InfoVis:Wiki - User contributions [en]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03 - Aufgabe 4

2009-01-07T21:25:39Z

UE-InfoVis0809 0201183: First step to success

== 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.

== Analysis ==

=== Dataset - Analysis ===
The data contains Homer Simpsons drinking behavior according to his personal circumstances or events in his life. The set which is based on abstract information representing the amount of sugar, coffein and alcohol absorbed through six different beverages.

The set consists of the following dimensions:
* Personal circumstances
Personal circumstances as nominal data are split up to the following categories:
Birth, Childhood, Puberty, Unemployment, Relationship, Marriage, Birth of Children,
Lovesickness, daily routine, favourite team win, favourite team loss, getting arrested, retirement

* Drink consumption
Drink consumption is split up to six categories of drinks (water, milk,
juice, coke, coffee, beer) containing continuous values of consumed liter per day.

* Ingredients consumption
Ingredients consumption is split up to three categories of ingredients
(sugar, coffein, alcohol) containing continuous values derived from the
drink consumption.

=== Fields of Application ===
With the aid of suitable visualizations of the given dataset it could be possible to study if there is a relation between personal circumstances and his drinking behavior. Therefore it can be studied in which way personal circumstances or events in Homers life affected his drinking behavior, or otherwise. This could be useful in fields of pschology and medicine. Based on the visualization nutrition advice could be given and schedules could be implemented.

=== Target Group - Analysis ===
Our target group contains medical scientists as well as their patients. So the program should contain all information necessary for a doctor to analyze the patients condition during a certain period and make a matching diagnoses, as well as that easy to understand to let the patient see his progress or regress during special situations in his life.

=== Goals of the Visualization ===
A primary goal of the visualization is to get information about the consumed amount of sugar, coffein and alcohol in respect to the recommended maximal allowance. The visualization should provide mechanisms to get an general overview and detailed information as well.
This information can be used for monitoring exceedance of the recommended maximal allowance. It can also be used for comparision of consumption depending on different personal circumstances.

== 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 03|Gruppe 03]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03 - Aufgabe 1 - Chernoff Face

2008-11-26T12:06:34Z

UE-InfoVis0809 0201183:

== Introduction ==
{{Quotation| a Chernoff face represents multivariate data in form of a face. |[Wikipedia, 2008]}}
This means that instead of using a vector representation for describing sets of data, a vector is represented by a face that can hold up to 18 dimensions. Changes of vectors result in different faces, which the human brain can treat better than vectors. Chernoff faces therefore are often used in statistic presentations as Figure 1 shows.

[[Image:lifeinla.GIF|thumb|none|right|150px|Fig. 1: Life in Los Angeles [Turner, 1977]]]

{{Quotation| Faces are type of [[Glyph|glyph]], a graphical object whose properties represent data values. |[Kosara, 2007]}}

The idea of displaying faces to represent multivariate data was first published in 1973 in The Journal of American National Statistic by Herman Chernoff who was born in 1923 in America.

== The idea in detail ==
As already said Chernoff faces are simplified faces that can help viewers to detect patterns, groupings, and correlation. Having data sets each dimension is assigned to a facial characteristic. Facial characteristics are for example eyebrow slant, eye spacing, head eccentricity, pupil size, and so on. Inside the data set each dimension represents a feature which can be classified. If we say for example that one feature of our face displays the rate of unemployment (rate) we could classify that rate into three classes e.g. rate < 3%, 3% < rate < 6% or rate > 6%. So we have three classes for the feature rate of unemployment. As each feature describes a characteristic of a face we could say that the shape of the mouth could stand for the rate of unemployment as figure 2 demonstrates.

[[Image:faces2.jpg|thumb|none|right|150px|Fig. 2: Six facial variations [Spinelli and Zhou, 2004]]]

Hence, every face unambiguously describes one feature vector, which in turn combines several features to describe one condition, like the quality of life as in [Spinelli and Zhou, 2004].

== Critics ==
Chernoff faces may be not that effective it seems. Certain features like the perception of eye size, eyebrow slant and the combination of those both are more influencing for longer viewing times than others. Therefore [Morris et. al, 2000] came to the conclusion that the use of Chernoff faces ''"may not have a significant advantage over other iconic visualization techniques for multidimensional information visualization.”''

== References ==
* [Wikipedia, 2008] Wikipedia contributors. Chernoff_face. ''Wikipedia, the free encyclopedia''. Last modified on October 5, 2008, at 15:41. Retrieved at: November 7, 2008. http://en.wikipedia.org/wiki/Chernoff_face
* [Turner, 1977] Eugene Turner, Life in LA, 1977 Retrieved at: November 7, 2008. http://www.csun.edu/%7Ehfgeg005/eturner/gallery/
* [Chernoff, 1973] Herman Chernoff. The Use of Faces to Represent Points in k-Dimensional Space Graphically, ''Journal of the American Statistical Association'', 68 (#342): 361-368, 1973. http://www.jstor.org/pss/2284077
* [Spinelli and Zhou, 2004] Joseph G. Spinelli and Yu Zhou. "Mapping Quality of Life with Chernoff Faces", ''4th Annual ESRI Education User Conference 2004'', San Diego, CA, August 2004.http://downloads2.esri.com/campus/uploads/library/pdfs/58415.pdf
* [Morris et al., 2000] Christopher J. Morris, David S. Ebert, Penny Rheingans. An Experimental Analysis of the Effectiveness of Features in Chernoff Faces. ''28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, Proceedings of SPIE'', pages 12- 17, 2000. http://www.csee.umbc.edu/~ebert/papers/Chernoff_990402.PDF
* [Kosara, 2007] Robert Kosara, A Critique of Chernoff Faces. Created at: 2007-02-25. Retrieved at: 2008-10-28. http://eagereyes.org/VisCrit/ChernoffFaces.html

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03 - Aufgabe 1 - Chernoff Face

2008-11-26T12:05:29Z

UE-InfoVis0809 0201183:

== Introduction ==
{{Quotation| a Chernoff face represents multivariate data in form of a face. |[Wikipedia, 2008]}}
This means that instead of using a vector representation for describing sets of data, a vector is represented by a face that can hold up to 18 dimensions.

Changes of vectors result in different faces, which the human brain can treat better than vectors. Chernoff faces therefore are often used in statistic presentations as Figure 1 shows.

[[Image:lifeinla.GIF|thumb|none|right|150px|Fig. 1: Life in Los Angeles [Turner, 1977]]]

{{Quotation| Faces are type of [[Glyph|glyph]], a graphical object whose properties represent data values. |[Kosara, 2007]}}

The idea of displaying faces to represent multivariate data was first published in 1973 in The Journal of American National Statistic by Herman Chernoff who was born in 1923 in America.

== The idea in detail ==
As already said Chernoff faces are simplified faces that can help viewers to detect patterns, groupings, and correlation. Having data sets each dimension is assigned to a facial characteristic. Facial characteristics are for example eyebrow slant, eye spacing, head eccentricity, pupil size, and so on. Inside the data set each dimension represents a feature which can be classified. If we say for example that one feature of our face displays the rate of unemployment (rate) we could classify that rate into three classes e.g. rate < 3%, 3% < rate < 6% or rate > 6%. So we have three classes for the feature rate of unemployment. As each feature describes a characteristic of a face we could say that the shape of the mouth could stand for the rate of unemployment as figure 2 demonstrates.

[[Image:faces2.jpg|thumb|none|right|150px|Fig. 2: Six facial variations [Spinelli and Zhou, 2004]]]

Hence, every face unambiguously describes one feature vector, which in turn combines several features to describe one condition, like the quality of life as in [Spinelli and Zhou, 2004].

== Critics ==
Chernoff faces may be not that effective it seems. Certain features like the perception of eye size, eyebrow slant and the combination of those both are more influencing for longer viewing times than others. Therefore [Morris et. al, 2000] came to the conclusion that the use of Chernoff faces ''"may not have a significant advantage over other iconic visualization techniques for multidimensional information visualization.”''

== References ==
* [Wikipedia, 2008] Wikipedia contributors. Chernoff_face. ''Wikipedia, the free encyclopedia''. Last modified on October 5, 2008, at 15:41. Retrieved at: November 7, 2008. http://en.wikipedia.org/wiki/Chernoff_face
* [Turner, 1977] Eugene Turner, Life in LA, 1977 Retrieved at: November 7, 2008. http://www.csun.edu/%7Ehfgeg005/eturner/gallery/
* [Chernoff, 1973] Herman Chernoff. The Use of Faces to Represent Points in k-Dimensional Space Graphically, ''Journal of the American Statistical Association'', 68 (#342): 361-368, 1973. http://www.jstor.org/pss/2284077
* [Spinelli and Zhou, 2004] Joseph G. Spinelli and Yu Zhou. "Mapping Quality of Life with Chernoff Faces", ''4th Annual ESRI Education User Conference 2004'', San Diego, CA, August 2004.http://downloads2.esri.com/campus/uploads/library/pdfs/58415.pdf
* [Morris et al., 2000] Christopher J. Morris, David S. Ebert, Penny Rheingans. An Experimental Analysis of the Effectiveness of Features in Chernoff Faces. ''28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, Proceedings of SPIE'', pages 12- 17, 2000. http://www.csee.umbc.edu/~ebert/papers/Chernoff_990402.PDF
* [Kosara, 2007] Robert Kosara, A Critique of Chernoff Faces. Created at: 2007-02-25. Retrieved at: 2008-10-28. http://eagereyes.org/VisCrit/ChernoffFaces.html

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03 - Aufgabe 1 - Chernoff Face

2008-11-26T12:04:34Z

UE-InfoVis0809 0201183:

== Introduction ==
{{Quotation| a Chernoff face represents multivariate data in form of a face. |[Wikipedia, 2008]}}
This means that instead of using a vector representation for describing sets of data, a vector is represented by a face that can hold up to 18 dimensions.

Changes of vectors result in different faces, which the human brain can treat better than vectors. Chernoff faces therefore are often used in statistic presentations like in Dr. Eugen Turners Map “Life in Los Angeles”.[Turner, 1977]

[[Image:lifeinla.GIF|thumb|none|right|150px|Fig. 1: Life in Los Angeles [Turner, 1977]]]

{{Quotation| Faces are type of [[Glyph|glyph]], a graphical object whose properties represent data values. |[Kosara, 2007]}}

The idea of displaying faces to represent multivariate data was first published in 1973 in The Journal of American National Statistic by Herman Chernoff who was born in 1923 in America.

== The idea in detail ==
As already said Chernoff faces are simplified faces that can help viewers to detect patterns, groupings, and correlation. Having data sets each dimension is assigned to a facial characteristic. Facial characteristics are for example eyebrow slant, eye spacing, head eccentricity, pupil size, and so on. Inside the data set each dimension represents a feature which can be classified. If we say for example that one feature of our face displays the rate of unemployment (rate) we could classify that rate into three classes e.g. rate < 3%, 3% < rate < 6% or rate > 6%. So we have three classes for the feature rate of unemployment. As each feature describes a characteristic of a face we could say that the shape of the mouth could stand for the rate of unemployment as figure 2 demonstrates.

[[Image:faces2.jpg|thumb|none|right|150px|Fig. 2: Six facial variations [Spinelli and Zhou, 2004]]]

Hence, every face unambiguously describes one feature vector, which in turn combines several features to describe one condition, like the quality of life as in [Spinelli and Zhou, 2004].

== Critics ==
Chernoff faces may be not that effective it seems. Certain features like the perception of eye size, eyebrow slant and the combination of those both are more influencing for longer viewing times than others. Therefore [Morris et. al, 2000] came to the conclusion that the use of Chernoff faces ''"may not have a significant advantage over other iconic visualization techniques for multidimensional information visualization.”''

== References ==
* [Wikipedia, 2008] Wikipedia contributors. Chernoff_face. ''Wikipedia, the free encyclopedia''. Last modified on October 5, 2008, at 15:41. Retrieved at: November 7, 2008. http://en.wikipedia.org/wiki/Chernoff_face
* [Turner, 1977] Eugene Turner, Life in LA, 1977 Retrieved at: November 7, 2008. http://www.csun.edu/%7Ehfgeg005/eturner/gallery/
* [Chernoff, 1973] Herman Chernoff. The Use of Faces to Represent Points in k-Dimensional Space Graphically, ''Journal of the American Statistical Association'', 68 (#342): 361-368, 1973. http://www.jstor.org/pss/2284077
* [Spinelli and Zhou, 2004] Joseph G. Spinelli and Yu Zhou. "Mapping Quality of Life with Chernoff Faces", ''4th Annual ESRI Education User Conference 2004'', San Diego, CA, August 2004.http://downloads2.esri.com/campus/uploads/library/pdfs/58415.pdf
* [Morris et al., 2000] Christopher J. Morris, David S. Ebert, Penny Rheingans. An Experimental Analysis of the Effectiveness of Features in Chernoff Faces. ''28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, Proceedings of SPIE'', pages 12- 17, 2000. http://www.csee.umbc.edu/~ebert/papers/Chernoff_990402.PDF
* [Kosara, 2007] Robert Kosara, A Critique of Chernoff Faces. Created at: 2007-02-25. Retrieved at: 2008-10-28. http://eagereyes.org/VisCrit/ChernoffFaces.html

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03 - Aufgabe 1 - Chernoff Face

2008-11-26T12:01:42Z

UE-InfoVis0809 0201183:

== Introduction ==
{{Quotation| a Chernoff face represents multivariate data in form of a face. |[Wikipedia, 2008]}}
This means that instead of using a vector representation for describing sets of data, a vector is represented by a face that can hold up to 18 dimensions.

Changes of vectors result in different faces, which the human brain can treat better than vectors. Chernoff faces therefore are often used in statistic presentations like in Dr. Eugen Turners Map “Life in Los Angeles”.[Turner, 1977]

[[Image:lifeinla.GIF|thumb|none|150px|Fig. 1: Life in Los Angeles [Turner, 1977]]]

{{Quotation| Faces are type of [[Glyph|glyph]], a graphical object whose properties represent data values. |[Kosara, 2007]}}

The idea of displaying faces to represent multivariate data was first published in 1973 in The Journal of American National Statistic by Herman Chernoff who was born in 1923 in America.

== The idea in detail ==
As already said Chernoff faces are simplified faces that can help viewers to detect patterns, groupings, and correlation. Having data sets each dimension is assigned to a facial characteristic. Facial characteristics are for example eyebrow slant, eye spacing, head eccentricity, pupil size, and so on. Inside the data set each dimension represents a feature which can be classified. If we say for example that one feature of our face displays the rate of unemployment (rate) we could classify that rate into three classes e.g. rate < 3%, 3% < rate < 6% or rate > 6%. So we have three classes for the feature rate of unemployment. As each feature describes a characteristic of a face we could say that the shape of the mouth could stand for the rate of unemployment as figure 2 demonstrates.

[[Image:faces2.jpg|thumb|none|350px|Fig. 2: Six facial variations [Spinelli and Zhou, 2004]]]

Hence, every face unambiguously describes one feature vector, which in turn combines several features to describe one condition, like the quality of life as in [Spinelli and Zhou, 2004].

== Critics ==
Chernoff faces may be not that effective it seems. Certain features like the perception of eye size, eyebrow slant and the combination of those both are more influencing for longer viewing times than others. Therefore [Morris et. al, 2000] came to the conclusion that the use of Chernoff faces ''"may not have a significant advantage over other iconic visualization techniques for multidimensional information visualization.”''

== References ==
* [Wikipedia, 2008] Wikipedia contributors. Chernoff_face. ''Wikipedia, the free encyclopedia''. Last modified on October 5, 2008, at 15:41. Retrieved at: November 7, 2008. http://en.wikipedia.org/wiki/Chernoff_face
* [Turner, 1977] Eugene Turner, Life in LA, 1977 Retrieved at: November 7, 2008. http://www.csun.edu/%7Ehfgeg005/eturner/gallery/
* [Chernoff, 1973] Herman Chernoff. The Use of Faces to Represent Points in k-Dimensional Space Graphically, ''Journal of the American Statistical Association'', 68 (#342): 361-368, 1973. http://www.jstor.org/pss/2284077
* [Spinelli and Zhou, 2004] Joseph G. Spinelli and Yu Zhou. "Mapping Quality of Life with Chernoff Faces", ''4th Annual ESRI Education User Conference 2004'', San Diego, CA, August 2004.http://downloads2.esri.com/campus/uploads/library/pdfs/58415.pdf
* [Morris et al., 2000] Christopher J. Morris, David S. Ebert, Penny Rheingans. An Experimental Analysis of the Effectiveness of Features in Chernoff Faces. ''28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, Proceedings of SPIE'', pages 12- 17, 2000. http://www.csee.umbc.edu/~ebert/papers/Chernoff_990402.PDF
* [Kosara, 2007] Robert Kosara, A Critique of Chernoff Faces. Created at: 2007-02-25. Retrieved at: 2008-10-28. http://eagereyes.org/VisCrit/ChernoffFaces.html

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03 - Aufgabe 2

2008-11-21T11:19:13Z

UE-InfoVis0809 0201183:

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

=== Zu beurteilende Tabelle ===

[[Image:Simuresults.jpg]]

== Critics & Changes ==

=== White space ===
=== Arrangement ===

The arranging of the mechanisms provided a grouping that makes it hard to read and recognize the differences.

* By adding mechanisms as a row header the legibility of the table increased. Additional white space between each group proofed also helpful to improve the clarity of the table.

=== Numbers & Alignment ===

Columns contain data with a varying number of decimal digits disrupt the visual structure of the columns in form of creating ragged edges on the right of a column.

* To facilitate comparison of numbers in columns and to preserve the visual structure of columns (''Gestalt principle of enclosure'') numbers have now equal number of decimal digits with same alignment down the columns. The column headers also have been aligned with the associated data.

Numbers occur with varying numeric precision.

* A numeric precision level of 5 decimal digits has been set to not exceed information with too excessive level of precision.

=== Descriptions ===

The abbreviated row headers ''Comp'' and ''Impu'' are not consistent with the title and are not convenient describing the use of ''CRs only'' and the ''proposed method''.

* The use of the abbreviations ''CR'' to describe the use of ''CRs only'' and ''prop'' to describe the ''proposed method'' link to the used methods in a more intuitive manner.

The arrangement of the rows ''Comp'' and ''Impu'' isn't handy to recognize that there is less difference between ''Full'' and ''Impu'' than between ''Full'' and ''Comp''.

* Therefore the rows have been arranged in such order to be unterstood more easily. The row ''prop'' has been placed above the row ''CR''.

== Corrected Table ==
[[image:table5.png|600px]]

== 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 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 03|Gruppe 03]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03 - Aufgabe 1 - Chernoff Face

2008-11-18T14:44:03Z

UE-InfoVis0809 0201183: redesign

== Introduction ==
{{Quotation| a Chernoff face represents multivariate data in form of a face. |[Wikipedia, 2008]}}
So instead of looking at a bunch of different numbers in a vector a human can look on faces, where each face describes a data set which can contain up to 18 dimensions.

Also the slightest change of the vector results in a different face. Studying faces the whole life-time the human brain is more used to distinguish between faces than vectors. Chernoff faces therefore are often used in statistic presentations like in Dr. Eugen Turners Map “Life in Los Angeles”.[Turner, 1977]

[[Image:lifeinla.GIF|thumb|none|150px|Fig. 1: Life in Los Angeles [Turner, 1977]]]

{{Quotation| Faces are type of [[Glyph|glyph]], a graphical object whose properties represent data values. |[Kosara, 2007]}}

The idea of displaying faces to represent multivariate data was first published in 1973 in The Journal of American National Statistic by Herman Chernoff who was born in 1923 in America.

== The idea in detail ==
As already said Chernoff faces are simplified faces that can help viewers to detect patterns, groupings, and correlation. Having data sets each dimension is assigned to a facial characteristic. Facial characteristics are for example eyebrow slant, eye spacing, head eccentricity, pupil size, and so on. Inside the data set each dimension represents a feature which can be classified. If we say for example that one feature of our face displays the rate of unemployment (rate) we could classify that rate into three classes e.g. rate < 3%, 3% < rate < 6% or rate > 6%. So we have three classes for the feature rate of unemployment. As each feature describes a characteristic of a face we could say that the shape of the mouth could stand for the rate of unemployment as figure 2 demonstrates.

[[Image:faces2.jpg|thumb|none|350px|Fig. 2: Six facial variations [Spinelli and Zhou, 2004]]]

Hence, every face unambiguously describes one feature vector, which in turn combines several features to describe one condition, like the quality of life as in [Spinelli and Zhou, 2004].

== Critics ==
Chernoff faces may be not that effective it seems. Certain features like the perception of eye size, eyebrow slant and the combination of those both are more influencing for longer viewing times than others. Therefore [Morris et. al, 2000] came to the conclusion that the use of Chernoff faces ''"may not have a significant advantage over other iconic visualization techniques for multidimensional information visualization.”''

== References ==
* [Wikipedia, 2008] Wikipedia contributors. Chernoff_face. ''Wikipedia, the free encyclopedia''. Last modified on October 5, 2008, at 15:41. Retrieved at: November 7, 2008. http://en.wikipedia.org/wiki/Chernoff_face
* [Turner, 1977] Eugene Turner, Life in LA, 1977 Retrieved at: November 7, 2008. http://www.csun.edu/%7Ehfgeg005/eturner/gallery/
* [Chernoff, 1973] Herman Chernoff. The Use of Faces to Represent Points in k-Dimensional Space Graphically, ''Journal of the American Statistical Association'', 68 (#342): 361-368, 1973. http://www.jstor.org/pss/2284077
* [Spinelli and Zhou, 2004] Joseph G. Spinelli and Yu Zhou. "Mapping Quality of Life with Chernoff Faces", ''4th Annual ESRI Education User Conference 2004'', San Diego, CA, August 2004.http://downloads2.esri.com/campus/uploads/library/pdfs/58415.pdf
* [Morris et al., 2000] Christopher J. Morris, David S. Ebert, Penny Rheingans. An Experimental Analysis of the Effectiveness of Features in Chernoff Faces. ''28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, Proceedings of SPIE'', pages 12- 17, 2000. http://www.csee.umbc.edu/~ebert/papers/Chernoff_990402.PDF
* [Kosara, 2007] Robert Kosara, A Critique of Chernoff Faces. Created at: 2007-02-25. Retrieved at: 2008-10-28. http://eagereyes.org/VisCrit/ChernoffFaces.html

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03 - Aufgabe 1 - Chernoff Face

2008-11-18T14:30:44Z

UE-InfoVis0809 0201183:

== Introduction ==
{{Quotation| a Chernoff face represents multivariate data in form of a face. |[Wikipedia, 2008]}} So instead of looking at a bunch of different numbers in a vector a human can look on faces, where each face describes a data set which can contain up to 18 dimensions.

Also the slightest change of the vector results in a different face. Studying faces the whole life-time the human brain is more used to distinguish between faces than vectors. Chernoff faces therefore are often used in statistic presentations like in Dr. Eugen Turners Map “Life in Los Angeles”.[Turner, 1977]

[[Image:lifeinla.GIF|thumb|none|150px|Life in Los Angeles [Turner, 1977]]]

Faces are type of [[Glyph|glyph]], a graphical object whose properties represent data values

The idea of displaying faces to represent multivariate data was first published in 1973 in The Journal of American National Statistic by Herman Chernoff who was born in 1923 in America. Article: “The Use of Faces to Represent Points in K-Dimensional Space Graphically”. [Chernoff, 1973]

== The idea in detail ==
As already said Chernoff faces are simplified faces that can help viewers to detect patterns, groupings, and correlation. Having data sets each dimension is assigned to a facial characteristic. Facial characteristics are for example eybrow slant, eye spacing, head eccentricity, pupil size, and so on. Inside the data set each dimension represents a feature which can be classified. If we say for example that one feature of our face displays the rate of unemployment (rou) we could classify that rate into three classes e.g. rou < 3%, 3%< rou <6% or rou > 6%. So we have three classes for the feature rate of unemployment. As each feature describes a characteristic of a face we could say that the shape of the mouth could stand for the rate of unemployment as figure 2 demonstrates.

[[Image:faces2.jpg|thumb|none|350px|Six facial variations [Spinelli and Zhou, 2004]]]

Hence, every face unambiguously describes one feature vector, which in turn combines several features to describe one condition, like the quality of life as in [Spinelli and Zhou, 2004].

== Critics ==
Chernoff faces may be not that effective it seems. Certain features like the perception of eye size, eyebrow slant and the combination of those both are more influencing for longer viewing times than others. Therefore [Morris et. al, 2000] came to the conclusion that the use of Chernoff faces ''"may not have a significant advantage over other iconic visualization techniques for multidimensional information visualization.”''

== References ==
* [Wikipedia, 2008] Wikipedia contributors. Chernoff_face. ''Wikipedia, the free encyclopedia''. Last modified on October 5, 2008, at 15:41. Retrieved at: November 7, 2008. http://en.wikipedia.org/wiki/Chernoff_face
* [Turner, 1977] Eugene Turner, Life in LA, 1977 Retrieved at: November 7, 2008. http://www.csun.edu/%7Ehfgeg005/eturner/gallery/
* [Chernoff, 1973] Herman Chernoff. The Use of Faces to Represent Points in k-Dimensional Space Graphically, ''Journal of the American Statistical Association'', 68 (#342): 361-368, 1973. http://www.jstor.org/pss/2284077
* [Spinelli and Zhou, 2004] Joseph G. Spinelli and Yu Zhou. "Mapping Quality of Life with Chernoff Faces", ''4th Annual ESRI Education User Conference 2004'', San Diego, CA, August 2004.http://downloads2.esri.com/campus/uploads/library/pdfs/58415.pdf
* [Morris et al., 2000] Christopher J. Morris, David S. Ebert, Penny Rheingans. An Experimental Analysis of the Effectiveness of Features in Chernoff Faces. ''28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, Proceedings of SPIE'', pages 12- 17, 2000. http://www.csee.umbc.edu/~ebert/papers/Chernoff_990402.PDF

User:UE-InfoVis0809 0201183

2008-10-25T12:36:57Z

UE-InfoVis0809 0201183: Added Picture

== Moser, Bernd ==

[[ Image:Pic0201183.jpg|200px ]]

* Matrikelnummer: 0201183
* Studienkennzahl: 066 935
* Mail: e0201183[at]student.tuwien.ac.at

File:Pic0201183.jpg

2008-10-25T12:30:28Z

UE-InfoVis0809 0201183: Picture of me!

== Summary ==
Picture of me!
== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03

2008-10-21T13:49:04Z

UE-InfoVis0809 0201183: added header

== Liste der Gruppenmitglieder ==

[[User:UE-InfoVis0809_0425646|Dincer, Engin]]

[[User:UE-InfoVis0809_0225026|Mayer, Philipp]]

[[User:UE-InfoVis0809_0201183|Moser, Bernd]]

== Aufgaben ==

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03

2008-10-21T13:45:06Z

UE-InfoVis0809 0201183: added line breaks

[[User:UE-InfoVis0809_0425646|Dincer, Engin]]

[[User:UE-InfoVis0809_0225026|Mayer, Philipp]]

[[User:UE-InfoVis0809_0201183|Moser, Bernd]]

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03

2008-10-21T13:44:31Z

UE-InfoVis0809 0201183: started group03-page

[[User:UE-InfoVis0809_0425646|Dincer, Engin]]
[[User:UE-InfoVis0809_0225026|Mayer, Philipp]]
[[User:UE-InfoVis0809_0201183|Moser, Bernd]]

Teaching:TUW - UE InfoVis WS 2008/09

2008-10-21T13:38:55Z

UE-InfoVis0809 0201183: added group03

[[Image:Aigner03infovis ue.gif]] <big>WS 2008/09</big>

'''LVA Nr:''' 188.308 ([http://tuwis.tuwien.ac.at/lva/tuwien/188308 TUWIS++ Seite])

'''LVA Homepage:''' http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws08/index.html

'''Leitung:''' [[Gschwandtner, Theresia|Theresia Gschwandtner]] [gschwandtner (at) ifs.tuwien.ac.at] 
'''Tutorin:''' [[User:Martha_Kaltenecker|Martha Kaltenecker]] [e0125193 (at) student.tuwien.ac.at]

== Gruppen ==

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

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03|Gruppe 03 (DINCER, MAYER, MOSER)]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 06|Gruppe 06 (Frank, Mayer, Rind)]]

[[Teaching:TUW - UE InfoVis WS 2007/08 - Gruppe 08|Gruppe 08]]

[[Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 10|Gruppe 10 (DEBONG, FISCHL, PETROV)]]

== News / Bemerkungen ==

User:UE-InfoVis0809 0201183

2008-10-21T13:16:11Z

UE-InfoVis0809 0201183: First draft

== Moser, Bernd ==

* Foto: tba
* Matrikelnummer: 0201183
* Studienkennzahl: 066 935
* Mail: e0201183[at]student.tuwien.ac.at