which year(s) the Top 25 is and you don´t know which period of the year is used. Because the reference source is from March 2007 and it is not possible that the "whole" years 2006 and 2007 are compared.
* The table shows the Top 25, but from the the way the lines are ordered its not easy to get the rank for example the Top 7. Further it´s not easy to follow the horizontal line, because there are no grids and rules .
* The mean of the colum "Increase/Decrease" is not clear, what shall it mean?
* In the colum "Percent" after every data the symbol % is missing and only in some cases a decimal place is published.
* The column "2006" and "2007" is not in chronological order.
* The subtitle electronic editions is used two times.
* A comma is placed to the left of every three digits of numbers, but because of the way numbers are written(aligned to the center) makes them difficult to interpret. So the direct comparison with the other lines is not possible - you can get a false impression of the size of the number.
* The column “Frequency” is not important because there is only one exception.
* It is difficult to track across the rows with this spacing.
* The name of the district is just published in some cases. It is placed with parenthesis in the title.

===Correction on the table ===

[[Image:Tablenewspaper04.jpg]]

===Changes on the table===
* Title should point on the year and the country in which the evaluation takes places. Our new title is: „Top 25 - USA Newspapers with electronic editions 2006/2007“. With this title you know exactly what’s the topic of the table, where the data comes from and in which time period it takes place.
* We insert a first new column, called „Rank“. In this column the rank of the Top 25 is registered, so you can easy go to row of the Top 8.
* Percent Numbers should have a + or – in front and a % behind the number to make the it easier to read. Place a percentage sign (i.e., %) immediately to the right of every percentage value (e.g., 8.75%). Numbers should have the same size of decimal place. If they have they have the same size it is easier to see which data is bigger and which is smaller. With a % sign afterwards you know with the first look at the row that every line means a percental number.
* If a header is used for two columns there can be just one header instead of one for every column (i.e. subheader 2006/2007). It is easier to see the dependency of the two rows if the header is used for both of them.
* Because we don’t want to suggest that the columns are more important than the rows data, we’ve used a row fill color the highlight them.
* The Columns are not in chronological order. We have exchanged the rows 2007 and 2006 because the reading direction is from the left to the right.
* Numbers have to be right-aligned with a comma for a thousands digit and a point for a decimal place. Further they should have the same number of decimal place. With the points and commas it is easier to read the numbers and with the same size of the decimal place and the right-alignment it’s a lot easier to see which data is bigger then an other one.
* In some cases the name of the origin of the newspaper is in the title. Sometimes left, right or in the name. We changed this by making a new row with the district of every newspaper. Now you can read this information if you are interested in or just leave it out.
* The value Frequency is for every row except of one the same. We have deleted this row and made a legend under the table, which descripes the behavior. With this step we saved much place with information that is not that important.
* The "***" are replaced by the term n/a - n/a stands for not available.

===References===
*[Few, 2004]:Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 8 - Table Design.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-12-14T10:00:53Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
==Exercise 2==

=== Table to evaluate ===

[[Image:Top25newspapers.gif]]

===Critics on the table===
In a first step the table was evaluated on the design principles of Few [2004]:
* The titel doesn´t contain of which year(s) the Top 25 is and you don´t know which period of the year is used. Because the reference source is from March 2007 and it is not possible that the "whole" years 2006 and 2007 are compared.
* The table shows the Top 25, but from the the way the lines are ordered its not easy to get the rank for example the Top 7. Further it´s not easy to follow the horizontal line, because there are no grids and rules .
* The mean of the colum "Increase/Decrease" is not clear, what shall it mean?
* In the colum "Percent" after every data the symbol % is missing and only in some cases a decimal place is published.
* The column "2006" and "2007" is not in chronological order.
* The subtitle electronic editions is used two times.
* A comma is placed to the left of every three digits of numbers, but because of the way numbers are written(aligned to the center) makes them difficult to interpret. So the direct comparison with the other lines is not possible - you can get a false impression of the size of the number.
* The column “Frequency” is not important because there is only one exception.
* It is difficult to track across the rows with this spacing.
* The name of the district is just published in some cases. It is placed with parenthesis in the title.

===Correction on the table ===

[[Image:Tablenewspaper04.jpg]]

===Changes on the table===
* Title should point on the year and the country in which the evaluation takes places. Our new title is: „Top 25 - USA Newspapers with electronic editions 2006/2007“. With this title you know exactly what’s the topic of the table, where the data comes from and in which time period it takes place.
* We insert a first new column, called „Rank“. In this column the rank of the Top 25 is registered, so you can easy go to row of the Top 8.
* Percent Numbers should have a + or – in front and a % behind the number to make the it easier to read. Place a percentage sign (i.e., %) immediately to the right of every percentage value (e.g., 8.75%). Numbers should have the same size of decimal place. If they have they have the same size it is easier to see which data is bigger and which is smaller. With a % sign afterwards you know with the first look at the row that every line means a percental number.
* If a header is used for two columns there can be just one header instead of one for every column (i.e. subheader 2006/2007). It is easier to see the dependency of the two rows if the header is used for both of them.
* Because we don’t want to suggest that the columns are more important than the rows data, we’ve used a row fill color the highlight them.
* The Columns are not in chronological order. We have exchanged the rows 2007 and 2006 because the reading direction is from the left to the right.
* Numbers have to be right-aligned with a comma for a thousands digit and a point for a decimal place. Further they should have the same number of decimal place. With the points and commas it is easier to read the numbers and with the same size of the decimal place and the right-alignment it’s a lot easier to see which data is bigger then an other one.
* In some cases the name of the origin of the newspaper is in the title. Sometimes left, right or in the name. We changed this by making a new row with the district of every newspaper. Now you can read this information if you are interested in or just leave it out.
* The value Frequency is for every row except of one the same. We have deleted this row and made a legend under the table, which descripes the behavior. With this step we saved much place with information that is not that important.
* The "***" are replaced by the term n/a - n/a stands for not available.

===References===
*[Few, 2004]:Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 8 - Table Design.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-26T07:52:27Z

UE-InfoVis0809 0126631:

= Visual Encoding =

== Definition ==
Visual encoding is the set of techniques enabling the representation of data on a screen or on paper. It comprises of the use of shapes, colours, areas and other visual variables that make it possible to associate data variables to graphic variables [Dürsteler, 2005]. Visual encodings are mappings of information to display elements [Munzner, 2000].

== Techniques of Visual Encoding ==

The fundamental substrate of visualizations is spatial position. Marks such as points, lines, or area-covering elements can be placed on this substrate. These marks can carry additional information independent of their spatial position, such as size, greyscale luminance (brightness) value, surface texture density, color hue, color saturation, curvature, angle, and shape [Munzner, 2000].

* Space
* Marks
* Connections & Enclosures
* Retinal Properties
* Temporal Encoding
* Viewpoint Transformation

=== Space ===
When you think about an empty paper as the beginning of a visualisation, the space between some possible object is one of the most powerful aspects to give something an important note.

=== Marks ===
Marks are the visible things that occur in space [Card et al., 1999], and are simply any graphical symbol visible on a display medium [Ignatius and Senay, 1999].
There are four types of simple Marks :
* Points
* Lines
* Areas
* Volumes

=== Connections & enclosures ===
Connections and enclosures build the important dependencies between the objects (marks). Connections show a relationship between objects, while enclosures can also indicate related objects.

=== Retinal properties ===
A retinal encoding is any variation of the marks that the retina of the eye can perceive besides position [Ignatius and Senay, 1999]. They are the informations that are carried by marks, such as crispness, shape, resolution, transperancy, color(value,hue & saturation), grayscale [Munzner, 2000].
Retinal properties describe how objects (marks) look like.

[[Image:retinal.JPG|center|400px|thumb|[Card et al., 1999] Retinal properties]]

=== Temporal encoding ===
A temporal encoding shows how the marks' properties vary over time.
It's the encoding which depends on the temporal changes of marks (mark position and their retinal properties) [Ignatius and Senay, 1999].

=== Viewpoint transformations ===

Viewpoint transformations modify interactively and augment Visual Structures to turn static presentations into visualizations by establishing graphical parameters to create Views of Visual Structures [Card et al., 1999; Jacko and Sears, 2002] in other words it is the modification of the view position of the viewer (or in general the modification of viewing parameters), thus enhancing the visual perception.

There are three common view transformations :
* Location Probes : Usage of Location in the visual structures to reveal additional info
* Viewpoint control : Moving the viewpoint to create visualisation : Pan,zoom,clip the viewpoint.
* Distortion : Creating a focus area and context area.

[[Image:filmfinder_sm.gif|center|400px|thumb|[Waloszek, 2008] FilmFinder]]

==References==
*[Card et al., 1999] Stuart K. Card, Jock D. Mackinlay, and Ben Schneiderman. ''Readings in Information Visualization. Using Vision to Think.''Morgan Kaufman Publ Inc, San Diego, 1990.
* [Dürsteler, 2005] Juan C. Dürsteler, Web Content Mining Visualisation. Created at: November 7. http://www.infovis.net/printMag.php?num=175&lang=2.
* [Ignatius and Senay, 1999] Ignatius Eve, and Senay Hikmet, Data,vocabulary,marks,composition rules and visual perception rules. Created at: ?. http://cose.math.bas.bg/Sci_Visualization/visConcepts/concepts/marks.htm.
*[Jacko and Sears, 2002] Julie A. Jacko, and Andrew Sears.''The Human-computer Interaction Handbook: Fundamentals, Evolving Technologies.''Lawrence Erlbaum Assoc in, NY, 2002.
* [Munzner, 2000] Tamara Munzner, Interactive Visualization of Large Graphs and Networks. Ph.D. dissertation, Stanford University. June 2000, http://graphics.stanford.edu/papers/munzner_thesis/.
* [Waloszek, 2008] Gerd Waloszek, SAP AG, SAP User Experience,Selecting Objects By Attributes – Part II. Created at: October 3. http://www.sapdesignguild.org/.../attributes_2.asp.

File:Filmfinder sm.gif

2008-11-26T07:51:42Z

UE-InfoVis0809 0126631:

== Summary ==

== Copyright status ==

== Source ==
[Waloszek, 2008] Gerd Waloszek, SAP AG, SAP User Experience,Selecting Objects By Attributes – Part II. Created at: October 3. http://www.sapdesignguild.org/.../attributes_2.asp.

File:Retinal.JPG

2008-11-26T07:50:36Z

UE-InfoVis0809 0126631:

== Summary ==
Retinal Properties
== Copyright status ==

== Source ==
[Card et al., 1999] Stuart K. Card, Jock D. Mackinlay, and Ben Schneiderman. Readings in Information Visualization. Using Vision to Think. Morgan Kaufman Publ Inc, San Diego, 1990.

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Cartogram

2008-11-26T07:48:52Z

UE-InfoVis0809 0126631:

= Cartogram =

== Definition ==
A Cartogram is a small diagram, on the face of a map, showing quantitative information or an abstracted and simplified map the base of which is not true to scale. Simply we can say cartograms are unique representations of geographical space. They use cartographic outlines to represent data which depends on this source [Bortis and Demers, 2002].

[[Image:USA2.jpg|center|400px|thumb|[Kocmound, 1997] a) traditional choropleth thematic map b) Cartogram]]

On the left side you can see a traditional map of the United states and on the right side a Cartogram of USA depending on the population density.

== Types of Cartograms ==
* Non-Continuous Cartograms
In non-continuous cartograms the regions on the map don't have to be connected to their neighbors. In this type of cartogram it is important to see the shape of the original map. User will recognize the map just because of their borders. The regions in the map are displaying the content with their own size. For an example a region with a smaller population will be smaller than a sector with a higher population [Kocmoud, 1997].

[[Image:noncont.jpg|center|400px|thumb|[Kocmound, 1997] non-continous cartogram]]

* Continuos Cartograms
Different to the non-continuous cartograms, the important point is that the regions in the map are connected to each other. Accordingly the shape of each region is changing their size [Bortis and Demers, 2002]. Therefore the outline of the hole map changes. As we can see in the picture below, France is very distorted but still connected to his neighbors. With changing the shape of this country, the outlines of the whole map has changed [Wikipedia, 2008].

[[Image:europe.jpg|center|400px|thumb|[Wikipedia, 2008] Cartogram of europe using continuos cartograms]]

* Perimeter-Preserving Cartograms
In this version the outline of the map is the same as in the original image. The regions in it are still connected to each other, so the only change is the border of the regions which is moving but still connected to his neighbors [Kocmoud, 1997].
* The usage of different shapes for representation of the regions
One type that can be used is the Dorling Cartogram. In this form the original regions are replaced with circles of varying size. With this kind of shape it is easier to see the difference between the regions. The same strategy is used by Demers which is use squares instead of circles. The positive effect of this is, that there are no free spaces between them [Florisson et al., 2005].

==References==

* [Bortis and Demers, 2002]Ian Bortis, and Steve Demers, USGS, Cartogram Central. Created at: December 7, 2002. http://www.ncgia.ucsb.edu/projects/Cartogram_Central/index.html .
* [Kocmoud, 1997] Christopher James Kocmoud, Constructing Continuous Cartograms:
A Constraint-Based Approach. Created at: December, 1997. http://www-viz.tamu.edu/faculty/house/cartograms/Thesis.html .
*[Florisson et al., 2005] Sander Florisson, Marc van Kreveld, and Bettina Speckmann. Rectangular Cartograms : Construction & Animation. 'Annual Symposium on Computational Geometry'.372–373, 2005.
* [Wikipedia, 2008] Wikipedia. Cartogramm. Retrieved at: October 5, 2008. http://en.wikipedia.org/wiki/Cartogram .

File:Europe.jpg

2008-11-26T07:48:25Z

UE-InfoVis0809 0126631:

== Summary ==

== Copyright status ==

== Source ==
[Wikipedia, 2008] Wikipedia. Cartogramm. Retrieved at: October 5, 2008. http://en.wikipedia.org/wiki/Cartogram .
Retrieved from "http://www.infovis-wiki.net/index.php?title=Teaching:TUW_-_UE_InfoVis_WS_2008/09_-_Gruppe_01_-_Aufgabe_1_-_Cartogram"

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Cartogram

2008-11-26T07:47:45Z

UE-InfoVis0809 0126631:

= Cartogram =

== Definition ==
A Cartogram is a small diagram, on the face of a map, showing quantitative information or an abstracted and simplified map the base of which is not true to scale. Simply we can say cartograms are unique representations of geographical space. They use cartographic outlines to represent data which depends on this source [Bortis and Demers, 2002].

[[Image:USA2.jpg|center|400px|thumb|[Kocmound, 1997] a) traditional choropleth thematic map b) Cartogram]]

On the left side you can see a traditional map of the United states and on the right side a Cartogram of USA depending on the population density.

== Types of Cartograms ==
* Non-Continuous Cartograms
In non-continuous cartograms the regions on the map don't have to be connected to their neighbors. In this type of cartogram it is important to see the shape of the original map. User will recognize the map just because of their borders. The regions in the map are displaying the content with their own size. For an example a region with a smaller population will be smaller than a sector with a higher population [Kocmoud, 1997].

[[Image:noncont.jpg|center|400px|thumb|[Kocmound, 1997]non-continous cartogram]]

* Continuos Cartograms
Different to the non-continuous cartograms, the important point is that the regions in the map are connected to each other. Accordingly the shape of each region is changing their size [Bortis and Demers, 2002]. Therefore the outline of the hole map changes. As we can see in the picture below, France is very distorted but still connected to his neighbors. With changing the shape of this country, the outlines of the whole map has changed [Wikipedia, 2008].

[[Image:europe.jpg|center|400px|thumb|[Wikipedia, 2008] Cartogram of europe using continuos cartograms]]

* Perimeter-Preserving Cartograms
In this version the outline of the map is the same as in the original image. The regions in it are still connected to each other, so the only change is the border of the regions which is moving but still connected to his neighbors [Kocmoud, 1997].
* The usage of different shapes for representation of the regions
One type that can be used is the Dorling Cartogram. In this form the original regions are replaced with circles of varying size. With this kind of shape it is easier to see the difference between the regions. The same strategy is used by Demers which is use squares instead of circles. The positive effect of this is, that there are no free spaces between them [Florisson et al., 2005].

==References==

* [Bortis and Demers, 2002]Ian Bortis, and Steve Demers, USGS, Cartogram Central. Created at: December 7, 2002. http://www.ncgia.ucsb.edu/projects/Cartogram_Central/index.html .
* [Kocmoud, 1997] Christopher James Kocmoud, Constructing Continuous Cartograms:
A Constraint-Based Approach. Created at: December, 1997. http://www-viz.tamu.edu/faculty/house/cartograms/Thesis.html .
*[Florisson et al., 2005] Sander Florisson, Marc van Kreveld, and Bettina Speckmann. Rectangular Cartograms : Construction & Animation. 'Annual Symposium on Computational Geometry'.372–373, 2005.
* [Wikipedia, 2008] Wikipedia. Cartogramm. Retrieved at: October 5, 2008. http://en.wikipedia.org/wiki/Cartogram .

File:Noncont.jpg

2008-11-26T07:46:42Z

UE-InfoVis0809 0126631:

== Summary ==

== Copyright status ==

== Source ==
[Kocmoud, 1997] Christopher James Kocmoud, Constructing Continuous Cartograms: A Constraint-Based Approach. Created at: December, 1997

File:USA2.jpg

2008-11-26T07:45:55Z

UE-InfoVis0809 0126631:

== Summary ==

== Copyright status ==

== Source ==
[Kocmoud, 1997] Christopher James Kocmoud, Constructing Continuous Cartograms:
A Constraint-Based Approach. Created at: December, 1997

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-11-21T20:56:32Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
==Exercise 2==

=== Table to evaluate ===

[[Image:Top25newspapers.gif]]

===Critics on the table===
* The titel doesn´t contain of which year(s) the Top 25 is and you don´t know which period of the year is used. Because the reference source is from March 2007 and it is not possible that the "whole" years 2006 and 2007 are compared.
* The table shows the Top 25, but from the the way the lines are ordered its not easy to get the rank for example the Top 7. Further it´s not easy to follow the horizontal line, because there are no grids and rules .
* The mean of the colum "Increase/Decrease" is not clear, what shall it mean?
* In the colum "Percent" after every data the symbol % is missing and only in some cases a decimal place is published.
* The column "2006" and "2007" is not in chronological order.
* The subtitle electronic editions is used two times.
* A comma is placed to the left of every three digits of numbers, but because of the way numbers are written(aligned to the center) makes them difficult to interpret. So the direct comparison with the other lines is not possible - you can get a false impression of the size of the number.
* The column “Frequency” is not important because there is only one exception.
* It is difficult to track across the rows with this spacing.
* The name of the district is just published in some cases. It is placed with parenthesis in the title.

===Correction on the table ===

[[Image:Tablenewspaper04.jpg]]

===Changes on the table===
* Title should point on the year and the country in which the evaluation takes places. Our new title is: „Top 25 - USA Newspapers with electronic editions 2006/2007“. With this title you know exactly what’s the topic of the table, where the data comes from and in which time period it takes place.
* We insert a first new column. In this column the rank of the Top 25 is registered, so you can easy go to row of the Top 8.
* Percent Numbers should have a + or – in front and a % behind the number to make the it easier to read. Place a percentage sign (i.e., %) immediately to the right of every percentage value (e.g., 8.75%). Numbers should have the same size of decimal place. If they have they have the same size it is easier to see which data is bigger and which is smaller. With a % sign afterwards you know with the first look at the row that every line means a percental number.
* If a header is used for two columns there can be just one header instead of one for every column (i.e. subheader 2006/2007). It is easier to see the dependency of the two rows if the header is used for both of them.
* Because we don’t want to suggest that the columns are more important than the rows data, we’ve used a row fill color the highlight them.
* The Columns are not in chronological order. We have exchanged the rows 2007 and 2006 because the reading direction is from the left to the right.
* Numbers have to be right-aligned with a comma for a thousands digit and a point for a decimal place. Further they should have the same number of decimal place. With the points and commas it is easier to read the numbers and with the same size of the decimal place and the right-alignment it’s a lot easier to see which data is bigger then an other one.
* In some cases the name of the origin of the newspaper is in the title. Sometimes left, right or in the name. We changed this by making a new row with the district of every newspaper. Now you can read this information if you are interested in or just leave it out.
* The value Frequency is for every row except of one the same. We have deleted this row and made a legend under the table, which descripes the behavior. With this step we saved much place with information that is not that important.
* The "***" are replaced by the term n/a - n/a stands for not available.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-11-21T20:54:31Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
==Exercise 2==

=== Table to evaluate ===

[[Image:Top25newspapers.gif]]

===Critics on the table===
* The titel doesn´t contain of which year(s) the Top 25 is and you don´t know which period of the year is used. Because the reference source is from March 2007 and it is not possible that the "whole" years 2006 and 2007 are compared.
* The table shows the Top 25, but from the the way the lines are ordered its not easy to get the rank for example the Top 7. Further it´s not easy to follow the horizontal line, because there are no grids and rules .
* The mean of the colum "Increase/Decrease" is not clear, what shall it mean?
* In the colum "Percent" after every data the symbol % is missing and only in some cases a decimal place is published.
* The column "2006" and "2007" is not in chronological order.
* The subtitle electronic editions is used two times.
* A comma is placed to the left of every three digits of numbers, but because of the way numbers are written(aligned to the center) makes them difficult to interpret. So the direct comparison with the other lines is not possible - you can get a false impression of the size of the number.
* The column “Frequency” is not important because there is only one exception.
* It is difficult to track across the rows with this spacing.
* The name of the district is just published in some cases. It is placed with parenthesis in the title.

===Correction on the table ===

[[Image:Tablenewspaper04.jpg]]

===Changes on the table===
* Title should point on the year and the country in which the evaluation takes places. Our new title is: „Top 25 - USA Newspapers with electronic editions 2006/2007“. With this title you know exactly what’s the topic of the table, where the data comes from and in which time period it takes place.
* We insert a first new column. In this column the rank of the Top 25 is registered, so you can easy go to row of the Top 8.
* Percent Numbers should have a + or – in front and a % behind the number to make the it easier to read. Place a percentage sign (i.e., %) immediately to the right of every percentage value (e.g., 8.75%). Numbers should have the same size of decimal place. If they have they have the same size it is easier to see which data is bigger and which is smaller. With a % sign afterwards you know with the first look at the row that every line means a percental number.
* If a header is used for two columns there can be just one header instead of one for every column (i.e. subheader 2006/2007). It is easier to see the dependency of the two rows if the header is used for both of them.
* Because we don’t want to suggest that the columns are more important than the rows data, we’ve used a row fill color the highlight them.
* The Columns are not in chronological order. We have exchanged the rows 2007 and 2006 because the reading direction is from the left to the right.
* Numbers have to be right-aligned with a comma for a thousands digit and a point for a decimal place. Further they should have the same number of decimal place. With the points and commas it is easier to read the numbers and with the same size of the decimal place and the right-alignment it’s a lot easier to see which data is bigger then an other one.
* In some cases the name of the origin of the newspaper is in the title. Sometimes left, right or in the name. We changed this by making a new row with the district of every newspaper. Now you can read this information if you are interested in or just leave it out.
* The value Frequency is for every row except of one the same. We have deleted this row and made a legend under the table, which descripes the behavior. With this step we saved much place with information that is not that important.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-11-21T20:49:48Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
==Exercise 2==

=== Table to evaluate ===

[[Image:Top25newspapers.gif]]

===Critics on the table===
* The titel doesn´t contain of which year(s) the Top 25 is and you don´t know which period of the year is used. Because the reference source is from March 2007 and it is not possible that the "whole" years 2006 and 2007 are compared.
* The table shows the Top 25, but from the the way the lines are ordered its not easy to get the rank for example the Top 7. Further it´s not easy to follow the horizontal line, because there are no grids and rules .
* The mean of the colum "Increase/Decrease" is not clear, what shall it mean?
* In the colum "Percent" after every data the symbol % is missing and only in some cases a decimal place is published.
* The column "2006" and "2007" is not in chronological order.
* The subtitle electronic editions is used two times.
* A comma is placed to the left of every three digits of numbers, but because of the way numbers are written(aligned to the center) makes them difficult to interpret. So the direct comparison with the other lines is not possible - you can get a false impression of the size of the number.
* The column “Frequency” is not important because there is only one exception.
* It is difficult to track across the rows with this spacing.
* The name of the district is just published in some cases. It is placed with parenthesis in the title.

===Correction on the table ===

[[Image:Tablenewspaper04.jpg]]

===Changes on the table===
* Title should point on the year and the country in which the evaluation takes places. Our new title is: „Top 25 - USA Newspapers with electronic editions 2006/2007“. With this title you know exactly what’s the topic of the table, where the data comes from and in which time period it takes place.
* Percent Numbers should have a + or – in front and a % behind the number to make the it easier to read. Place a percentage sign (i.e., %) immediately to the right of every percentage value (e.g., 8.75%). Numbers should have the same size of decimal place. If they have they have the same size it is easier to see which data is bigger and which is smaller. With a % sign afterwards you know with the first look at the row that every line means a percental number.
* If a header is used for two columns there can be just one header instead of one for every column (i.e. subheader 2006/2007). It is easier to see the dependency of the two rows if the header is used for both of them.
* Because we don’t want to suggest that the columns are more important than the rows data, we’ve used a row fill color the highlight them.
* The Columns are not in chronological order. We have exchanged the rows 2007 and 2006 because the reading direction is from the left to the right.
* Numbers have to be right-aligned with a comma for a thousands digit and a point for a decimal place. Further they should have the same number of decimal place. With the points and commas it is easier to read the numbers and with the same size of the decimal place and the right-alignment it’s a lot easier to see which data is bigger then an other one.
* In some cases the name of the origin of the newspaper is in the title. Sometimes left, right or in the name. We changed this by making a new row with the district of every newspaper. Now you can read this information if you are interested in or just leave it out.
* The value Frequency is for every row except of one the same. We have deleted this row and made a legend under the table, which descripes the behavior. With this step we saved much place with information that is not that important.

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-11-19T11:48:14Z

UE-InfoVis0809 0126631:

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-11-19T11:05:15Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
==Exercise 2==

=== Table to evaluate ===

[[Image:Top25newspapers.gif]]

===Critics on the table===
* The table shows the Top 25, but because of the way the lines are ordered its not easy to get the rank for exampe the Top 7 (From the order the Rank of the Newspapers are not clear). Also it´s not easy to follow the horizontal line, because there is a lack of grids and rules.
* The titel doesn´t contain of which year the Top 25 is.
* The mean of the colum "Increase / Decrease" is not clear, what shall it mean=
* In the colum "Percent" after every data the symbol % is missing.
* The column "2006" and "2007" should be in chronological order.
* Title is bold, but subtitle is not ….. Subtitel besser hervorheben
* Numbers: there is a comma (A comma is placed to the left of every three digits), but the data is center aligned.So the direct comparison with the other lines is not possible - you get an false impression of the number-
*
* The Row “frequency” is not from importance because there is only one exception, would be better as text info with *, so the table body is clear from unimportant data / contains only important data (number).
* Because of the way numbers are written and read, aligning them to the left or
center makes them difficult to interpret.
* It is difficult to track across the rows with this spacing => besser : white space between the rows equal to the height of the rows (siehe Fig. 8.3) In the next example, I’ve exceeded the practical limits of vertical white space, with white space that equals 150% the height of the data. Figure8.4In this case you certainly don’t have any difficulty tracking across the rows, but too few rows now fit on the page
*

===Correction on the table ===

grafic of new table

===Which changes have been made? Why is the changed one better than the original table?===
*Titel sollte sich aufs Jahr beziehen – Top 25 (2007); weiters bezieht es sich auf USA oder ? => Top 25 USA Newspaper … 2007
*bei Prozent + oder -
Nicht nur Prozent sondern auch % (Symbolkraft,visuelle Typen)
Place a percentage sign (i.e., %) immediately to the right of every percentage value (e.g., 8.75%).
* Negative Zahlen in Klammer ? (+- oder rote, grüne Schrift)
* gemeinsamer Header (Unterpunkte 2006/2007)
* grau, weiß horizontale Aufmerksamkeit auf Zeile und nicht auf Spalte!!!
Because we don’t want to suggest that the names of the months or the totals are
more important than the other data, I’ve used a subtle fill color.
*Störend dass zuerst 2007 dann 2006 – um drehen zuerst 2006 und dann 2007 (chronologische Reihenfolge) – Lesefluss von links nach rechts
chronological order of dates and times.
*Zahlen rechtsbündig, mit , für Tausenderstellen bzw. gleiche Anzahl an Nachkommastellen
* Highlights setzen? Mit Zellenhintergrundfarbe oder mit Schriftfarbe

===References===
* [Few, 2004]:Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 8 - Table Design.
* [Wallace, 2004]: Rosa Wallace, Designing Tables, NC State University LabWrite Resources, 2004. http://www.ncsu.edu/labwrite/res/gh/gh-tables.html

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-11-19T11:04:00Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
==EXERCISE 2==

=== Table to evaluate ===

[[Image:Top25newspapers.gif]]

===Critics on the table===
* The table shows the Top 25, but because of the way the lines are ordered its not easy to get the rank for exampe the Top 7 (From the order the Rank of the Newspapers are not clear). Also it´s not easy to follow the horizontal line, because there is a lack of grids and rules.
* The titel doesn´t contain of which year the Top 25 is.
* The mean of the colum "Increase / Decrease" is not clear, what shall it mean=
* In the colum "Percent" after every data the symbol % is missing.
* The column "2006" and "2007" should be in chronological order.
* Title is bold, but subtitle is not ….. Subtitel besser hervorheben
* Numbers: there is a comma (A comma is placed to the left of every three digits), but the data is center aligned.So the direct comparison with the other lines is not possible - you get an false impression of the number-
*
* The Row “frequency” is not from importance because there is only one exception, would be better as text info with *, so the table body is clear from unimportant data / contains only important data (number).
* Because of the way numbers are written and read, aligning them to the left or
center makes them difficult to interpret.
* It is difficult to track across the rows with this spacing => besser : white space between the rows equal to the height of the rows (siehe Fig. 8.3) In the next example, I’ve exceeded the practical limits of vertical white space, with white space that equals 150% the height of the data. Figure8.4In this case you certainly don’t have any difficulty tracking across the rows, but too few rows now fit on the page
*

===Correction on the table ===

grafic of new table

===Which changes have been made? Why is the changed one better than the original table?===
*Titel sollte sich aufs Jahr beziehen – Top 25 (2007); weiters bezieht es sich auf USA oder ? => Top 25 USA Newspaper … 2007
*bei Prozent + oder -
Nicht nur Prozent sondern auch % (Symbolkraft,visuelle Typen)
Place a percentage sign (i.e., %) immediately to the right of every percentage value (e.g., 8.75%).
* Negative Zahlen in Klammer ? (+- oder rote, grüne Schrift)
* gemeinsamer Header (Unterpunkte 2006/2007)
* grau, weiß horizontale Aufmerksamkeit auf Zeile und nicht auf Spalte!!!
Because we don’t want to suggest that the names of the months or the totals are
more important than the other data, I’ve used a subtle fill color.
*Störend dass zuerst 2007 dann 2006 – um drehen zuerst 2006 und dann 2007 (chronologische Reihenfolge) – Lesefluss von links nach rechts
chronological order of dates and times.
*Zahlen rechtsbündig, mit , für Tausenderstellen bzw. gleiche Anzahl an Nachkommastellen
* Highlights setzen? Mit Zellenhintergrundfarbe oder mit Schriftfarbe

===References===
* [Few, 2004]:Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 8 - Table Design.
* [Wallace, 2004]: Rosa Wallace, Designing Tables, NC State University LabWrite Resources, 2004. http://www.ncsu.edu/labwrite/res/gh/gh-tables.html

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-11-19T11:02:58Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
==EXERCISE 2==

=== Table to evaluate ===

[[Image:Top25newspapers.gif]]

===Critics on the table===
* The table shows the Top 25, but because of the way the lines are ordered its not easy to get the rank for exampe the Top 7 (From the order the Rank of the Newspapers are not clear). Also it´s not easy to follow the horizontal line, because there is a lack of grids and rules.
* The titel doesn´t contain of which year the Top 25 is.
* The mean of the colum "Increase / Decrease" is not clear, what shall it mean=
* In the colum "Percent" after every data the symbol % is missing.
* The column "2006" and "2007" should be in chronological order.
* Title is bold, but subtitle is not ….. Subtitel besser hervorheben
* Numbers: there is a comma (A comma is placed to the left of every three digits), but the data is center aligned.So the direct comparison with the other lines is not possible - you get an false impression of the number-
*
* The Row “frequency” is not from importance because there is only one exception, would be better as text info with *, so the table body is clear from unimportant data / contains only important data (number).
* Because of the way numbers are written and read, aligning them to the left or
center makes them difficult to interpret.
* It is difficult to track across the rows with this spacing => besser : white space between the rows equal to the height of the rows (siehe Fig. 8.3) In the next example, I’ve exceeded the practical limits of vertical white space, with white space that equals 150% the height of the data. Figure8.4In this case you certainly don’t have any difficulty tracking across the rows, but too few rows now fit on the page
*

===Correction on the table ===

grafic of new table

===Which changes have been made? ===
*Titel sollte sich aufs Jahr beziehen – Top 25 (2007); weiters bezieht es sich auf USA oder ? => Top 25 USA Newspaper … 2007
*bei Prozent + oder -
Nicht nur Prozent sondern auch % (Symbolkraft,visuelle Typen)
Place a percentage sign (i.e., %) immediately to the right of every percentage value (e.g., 8.75%).
* Negative Zahlen in Klammer ? (+- oder rote, grüne Schrift)
* gemeinsamer Header (Unterpunkte 2006/2007)
* grau, weiß horizontale Aufmerksamkeit auf Zeile und nicht auf Spalte!!!
Because we don’t want to suggest that the names of the months or the totals are
more important than the other data, I’ve used a subtle fill color.
*Störend dass zuerst 2007 dann 2006 – um drehen zuerst 2006 und dann 2007 (chronologische Reihenfolge) – Lesefluss von links nach rechts
chronological order of dates and times.
*Zahlen rechtsbündig, mit , für Tausenderstellen bzw. gleiche Anzahl an Nachkommastellen
* Highlights setzen? Mit Zellenhintergrundfarbe oder mit Schriftfarbe

=== Why is the changed one better than the original table?===

===References===
* [Few, 2004]:Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 8 - Table Design.
* [Wallace, 2004]: Rosa Wallace, Designing Tables, NC State University LabWrite Resources, 2004. http://www.ncsu.edu/labwrite/res/gh/gh-tables.html

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-11-09T21:24:40Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]

=== Zu beurteilende Tabelle ===

[[Image:Top25newspapers.gif]]

==EXERCISE 2==

===Critics on the table===
* Fact1
* Fact2

===Correction on the table ===

grafic of new table

===Which changes have been made? ===
=== Why is the changed one better than the original table?===

===References===
* [Reference 1, ?]....

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-11-09T21:23:34Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]

=== Zu beurteilende Tabelle ===

[[Image:Top25newspapers.gif]]

==EXERCISE 2==

===Critics on the table===
* Fact1
* Fact2

===Correction on the table ===

grafic of new table

===Which changes have been made? Why is it better than the original table?===

===References===
* [Reference 1, ?]....

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2

2008-11-09T21:21:40Z

UE-InfoVis0809 0126631:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]

=== Zu beurteilende Tabelle ===

[[Image:Top25newspapers.gif]]

EXERCISE 2

1. Critics on the table
* Fact1
* Fact2

2. Correction on the table

grafic of new table

3. Which changes have been made? Why is it better than the original table?

4. References
* [Reference 1, ?]....

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

* [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-07T13:46:39Z

UE-InfoVis0809 0126631:

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Cartogram

2008-11-07T13:45:15Z

UE-InfoVis0809 0126631:

= Cartogram =

== Definition ==
A Cartogram is a small diagram, on the face of a map, showing quantitative information or an abstracted and simplified map the base of which is not true to scale. Simply we can say cartograms are unique representations of geographical space. They use cartographic outlines to represent data which depends on this source [Bortis and Demers, 2002].

[[Image:USA2.jpg|center|400px|thumb|[Kocmound, 1997] a) traditional choropleth thematic map b) Cartogram]]

On the left side you can see a traditional map of the United states and on the right side a Cartogram of USA depending on the population density.

== Types of Cartograms ==
* Non-Continuous Cartograms
In non-continuous cartograms the regions on the map don't have to be connected to their neighbors. In this type of cartogram it is important to see the shape of the original map. User will recognize the map just because of their borders. The regions in the map are displaying the content with their own size. For an example a region with a smaller population will be smaller than a sector with a higher population [Kocmoud, 1997].

[[Image:noncont.jpg|center|400px|thumb|[non-continous cartogram]]

* Continuos Cartograms
Different to the non-continuous cartograms, the important point is that the regions in the map are connected to each other. Accordingly the shape of each region is changing their size [Bortis and Demers, 2002]. Therefore the outline of the hole map changes. As we can see in the picture below, France is very distorted but still connected to his neighbors. With changing the shape of this country, the outlines of the whole map has changed [Wikipedia, 2008].

[[Image:europe.jpg|center|400px|thumb|[Wikipedia, 2008] Cartogram of europe using continuos cartograms]]

* Perimeter-Preserving Cartograms
In this version the outline of the map is the same as in the original image. The regions in it are still connected to each other, so the only change is the border of the regions which is moving but still connected to his neighbors [Kocmoud, 1997].
* The usage of different shapes for representation of the regions
One type that can be used is the Dorling Cartogram. In this form the original regions are replaced with circles of varying size. With this kind of shape it is easier to see the difference between the regions. The same strategy is used by Demers which is use squares instead of circles. The positive effect of this is, that there are no free spaces between them [Florisson et al., 2005].

==References==

* [Bortis and Demers, 2002]Ian Bortis, and Steve Demers, USGS, Cartogram Central. Created at: December 7, 2002. http://www.ncgia.ucsb.edu/projects/Cartogram_Central/index.html .
* [Kocmoud, 1997] Christopher James Kocmoud, Constructing Continuous Cartograms:
A Constraint-Based Approach. Created at: December, 1997. http://www-viz.tamu.edu/faculty/house/cartograms/Thesis.html .
*[Florisson et al., 2005] Sander Florisson, Marc van Kreveld, and Bettina Speckmann. Rectangular Cartograms : Construction & Animation. 'Annual Symposium on Computational Geometry'.372–373, 2005.
* [Wikipedia, 2008] Wikipedia. Cartogramm. Retrieved at: October 5, 2008. http://en.wikipedia.org/wiki/Cartogram .

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Cartogram

2008-11-07T13:32:37Z

UE-InfoVis0809 0126631:

= Cartogram =

== Definition ==
A Cartogram is a small diagram, on the face of a map, showing quantitative information or an abstracted and simplified map the base of which is not true to scale. Simply we can say cartograms are unique representations of geographical space. They use cartographic outlines to represent data which depends on this source [Bortis and Demers, 2002].

[[Image:USA2.jpg|center|400px|thumb|[Kocmound, 1997] a) traditional choropleth thematic map b) Cartogram]]

On the left side you can see a traditional map of the United states and on the right side a Cartogram of USA depending on the population density.

== Types of Cartograms ==
* Non-Continuous Cartograms
In non-continuous cartograms the regions on the map don't have to be connected to their neighbors. In this type of cartogram it is important to see the shape of the original map. User will recognize the map just because of their borders. The regions in the map are displaying the content with their own size. For an example a region with a smaller population will be smaller than a sector with a higher population [Kocmoud, 1997].

[[Image:noncont.jpg|center|400px|thumb|[non-continous cartogram]]

* Continuos Cartograms
Different to the non-continuous cartograms, the important point is that the regions in the map are connected to each other. Accordingly the shape of each region is changing their size [Bortis and Demers, 2002]. Therefore the outline of the hole map changes. As we can see in the picture below, France is very distorted but still connected to his neighbors. With changing the shape of this country, the outlines of the whole map has changed [Wikipedia, 2008].

[[Image:europe.jpg|center|400px|thumb|[Wikipedia, 2008] Cartogram of europe using continuos cartograms]]

* Perimeter-Preserving Cartograms
In this version the outline of the map is the same as in the original image. The regions in it are still connected to each other, so the only change is the border of the regions which is moving but still connected to his neighbors [Kocmoud, 1997].
* The usage of different shapes for representation of the regions
One type that can be used is the Dorling Cartogram. In this form the original regions are replaced with circles of varying size. With this kind of shape it is easier to see the difference between the regions. The same strategy is used by Demers which is use squares instead of circles. The positive effect of this is, that there are no free spaces between them [Florisson et al., 2005].

==References==

* [Bortis and Demers, 2002]Ian Bortis, and Steve Demers, USGS, Cartogram Central. Created at: December 7, 2002. http://www.ncgia.ucsb.edu/projects/Cartogram_Central/index.html .
* [Wikipedia, 2008] Wikipedia. Cartogramm. Retrieved at: October 5, 2008. http://en.wikipedia.org/wiki/Cartogram .
* [Kocmoud, 1997] Christopher James Kocmoud, Constructing Continuous Cartograms:
A Constraint-Based Approach. Created at: December, 1997. http://www-viz.tamu.edu/faculty/house/cartograms/Thesis.html .
*[Florisson et al., 2005] Sander Florisson, Marc van Kreveld, and Bettina Speckmann. Rectangular Cartograms : Construction & Animation. 'Annual Symposium on Computational Geometry'.372–373, 2005.

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Cartogram

2008-11-07T13:29:47Z

UE-InfoVis0809 0126631:

= Cartogram =

== Definition ==
A Cartogram is a small diagram, on the face of a map, showing quantitative information or an abstracted and simplified map the base of which is not true to scale. Simply we can say cartograms are unique representations of geographical space. They use cartographic outlines to represent data which depends on this source [Bortis and Demers, 2002].

[[Image:USA2.jpg|center|400px|thumb|[Kocmound, 1997] a) traditional choropleth thematic map b) Cartogram]]

On the left side you can see a traditional map of the United states and on the right side a Cartogram of USA depending on the population density.

== Types of Cartograms ==
* Non-Continuous Cartograms
In non-continuous cartograms the regions on the map don't have to be connected to their neighbors. In this type of cartogram it is important to see the shape of the original map. User will recognize the map just because of their borders. The regions in the map are displaying the content with their own size. For an example a region with a smaller population will be smaller than a sector with a higher population [Kocmoud, 1997].

[[Image:noncont.jpg|center|400px|thumb|[non-continous cartogram]]

* Continuos Cartograms
Different to the non-continuous cartograms, the important point is that the regions in the map are connected to each other. Accordingly the shape of each region is changing their size [Bortis and Demers, 2002]. Therefore the outline of the hole map changes. As we can see in the picture below, France is very distorted but still connected to his neighbors. With changing the shape of this country, the outlines of the whole map has changed [Wikipedia, 2008].

[[Image:europe.jpg|center|400px|thumb|[Wikipedia, 2008] Cartogram of europe using continuos cartograms]]

* Perimeter-Preserving Cartograms
In this version the outline of the map is the same as in the original image. The regions in it are still connected to each other, so the only change is the border of the regions which is moving but still connected to his neighbors [Kocmoud, 1997].
* The usage of different shapes for representation of the regions
One type that can be used is the Dorling Cartogram. In this form the original regions are replaced with circles of varying size. With this kind of shape it is easier to see the difference between the regions. The same strategy is used by Demers which is use squares instead of circles. The positive effect of this is, that there are no free spaces between them [Florisson et al., 2005].

==References==

* [Bortis and Demers, 2002]Ian Bortis, and Steve Demers, USGS, Cartogram Central. Created at: December 7, 2002. http://www.ncgia.ucsb.edu/projects/Cartogram_Central/index.html .
* [Wikipedia, 2008] Wikipedia. Cartogramm. Created at: October 5, 2008. http://en.wikipedia.org/wiki/Cartogram .
* [Kocmoud, 1997] Christopher James Kocmoud, Constructing Continuous Cartograms:
A Constraint-Based Approach. Created at: December, 1997. http://www-viz.tamu.edu/faculty/house/cartograms/Thesis.html .
*[Florisson et al., 2005] Sander Florisson, Marc van Kreveld, and Bettina Speckmann. Rectangular Cartograms : Construction & Animation. 'Annual Symposium on Computational Geometry'.372–373, 2005.

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Cartogram

2008-11-07T13:28:28Z

UE-InfoVis0809 0126631:

= Cartogram =

== Definition ==
A Cartogram is a small diagram, on the face of a map, showing quantitative information or an abstracted and simplified map the base of which is not true to scale. Simply we can say cartograms are unique representations of geographical space. They use cartographic outlines to represent data which depends on this source [Bortis and Demers, 2002].

[[Image:USA2.jpg|center|400px|thumb|[Kocmound, 1997] a) traditional choropleth thematic map b) Cartogram]]

On the left side you can see a traditional map of the United states and on the right side a Cartogram of USA depending on the population density.

== Types of Cartograms ==
* Non-Continuous Cartograms
In non-continuous cartograms the regions on the map don't have to be connected to their neighbors. In this type of cartogram it is important to see the shape of the original map. User will recognize the map just because of their borders. The regions in the map are displaying the content with their own size. For an example a region with a smaller population will be smaller than a sector with a higher population [Kocmoud, 1997].

[[Image:noncont.jpg|center|400px|thumb|[non-continous cartogram]]

* Continuos Cartograms
Different to the non-continuous cartograms, the important point is that the regions in the map are connected to each other. Accordingly the shape of each region is changing their size [Bortis and Demers, 2002]. Therefore the outline of the hole map changes. As we can see in the picture below, France is very distorted but still connected to his neighbors. With changing the shape of this country, the outlines of the whole map has changed. [Wikipedia, 2008]

[[Image:europe.jpg|center|400px|thumb|[Wikipedia, 2008] Cartogram of europe using continuos cartograms]]

* Perimeter-Preserving Cartograms
In this version the outline of the map is the same as in the original image. The regions in it are still connected to each other, so the only change is the border of the regions which is moving but still connected to his neighbors [Kocmoud, 1997].
* The usage of different shapes for representation of the regions
One type that can be used is the Dorling Cartogram. In this form the original regions are replaced with circles of varying size. With this kind of shape it is easier to see the difference between the regions. The same strategy is used by Demers which is use squares instead of circles. The positive effect of this is, that there are no free spaces between them [Florisson et al., 2005].

==References==

* [Bortis and Demers, 2002]Ian Bortis, and Steve Demers, USGS, Cartogram Central. Created at: December 7, 2002. http://www.ncgia.ucsb.edu/projects/Cartogram_Central/index.html .
* [Wikipedia, 2008] Wikipedia. Cartogramm. Created at: October 5, 2008. http://en.wikipedia.org/wiki/Cartogram .
* [Kocmoud, 1997] Christopher James Kocmoud, Constructing Continuous Cartograms:
A Constraint-Based Approach. Created at: December, 1997. http://www-viz.tamu.edu/faculty/house/cartograms/Thesis.html .
*[Florisson et al., 2005] Sander Florisson, Marc van Kreveld, and Bettina Speckmann. Rectangular Cartograms : Construction & Animation. 'Annual Symposium on Computational Geometry'.372–373, 2005.

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-07T13:12:48Z

UE-InfoVis0809 0126631:

= Visual Encoding =

== Definition ==
Visual encoding is the set of techniques enabling the representation of data on a screen or on paper. It comprises of the use of shapes, colours, areas and other visual variables that make it possible to associate data variables to graphic variables [Dürsteler, 2005]. Visual encodings are mappings of information to display elements [Munzner, 2000].

== Techniques of Visual Encoding ==

The fundamental substrate of visualizations is spatial position. Marks such as points, lines, or area-covering elements can be placed on this substrate. These marks can carry additional information independent of their spatial position, such as size, greyscale luminance (brightness) value, surface texture density, color hue, color saturation, curvature, angle, and shape [Munzner, 2000].

* Space
* Marks
* Connections & Enclosures
* Retinal Properties
* Temporal Encoding
* Viewpoint Transformation

=== Space ===
When you think about an empty paper as the beginning of a visualisation, the space between some possible object is one of the most powerful aspects to give something an important note.

=== Marks ===
Marks are the visible things that occur in space [Card et al., 1999], and are simply any graphical symbol visible on a display medium [Ignatius and Senay, 1999].
There are four types of simple Marks :
* Points
* Lines
* Areas
* Volumes

=== Connections & enclosures ===
Connections and enclosures build the important dependencies between the objects (marks). Connections show a relationship between objects, while enclosures can also indicate related objects.

=== Retinal properties ===
A retinal encoding is any variation of the marks that the retina of the eye can perceive besides position [Ignatius and Senay, 1999]. They are the informations that are carried by marks, such as crispness, shape, resolution, transperancy, color(value,hue & saturation), grayscale [Munzner, 2000].
Retinal properties describe how objects (marks) look like.

[[Image:retinal.JPG|center|400px|thumb|[Card et al., 1999] Retinal properties]]

=== Temporal encoding ===
A temporal encoding shows how the marks' properties vary over time.
It's the encoding which depends on the temporal changes of marks (mark position and their retinal properties) [Ignatius and Senay, 1999].

=== Viewpoint transformations ===

Viewpoint transformations modify interactively and augment Visual Structures to turn static presentations into visualizations by establishing graphical parameters to create Views of Visual Structures [Card et al., 1999; Jacko and Sears, 2002] in other words it is the modification of the view position of the viewer (or in general the modification of viewing parameters), thus enhancing the visual perception.

There are three common view transformations :
* Location Probes : Usage of Location in the visual structures to reveal additional info
* Viewpoint control : Moving the viewpoint to create visualisation : Pan,zoom,clip the viewpoint.
* Distortion : Creating a focus area and context area.

[[Image:filmfinder_sm.gif|center|400px|thumb|[Waloszek, 2008] FilmFinder]]

==References==
* [Dürsteler, 2005] Juan C. Dürsteler, Web Content Mining Visualisation. Created at: November 7. http://www.infovis.net/printMag.php?num=175&lang=2.
* [Munzner, 2000] Tamara Munzner, Interactive Visualization of Large Graphs and Networks. Ph.D. dissertation, Stanford University. June 2000, http://graphics.stanford.edu/papers/munzner_thesis/.
* [Ignatius and Senay, 1999] Ignatius Eve, and Senay Hikmet, Data,vocabulary,marks,composition rules and visual perception rules. Created at: ?. http://cose.math.bas.bg/Sci_Visualization/visConcepts/concepts/marks.htm.
*[Jacko and Sears, 2002] Julie A. Jacko, and Andrew Sears.''The Human-computer Interaction Handbook: Fundamentals, Evolving Technologies.''Lawrence Erlbaum Assoc in, NY, 2002.
*[Card et al., 1999] Stuart K. Card, Jock D. Mackinlay, and Ben Schneiderman. ''Readings in Information Visualization. Using Vision to Think.''Morgan Kaufman Publ Inc, San Diego, 1990.
* [Waloszek, 2008] Gerd Waloszek, SAP AG, SAP User Experience,Selecting Objects By Attributes – Part II. Created at: October 3. http://www.sapdesignguild.org/.../attributes_2.asp .

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-07T13:00:24Z

UE-InfoVis0809 0126631:

= Visual Encoding =

== Definition ==
Visual encoding is the set of techniques enabling the representation of data on a screen or on paper. It comprises of the use of shapes, colours, areas and other visual variables that make it possible to associate data variables to graphic variables [Dürsteler, 2005]. Visual encodings are mappings of information to display elements [Munzner, 2000].

== Techniques of Visual Encoding ==

The fundamental substrate of visualizations is spatial position. Marks such as points, lines, or area-covering elements can be placed on this substrate. These marks can carry additional information independent of their spatial position, such as size, greyscale luminance (brightness) value, surface texture density, color hue, color saturation, curvature, angle, and shape [Munzner,2000].

* Space
* Marks
* Connections & Enclosures
* Retinal Properties
* Temporal Encoding
* Viewpoint Transformation

=== Space ===
When you think about an empty paper as the beginning of a visualisation, the space between some possible object is one of the most powerful aspects to give something an important note.

=== Marks ===
Marks are the visible things that occur in space [Card et al., 1999], and are simply any graphical symbol visible on a display medium [Ignatius and Senay, 1999].
There are four types of simple Marks :
* Points
* Lines
* Areas
* Volumes

=== Connections & enclosures ===
Connections and enclosures build the important dependencies between the objects (marks). Connections show a relationship between objects, while enclosures can also indicate related objects.

=== Retinal properties ===
A retinal encoding is any variation of the marks that the retina of the eye can perceive besides position [Ignatius and Senay, 1999]. They are the informations that are carried by marks, such as crispness, shape, resolution, transperancy, color(value,hue&saturation), grayscale [Munzner, 2000].
Retinal properties describe how objects (marks) look like.

Abbildung S. 30 von Readings in Information Visualization
[[Image:retinal.JPG|center|400px|thumb|[Card] Retinal properties]]

=== Temporal encoding ===
A temporal encoding shows how the marks' properties vary over time [Ignatius,Eve&Senay,Hikmet].

It's the encoding which depends on the temporal changes of marks (mark position and their retinal properties). [ todo : Source ]

=== Viewpoint transformations ===

Viewpoint transformations modify interactively and augment Visual Structures to turn static presentations into visualizations by establishing graphical parameters to create Views of Visual Structures [Card], in other words it is the modification of the view position of the viewer (or in general the modification of viewing parameters), thus enhancing the visual perception.

There are three common view transformations :
* Location Probes : Usage of Location in the visual structures to reveal additional info
* Viewpoint control : Moving the viewpoint to create visualisation : Pan,zoom,clip the viewpoint.
* Distortion : Creating a focus area and context area.

[[Image:filmfinder_sm.gif|center|400px|thumb|[Waloszek, 2008] FilmFinder]]

==References==
* [Dürsteler, 2005] Juan C. Dürsteler, Web Content Mining Visualisation. Created at: November 7. http://www.infovis.net/printMag.php?num=175&lang=2.
* [Munzner, 2000] Tamara Munzner, Interactive Visualization of Large Graphs and Networks. Ph.D. dissertation, Stanford University. June 2000, http://graphics.stanford.edu/papers/munzner_thesis/.
* [Ignatius and Senay, 1999] Ignatius Eve, and Senay Hikmet, Data,vocabulary,marks,composition rules and visual perception rules. Created at: ?. http://cose.math.bas.bg/Sci_Visualization/visConcepts/concepts/marks.htm.
*[Jacko and Sears, 2002]Julie A. Jacko, and Andrew Sears.''The Human-computer Interaction Handbook: Fundamentals, Evolving Technologies.''Lawrence Erlbaum Assoc in, NY, 2002.
*[Card et al., 1999]Stuart K. Card, Jock D. Mackinlay, and Ben Schneiderman. ''Readings in Information Visualization. Using Vision to Think.''Morgan Kaufman Publ Inc, San Diego, 1990.
* [Waloszek, 2008]Gerd Waloszek, SAP AG, SAP User Experience,Selecting Objects By Attributes – Part II. Created at: October 3. http://www.sapdesignguild.org/.../attributes_2.asp .

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-07T12:54:42Z

UE-InfoVis0809 0126631:

= Visual Encoding =

== Definition ==
Visual encoding is the set of techniques enabling the representation of data on a screen or on paper. It comprises of the use of shapes, colours, areas and other visual variables that make it possible to associate data variables to graphic variables [Dürsteler, 2005]. Visual encodings are mappings of information to display elements [Munzner, 2000].

== Techniques of Visual Encoding ==

The fundamental substrate of visualizations is spatial position. Marks such as points, lines, or area-covering elements can be placed on this substrate. These marks can carry additional information independent of their spatial position, such as size, greyscale luminance (brightness) value, surface texture density, color hue, color saturation, curvature, angle, and shape [Munzner,2000].

* Space
* Marks
* Connections & Enclosures
* Retinal Properties
* Temporal Encoding
* Viewpoint Transformation

=== Space ===
When you think about an empty paper as the beginning of a visualisation, the space between some possible object is one of the most powerful aspects to give something an important note.

=== Marks ===
Marks are the visible things that occur in space [Jacko], and are simply any graphical symbol visible on a display medium[Ignatius,Eve&Senay,Hikmet].
There are four types of simple Marks :
* Points
* Lines
* Areas
* Volumes

=== Connections & enclosures ===
Connections and enclosures build the important dependencies between the objects (marks). Connections show a relationship between objects, while enclosures can also indicate related objects.

=== Retinal properties ===
A retinal encoding is any variation of the marks that the retina of the eye can perceive besides position [Ignatius,Eve&Senay,Hikmet]. They are the informations that are carried by marks, such as crispness, shape, resolution, transperancy, color(value,hue&saturation), grayscale[Munzner, 2000].
Retinal properties describe how objects (marks) look like.

Abbildung S. 30 von Readings in Information Visualization
[[Image:retinal.JPG|center|400px|thumb|[Card] Retinal properties]]

=== Temporal encoding ===
A temporal encoding shows how the marks' properties vary over time [Ignatius,Eve&Senay,Hikmet].

It's the encoding which depends on the temporal changes of marks (mark position and their retinal properties). [ todo : Source ]

=== Viewpoint transformations ===

Viewpoint transformations modify interactively and augment Visual Structures to turn static presentations into visualizations by establishing graphical parameters to create Views of Visual Structures [Card], in other words it is the modification of the view position of the viewer (or in general the modification of viewing parameters), thus enhancing the visual perception.

There are three common view transformations :
* Location Probes : Usage of Location in the visual structures to reveal additional info
* Viewpoint control : Moving the viewpoint to create visualisation : Pan,zoom,clip the viewpoint.
* Distortion : Creating a focus area and context area.

[[Image:filmfinder_sm.gif|center|400px|thumb|[Waloszek] FilmFinder]]

==References==
* [Dürsteler, 2005] Juan C. Dürsteler, Web Content Mining Visualisation. Created at: November 7. http://www.infovis.net/printMag.php?num=175&lang=2.
* [Munzner, 2000] Tamara Munzner, Interactive Visualization of Large Graphs and Networks. Ph.D. dissertation, Stanford University. June 2000, http://graphics.stanford.edu/papers/munzner_thesis/.
* [Ignatius and Senay, 1999] Ignatius,Eve and Senay, Hikmet, Data,vocabulary,marks,composition rules and visual perception rules. Created at: ?. http://cose.math.bas.bg/Sci_Visualization/visConcepts/concepts/marks.htm.
*[Jacko and Sears, 2002]Julie A. Jacko, and Andrew Sears.''The Human-computer Interaction Handbook: Fundamentals, Evolving Technologies.''Lawrence Erlbaum Assoc in, NY, 2002.
*[Card et al., 1999]Stuart K. Card, Jock D. Mackinlay, and Ben Schneiderman. ''Readings in Information Visualization. Using Vision to Think.''Morgan Kaufman Publ Inc, San Diego, 1990.
* [Waloszek, 2008]Gerd Waloszek, SAP AG, SAP User Experience,Selecting Objects By Attributes – Part II. Created at: October 3. http://www.sapdesignguild.org/.../attributes_2.asp .

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-07T12:52:13Z

UE-InfoVis0809 0126631:

= Visual Encoding =

== Definition ==
Visual encoding is the set of techniques enabling the representation of data on a screen or on paper. It comprises of the use of shapes, colours, areas and other visual variables that make it possible to associate data variables to graphic variables [Dürsteler, 2005]. Visual encodings are mappings of information to display elements [Munzner, 2000].

== Techniques of Visual Encoding ==

The fundamental substrate of visualizations is spatial position. Marks such as points, lines, or area-covering elements can be placed on this substrate. These marks can carry additional information independent of their spatial position, such as size, greyscale luminance (brightness) value, surface texture density, color hue, color saturation, curvature, angle, and shape [Munzner,2000].

* Space
* Marks
* Connections & Enclosures
* Retinal Properties
* Temporal Encoding
* Viewpoint Transformation

=== Space ===
When you think about an empty paper as the beginning of a visualisation, the space between some possible object is one of the most powerful aspects to give something an important note.

=== Marks ===
Marks are the visible things that occur in space [Jacko], and are simply any graphical symbol visible on a display medium[Ignatius,Eve&Senay,Hikmet].
There are four types of simple Marks :
* Points
* Lines
* Areas
* Volumes

=== Connections & enclosures ===
Connections and enclosures build the important dependencies between the objects (marks). Connections show a relationship between objects, while enclosures can also indicate related objects.

=== Retinal properties ===
A retinal encoding is any variation of the marks that the retina of the eye can perceive besides position [Ignatius,Eve&Senay,Hikmet]. They are the informations that are carried by marks, such as crispness, shape, resolution, transperancy, color(value,hue&saturation), grayscale[Munzner, 2000].
Retinal properties describe how objects (marks) look like.

Abbildung S. 30 von Readings in Information Visualization
[[Image:retinal.JPG|center|400px|thumb|[Card] Retinal properties]]

=== Temporal encoding ===
A temporal encoding shows how the marks' properties vary over time [Ignatius,Eve&Senay,Hikmet].

It's the encoding which depends on the temporal changes of marks (mark position and their retinal properties). [ todo : Source ]

=== Viewpoint transformations ===

Viewpoint transformations modify interactively and augment Visual Structures to turn static presentations into visualizations by establishing graphical parameters to create Views of Visual Structures [Card], in other words it is the modification of the view position of the viewer (or in general the modification of viewing parameters), thus enhancing the visual perception.

There are three common view transformations :
* Location Probes : Usage of Location in the visual structures to reveal additional info
* Viewpoint control : Moving the viewpoint to create visualisation : Pan,zoom,clip the viewpoint.
* Distortion : Creating a focus area and context area.

[[Image:filmfinder_sm.gif|center|400px|thumb|[Waloszek] FilmFinder]]

==References==
* [Dürsteler, 2005] Juan C. Dürsteler, Web Content Mining Visualisation. Created at: November 7. http://www.infovis.net/printMag.php?num=175&lang=2.
* [Munzner, 2000] Tamara Munzner, Interactive Visualization of Large Graphs and Networks. Ph.D. dissertation, Stanford University. June 2000, http://graphics.stanford.edu/papers/munzner_thesis/.
* [Ignatius and Senay, 1999] Ignatius,Eve and Senay, Hikmet, Data,vocabulary,marks,composition rules and visual perception rules. Created at: ?. http://cose.math.bas.bg/Sci_Visualization/visConcepts/concepts/marks.htm.
*[Jacko and Sears, 2002]Julie A. Jacko, and Andrew Sears.''The Human-computer Interaction Handbook: Fundamentals, Evolving Technologies.''Lawrence Erlbaum Assoc in, NY,2002.
*[Card et al., 1999]Stuart K. Card, Jock D. Mackinlay, and Ben Schneiderman. ''Readings in Information Visualization. Using Vision to Think.''Morgan Kaufman Publ Inc, San Diego, 1990.
* [Waloszek, 2008]Gerd Waloszek, SAP AG, SAP User Experience,Selecting Objects By Attributes – Part II. Created at: October 3. http://www.sapdesignguild.org/.../attributes_2.asp

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-07T12:39:43Z

UE-InfoVis0809 0126631:

= Visual Encoding =

== Definition ==
Visual encoding is the set of techniques enabling the representation of data on a screen or on paper. It comprises of the use of shapes, colours, areas and other visual variables that make it possible to associate data variables to graphic variables [Dürsteler, 2005]. Visual encodings are mappings of information to display elements [Munzner, 2000].

== Techniques of Visual Encoding ==

The fundamental substrate of visualizations is spatial position. Marks such as points, lines, or area-covering elements can be placed on this substrate. These marks can carry additional information independent of their spatial position, such as size, greyscale luminance (brightness) value, surface texture density, color hue, color saturation, curvature, angle, and shape [Munzner,2000].

* Space
* Marks
* Connections & Enclosures
* Retinal Properties
* Temporal Encoding
* Viewpoint Transformation

=== Space ===
When you think about an empty paper as the beginning of a visualisation, the space between some possible object is one of the most powerful aspects to give something an important note.

=== Marks ===
Marks are the visible things that occur in space [Jacko], and are simply any graphical symbol visible on a display medium[Ignatius,Eve&Senay,Hikmet].
There are four types of simple Marks :
* Points
* Lines
* Areas
* Volumes

=== Connections & enclosures ===
Connections and enclosures build the important dependencies between the objects (marks). Connections show a relationship between objects, while enclosures can also indicate related objects.

=== Retinal properties ===
A retinal encoding is any variation of the marks that the retina of the eye can perceive besides position [Ignatius,Eve&Senay,Hikmet]. They are the informations that are carried by marks, such as crispness, shape, resolution, transperancy, color(value,hue&saturation), grayscale[Munzner, 2000].
Retinal properties describe how objects (marks) look like.

Abbildung S. 30 von Readings in Information Visualization
[[Image:retinal.JPG|center|400px|thumb|[Card] Retinal properties]]

=== Temporal encoding ===
A temporal encoding shows how the marks' properties vary over time [Ignatius,Eve&Senay,Hikmet].

It's the encoding which depends on the temporal changes of marks (mark position and their retinal properties). [ todo : Source ]

=== Viewpoint transformations ===

Viewpoint transformations modify interactively and augment Visual Structures to turn static presentations into visualizations by establishing graphical parameters to create Views of Visual Structures [Card], in other words it is the modification of the view position of the viewer (or in general the modification of viewing parameters), thus enhancing the visual perception.

There are three common view transformations :
* Location Probes : Usage of Location in the visual structures to reveal additional info
* Viewpoint control : Moving the viewpoint to create visualisation : Pan,zoom,clip the viewpoint.
* Distortion : Creating a focus area and context area.

[[Image:filmfinder_sm.gif|center|400px|thumb|[Waloszek] FilmFinder]]

==References==
* [Dürsteler, 2005] Juan C. Dürsteler, Web Content Mining Visualisation. Created at: November 7. http://www.infovis.net/printMag.php?num=175&lang=2
* [Munzner,2000] Tamara Munzner, Interactive Visualization of Large Graphs and Networks. Ph.D. dissertation, Stanford University, June 2000. http://graphics.stanford.edu/papers/munzner_thesis/
* [Ignatius,Eve&Senay,Hikmet] Data,vocabulary,marks,composition rules and visual perception rules, EN: http://cose.math.bas.bg/Sci_Visualization/visConcepts/concepts/marks.htm
*[Jacko, 2002]Julie A. Jacko, Andrew Sears.''The Human-computer Interaction Handbook: Fundamentals, Evolving Technologies.''Lawrence Erlbaum Assoc in, 2002
*[Card, 1999]Stuart K. Card, Jock D. Mackinlay, Ben Schneiderman. ''Readings in Information Visualization. Using Vision to Think.'',Morgan Kaufman Publ Inc, 1990.
* [Waloszek, 2008]Gerd Waloszek, SAP AG, SAP User Experience, ''Selecting Objects By Attributes – Part II '' Created at: October 3, 2008 03/10/2008. www.sapdesignguild.org/.../attributes_2.asp

File:Filmfinder sm.gif

2008-11-06T20:54:19Z

UE-InfoVis0809 0126631:

== Summary ==

== Copyright status ==

== Source ==
Selecting Objects By Attributes – Part II
By Gerd Waloszek, SAP AG, SAP User Experience – 03/10/2008
www.sapdesignguild.org/.../attributes_2.asp

File:Filmfinder sm.gif

2008-11-06T20:53:31Z

UE-InfoVis0809 0126631: New page: == Summary == == Copyright status == == Source ==

== Summary ==

== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-06T20:52:56Z

UE-InfoVis0809 0126631:

= Visual Encoding =

== Definition ==
Visual encoding is the set of techniques enabling the representation of data on a screen or on paper. It comprises of the use of shapes, colours, areas and other visual variables that make it possible to associate data variables to graphic variables [Dürsteler, 2005]. Visual encodings are mappings of information to display elements [Munzner, 2000].

== Techniques of Visual Encoding ==

The fundamental substrate of visualizations is spatial position. Marks such as points, lines, or area-covering elements can be placed on this substrate. These marks can carry additional information independent of their spatial position, such as size, greyscale luminance (brightness) value, surface texture density, color hue, color saturation, curvature, angle, and shape [Munzner,2000].

* Space
* Marks
* Connections & Enclosures
* Retinal Properties
* Temporal Encoding
* Viewpoint Transformation

=== Space ===
When you think about an empty paper as the beginning of a visualisation, the space between some possible object is one of the most powerful aspects to give something an important note.

=== Marks ===
Marks are the visible things that occur in space [Jacko], and are simply any graphical symbol visible on a display medium[Ignatius,Eve&Senay,Hikmet].
There are four types of simple Marks :
* Points
* Lines
* Areas
* Volumes

=== Connections & enclosures ===
Connections and enclosures build the important dependencies between the objects (marks). Connections show a relationship between objects, while enclosures can also indicate related objects.

=== Retinal properties ===
A retinal encoding is any variation of the marks that the retina of the eye can perceive besides position [Ignatius,Eve&Senay,Hikmet]. They are the informations that are carried by marks, such as crispness, shape, resolution, transperancy, color(value,hue&saturation), grayscale[Munzner, 2000].
Retinal properties describe how objects (marks) look like.

Abbildung S. 30 von Readings in Information Visualization
[[Image:retinal.JPG|center|400px|thumb|[Card] Retinal properties]]

=== Temporal encoding ===
A temporal encoding shows how the marks' properties vary over time [Ignatius,Eve&Senay,Hikmet].

It's the encoding which depends on the temporal changes of marks (mark position and their retinal properties). [ todo : Source ]

=== Viewpoint transformations ===

Viewpoint transformations modify interactively and augment Visual Structures to turn static presentations into visualizations by establishing graphical parameters to create Views of Visual Structures [Card], in other words it is the modification of the view position of the viewer (or in general the modification of viewing parameters), thus enhancing the visual perception.

There are three common view transformations :
* Location Probes : Usage of Location in the visual structures to reveal additional info
* Viewpoint control : Moving the viewpoint to create visualisation : Pan,zoom,clip the viewpoint.
* Distortion : Creating a focus area and context area.

[[Image:filmfinder_sm.gif|center|400px|thumb|[Waloszek] FilmFinder]]

==References==
* [Dürsteler, 2005] Web Content Mining Visualisation , EN:http://www.infovis.net/printMag.php?num=175&lang=2
* [Munzner,2000] Interactive Visualization of Large Graphs and Networks, EN: http://graphics.stanford.edu/papers/munzner_thesis/
* [Card,1999] Readings in Information visualization : Using vision to think, EN: http://books.google.com/books?id=wdh2gqWfQmgC/
* [Ignatius,Eve&Senay,Hikmet] Data,vocabulary,marks,composition rules and visual perception rules, EN: http://cose.math.bas.bg/Sci_Visualization/visConcepts/concepts/marks.htm
*Julie A. Jacko, Andrew Sears, 2003, The Human-computer Interaction Handbook: Fundamentals, Evolving Technologies
*Readings in Information Visualization Von Stuart K. Card, Jock D. Mackinlay, Ben
*Selecting Objects By Attributes – Part II
By Gerd Waloszek, SAP AG, SAP User Experience – 03/10/2008 - www.sapdesignguild.org/.../attributes_2.asp

File:Retinal.JPG

2008-11-06T20:38:08Z

UE-InfoVis0809 0126631: Retinal Properties

== Summary ==
Retinal Properties
== Copyright status ==

== Source ==
Readings in Information Visualization (Stuart K. Card, Jock D. Mackinlay, Ben) - page 30

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-06T20:36:56Z

UE-InfoVis0809 0126631:

= Visual Encoding =

== Definition ==
Visual encoding is the set of techniques enabling the representation of data on a screen or on paper. It comprises of the use of shapes, colours, areas and other visual variables that make it possible to associate data variables to graphic variables [Dürsteler, 2005]. Visual encodings are mappings of information to display elements [Munzner, 2000].

== Techniques of Visual Encoding ==

The fundamental substrate of visualizations is spatial position. Marks such as points, lines, or area-covering elements can be placed on this substrate. These marks can carry additional information independent of their spatial position, such as size, greyscale luminance (brightness) value, surface texture density, color hue, color saturation, curvature, angle, and shape [Munzner,2000].

* Space
* Marks
* Connections & Enclosures
* Retinal Properties
* Temporal Encoding
* Viewpoint Transformation

=== Space ===
When you think about an empty paper as the beginning of a visualisation, the space between some possible object is one of the most powerful aspects to give something an important note.

=== Marks ===
Marks are the visible things that occur in space [Jacko], and are simply any graphical symbol visible on a display medium[Ignatius,Eve&Senay,Hikmet].
There are four types of simple Marks :
* Points
* Lines
* Areas
* Volumes

=== Connections & enclosures ===
Connections and enclosures build the important dependencies between the objects (marks). Connections show a relationship between objects, while enclosures can also indicate related objects.

=== Retinal properties ===
A retinal encoding is any variation of the marks that the retina of the eye can perceive besides position [Ignatius,Eve&Senay,Hikmet]. They are the informations that are carried by marks, such as crispness, shape, resolution, transperancy, color(value,hue&saturation), grayscale[Munzner, 2000].
Retinal properties describe how objects (marks) look like.

Abbildung S. 30 von Readings in Information Visualization
[[Image:retinal.JPG|center|400px|thumb|[Card] Retinal properties]]

=== Temporal encoding ===
A temporal encoding shows how the marks' properties vary over time [Ignatius,Eve&Senay,Hikmet].

It's the encoding which depends on the temporal changes of marks (mark position and their retinal properties). [ todo : Source ]

=== Viewpoint transformations ===

Viewpoint transformations modify interactively and augment Visual Structures to turn static presentations into visualizations by establishing graphical parameters to create Views of Visual Structures [Card], in other words it is the modification of the view position of the viewer (or in general the modification of viewing parameters), thus enhancing the visual perception.

There are three common view transformations :
* Location Probes : Usage of Location in the visual structures to reveal additional info
* Viewpoint control : Moving the viewpoint to create visualisation : Pan,zoom,clip the viewpoint.
* Distortion : Creating a focus area and context area.

==References==
* [Dürsteler, 2005] Web Content Mining Visualisation , EN:http://www.infovis.net/printMag.php?num=175&lang=2
* [Munzner,2000] Interactive Visualization of Large Graphs and Networks, EN: http://graphics.stanford.edu/papers/munzner_thesis/
* [Card,1999] Readings in Information visualization : Using vision to think, EN: http://books.google.com/books?id=wdh2gqWfQmgC/
* [Ignatius,Eve&Senay,Hikmet] Data,vocabulary,marks,composition rules and visual perception rules, EN: http://cose.math.bas.bg/Sci_Visualization/visConcepts/concepts/marks.htm
*Julie A. Jacko, Andrew Sears, 2003, The Human-computer Interaction Handbook: Fundamentals, Evolving Technologies
*Readings in Information Visualization Von Stuart K. Card, Jock D. Mackinlay, Ben

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-06T20:33:50Z

UE-InfoVis0809 0126631:

= Visual Encoding =

== Definition ==
Visual encoding is the set of techniques enabling the representation of data on a screen or on paper. It comprises of the use of shapes, colours, areas and other visual variables that make it possible to associate data variables to graphic variables [Dürsteler, 2005]. Visual encodings are mappings of information to display elements [Munzner, 2000].

== Techniques of Visual Encoding ==

The fundamental substrate of visualizations is spatial position. Marks such as points, lines, or area-covering elements can be placed on this substrate. These marks can carry additional information independent of their spatial position, such as size, greyscale luminance (brightness) value, surface texture density, color hue, color saturation, curvature, angle, and shape [Munzner,2000].

* Space
* Marks
* Connections & Enclosures
* Retinal Properties
* Temporal Encoding
* Viewpoint Transformation

=== Space ===
When you think about an empty paper as the beginning of a visualisation, the space between some possible object is one of the most powerful aspects to give something an important note.

=== Marks ===
Marks are the visible things that occur in space [Jacko], and are simply any graphical symbol visible on a display medium[Ignatius,Eve&Senay,Hikmet].
There are four types of simple Marks :
* Points
* Lines
* Areas
* Volumes

=== Connections & enclosures ===
Connections and enclosures build the important dependencies between the objects (marks). Connections show a relationship between objects, while enclosures can also indicate related objects.

=== Retinal properties ===
A retinal encoding is any variation of the marks that the retina of the eye can perceive besides position [Ignatius,Eve&Senay,Hikmet]. They are the informations that are carried by marks, such as crispness, shape, resolution, transperancy, color(value,hue&saturation), grayscale[Munzner, 2000].
Retinal properties describe how objects (marks) look like.

Abbildung S. 30 von Readings in Information Visualization

=== Temporal encoding ===
A temporal encoding shows how the marks' properties vary over time [Ignatius,Eve&Senay,Hikmet].

It's the encoding which depends on the temporal changes of marks (mark position and their retinal properties). [ todo : Source ]

=== Viewpoint transformations ===

Viewpoint transformations modify interactively and augment Visual Structures to turn static presentations into visualizations by establishing graphical parameters to create Views of Visual Structures [Card], in other words it is the modification of the view position of the viewer (or in general the modification of viewing parameters), thus enhancing the visual perception.

There are three common view transformations :
* Location Probes : Usage of Location in the visual structures to reveal additional info
* Viewpoint control : Moving the viewpoint to create visualisation : Pan,zoom,clip the viewpoint.
* Distortion : Creating a focus area and context area.

==References==
* [Dürsteler, 2005] Web Content Mining Visualisation , EN:http://www.infovis.net/printMag.php?num=175&lang=2
* [Munzner,2000] Interactive Visualization of Large Graphs and Networks, EN: http://graphics.stanford.edu/papers/munzner_thesis/
* [Card,1999] Readings in Information visualization : Using vision to think, EN: http://books.google.com/books?id=wdh2gqWfQmgC/
* [Ignatius,Eve&Senay,Hikmet] Data,vocabulary,marks,composition rules and visual perception rules, EN: http://cose.math.bas.bg/Sci_Visualization/visConcepts/concepts/marks.htm
*Julie A. Jacko, Andrew Sears, 2003, The Human-computer Interaction Handbook: Fundamentals, Evolving Technologies
*Readings in Information Visualization Von Stuart K. Card, Jock D. Mackinlay, Ben

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding

2008-11-05T19:09:57Z

UE-InfoVis0809 0126631:

= Visual Encoding =

== Definition ==
Visual encoding is the set of techniques enabling the representation of data on a screen or on paper. It comprises of the use of shapes, colours, areas and other visual variables that make it possible to associate data variables to graphic variables [Dürsteler]. Visual encodings are mappings of information to display elements [Munzner, 2000].

== Techniques of Visual Encoding ==

The fundamental substrate of visualizations is spatial position. Marks such as points, lines, or area-covering elements can be placed on this substrate. These marks can carry additional information independent of their spatial position, such as size, greyscale luminance (brightness) value, surface texture density, color hue, color saturation, curvature, angle, and shape.[Munzner]

* Space
* Marks
* Connections & Enclosures
* Retinal Properties
* Temporal Encoding
* Viewpoint Transformation

=== Space ===
When you think about an empty paper as the beginning of a visualisation, the space between some possible object is one of the most powerful aspects to give something an important note.

=== Marks ===
Marks are the visible things that occur in space [Jacko], and are simply any graphical symbol visible on a display medium[Ignatius,Eve&Senay,Hikmet].
There are four types of simple Marks :
* Points
* Lines
* Areas
* Volumes

=== Connections & enclosures ===
Connections and enclosures build the important dependencies between the objects (marks). Connections show a relationship between objects, while enclosures can also indicate related objects.

=== Retinal properties ===
A retinal encoding is any variation of the marks that the retina of the eye can perceive besides position [Ignatius,Eve&Senay,Hikmet]. They are the informations that are carried by marks, such as crispness, shape, resolution, transperancy, color(value,hue&saturation), grayscale.[Munzner].
Retinal properties describe how objects (marks) look like.

=== Temporal encoding ===
A temporal encoding shows how the marks' properties vary over time [Ignatius,Eve&Senay,Hikmet].

It's the encoding which depends on the temporal changes of marks (mark position and their retinal properties). [ todo : Source ]

=== Viewpoint transformations ===

Viewpoint transformations modify interactively and augment Visual Structures to turn static presentations into visualizations by establishing graphical parameters to create Views of Visual Structures [Card], in other words it is the modification of the view position of the viewer (or in general the modification of viewing parameters), thus enhancing the visual perception.

There are three common view transformations :
* Location Probes : Usage of Location in the visual structures to reveal additional info
* Viewpoint control : Moving the viewpoint to create visualisation : Pan,zoom,clip the viewpoint.
* Distortion : Creating a focus area and context area.

==References==

* [Munzner,2000] Interactive Visualization of Large Graphs and Networks, EN: http://graphics.stanford.edu/papers/munzner_thesis/
* [Card,1999] Readings in Information visualization : Using vision to think, EN: http://books.google.com/books?id=wdh2gqWfQmgC/
* [Ignatius,Eve&Senay,Hikmet] Data,vocabulary,marks,composition rules and visual perception rules, EN: http://cose.math.bas.bg/Sci_Visualization/visConcepts/concepts/marks.htm

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1

2008-11-02T16:56:56Z

UE-InfoVis0809 0126631: New page: == Aufgabenstellung == [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe1.html Beschreibung der Aufgabe 1] === Auszuarbeitende InfoVis Begriffe === *'''[[T...

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/infovis_ue_aufgabe1.html Beschreibung der Aufgabe 1]
=== Auszuarbeitende InfoVis Begriffe ===
*'''[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Cartogram|Cartogram]]'''
*'''[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 - Visual Encoding|Visual Encoding]]'''

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2008/09|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01

2008-11-02T16:56:25Z

UE-InfoVis0809 0126631:

== [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01 (KARALL, REGNER, UGUR)]] ==

[[User:UE-InfoVis0809_0126631|Karall, Eva]]

[[User:UE-InfoVis0809_0325767|Regner, Andreas ]]

[[User:UE-InfoVis0809_0427537|Ugur, Fatih]]

== Aufgaben : ==

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 0 | Aufgabe 0]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 1 | Aufgabe 1]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2 | Aufgabe 2]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 3 | Aufgabe 3]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 4 | Aufgabe 4]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01

2008-10-31T05:24:32Z

UE-InfoVis0809 0126631:

== [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01 (KARALL, REGNER, UGUR)]] ==

[[User:UE-InfoVis0809_0126631|Karall, Eva]]

[[User:UE-InfoVis0809_0325767|Regner, Andreas ]]

[[User:UE-InfoVis0809_0427537|Ugur, Fatih]]

== Aufgaben : ==

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 0 | Aufgabe 0]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 01 | Aufgabe 01]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 2 | Aufgabe 2]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 3 | Aufgabe 3]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 4 | Aufgabe 4]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01

2008-10-31T05:18:55Z

UE-InfoVis0809 0126631:

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01

2008-10-31T05:15:07Z

UE-InfoVis0809 0126631:

== [[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01|Gruppe 01 (KARALL, REGNER, UGUR)]] ==

[[User:UE-InfoVis0809_0126631|Karall, Eva]]

[[User:UE-InfoVis0809_0325767|Regner, Andreas ]]

[[User:UE-InfoVis0809_0427537|Ugur, Fatih]]

== Aufgaben : ==

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 00 | Aufgabe 00]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 01 | Aufgabe 01]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 02 | Aufgabe 02]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 03 | Aufgabe 03]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 01 - Aufgabe 04 | Aufgabe 04]]