InfoVis:Wiki - User contributions [en]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 4

2010-01-06T18:18:22Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe4.html Beschreibung der Aufgabe 4]
=== Zu erstellende Visualisierung ===
-------------------------------
* Stammbaum der Nachkommen von Lisa und Bart Simpson*

...Visualisierung der Nachkommen von Lisa Simpson sowie der Nachkommen von Bart Simpson. Dabei sollen zwei Stammbäume entstehen - einer von Bart und einer von Lisa - die dann miteinander verglichen werden können. Zuerst kommen Lisa und Bart, dann deren Kinder, ihre Enkel, etc. (mind 4 Generationen). Da es noch keine Nachkommen gibt, können diese frei erfunden werden.

Die Visualisierung soll folgende Informationen darstellen:

- Verwandtschaftsverhältnisse (zumindest Eltern-Kinder),

- Unterscheidung zwischen Blutsverwandtschaft und angeheirateten Familienmitgliedern,

- Geburts- und Todestag sowie Lebensdauer von allen Familienmitgliedern,

- wichtige Ereignisse im Leben jedes Familienmitglieds (z.B., Anzeigen, Gefängnisaufenthalte, Schulzeit, Studienzeit, Nobelpreise, Arbeitslosigkeit etc.)

- Zufriedenheit jedes Familienmitglieds (Skala: sehr niedrig - niedrig - mittel - hoch - sehr hoch); kann sich im Laufe des Lebens ändern.

Die Visualisierung soll die interaktive Auseinandersetzung mit den Daten ermöglichen.
Verpflichtend:
Möglichkeiten zum besseren Vergleich von einzelnen Abschnitten der Stammbäume bzw. Vergleich von Ausschnitten aus Lisas und Barts Stammbäumen.
+ mind. 2 weitere Interaktionsmöglichkeiten (z.B., Details on Demand, Filteroptionen)

Allgemein:

- Die Daten sollen zur Analyse von Zusammenhängen zwischen Familienverhältnissen, wichtigen Ereignissen und Zufriedenheit visualisiert werden (die Anwendungsgebiets- und Zielgruppenanalyse kann kurz gehalten werden).

- Die bisher erlernten Design-Prinzipien sollen umgesetzt werden z.B.: Optimierung der Data-ink ratio (keine Comics!), visuelle Attribute (Größe, Farbe, Position, etc.) sollen sinnvoll eingesetzt werden (Information darstellen).

- Die Mockups sollten zumindest 1) die beiden Stammbäume im Überblick und 2) eine detaillierte Vergleichsansicht von 2 Teil-Stammbäumen wiedergeben.

- Alle nicht angeführten Daten können frei erfunden werden.

------------------------------

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2009/10|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04|Gruppe 04]]

--------------------------------

== part a ==

=== 1. used application area and datas===

==== application analysis ====
* The used family tree analysis helps to visualise Bart and Lisa Simpsons´ pedigree until the fourth generation including detailed information like the date of birth, relations inbetween each others, etc. according to each certain person. Supportingly color represents the satisfaction of each family member. The final tree should allow to compare single sections with each others.
* In the visualization of the family tree you find the following implementation of the information:
** Gender --> (color?)
** Name -->
** Relations --> (lines?)
** Date of birth/death --> ?
** Satisfaction -->
** Special events -->

==== data analysis ====
* bla
* bla

=== 2. analysis of the target group ===
* In general this type of visualization of the family tree mainly adresses future family members of psychoterapists.
* The information you gain concerns information in general that is very superficial and unpersonal, whereas the color underlined envelopment of satisfaction gives a very personal view of the family member. For this reason it will just be related persons or professions with an interest of the psychical side of a person and their past.
* Different ways of visualization:
** The most current and best known way of the visualization of relations between families is the form of a directed graph (gerichteter Graph), whereby generations are ranked by the age from down to up with the eldest family member on the bottom of the graph.
** The pedigree (Stammtafel) puts a person on the top of it to form the basis for the following members. The information is limited to the surnames and their marriage partners. The pedigree becomes confusing and unclear in the moment the family grows.
** Another display format of a listed pedigree (Stammliste/ Nachfahrenliste) which includes just family members with the same surname.

=== 3. aim of visualization ===
* The aim of visualization is the creation of a clear, fast reproducible graphic to recognize relations between family members easy and clear. The additional information you get out of the visualization depends on the type of graph you chose.
* Unclear relations between family members may be recognized fast. i.e. adpoted children or stepparents.
* Different relationships that are possible between the members of a family should be shown in a graphic.

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 3

2010-01-06T13:23:13Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe3.html Beschreibung der Aufgabe 3]
=== Zu verbessernde Grafik ===
------------------------------- 
[[Image:geo1.jpg]]

== Ausarbeitung ==

=== Criticism ===

==== Steven Few, Show me the numbers: ====
* Some of the circles cover the map behind which are supposed to convey important information. Thus decreasing or putting next to the map with a line connected to the country it is concerned to.
* The shape of a circle covers way too much information. The usage of a bar would give the same information without blocking that much.
* The real message/data is not supported in the Graph, which is against the task of visualizing quantitative information.
* It is not clear, which data has priority. TOE/capita? The sources of energy?
* There is no direction for order in which data should be read.
* The information-scale on the left can´t be taken as a referenc, because it is too far away from the circles.To decode the size of the circles it takes several steps: first compare the size with the scale, which is hard to tell, when the circles have no extreme. Secondly you have to look for an explanation for the shortcut "TOE". It is put somewhere under a title insted of underneath or put in parenthesis next to the TOE.
* The many colors are not necessary. It is better to work with forms and sizes.
* We are more sensitive to the vertical and horizontal alignment than we might imagine. Therefor we should use it to give more weight to the real content of the graphic.
* The unstrucstured ordering of the circled makes it difficult to separately scan the major content.

==== Steven Few, Elegance Through Simplicity: ====
* There is too much unnecessary ink used for the graphic, because the important values need less place in contrary to the borders around them. The greater the ratio of the ink that you use to communicate the data to the total amount of ink in the table or graph, the better you´ve highlighted the data.

=== Corrections ===
* The graph is reorganized by dividing the graph in three parts:
** TOE/capita plot in bars
** Types of energy by colors. Besides is the color scale - not round.
** Some explaning lines are added.
* The essential message of the graph and additional information is clarified.
** Main message: Most of the sources of energy is based on Fossil Fuel.
** Additional Message: Does the size of the country has a bigger effect on the used energy or does it more depend on the richness there or the mental relation to energy.
* The TOE/capita scale on the left side of the bars helps to read the scale. It does not go until infinity, but until the highest information we have. There is no need for an y-axis.
** Additionally the bars are ordered by their size. That way it is easier to compare and to read the content.
* Objects positioned on the right are less seen that objects positioned on the top. Therefor we put the titles underneath each other to introduce the graph.

=== New Table ===

[[Image:EnergyProductionV2 Kopie_.png]]

=== References ===
* Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 7 - General Design for Communication.
* Stephen Few, Elegance Through Simplicity, intelligent enterprise, Oct 16, 2004.

File:EnergyProductionV2 Kopie .png

2010-01-06T13:20:24Z

UE-InfoVis0910 0401099: New page: == Summary == == Copyright status == == Source ==

== Summary ==

== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 3

2010-01-06T13:17:16Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe3.html Beschreibung der Aufgabe 3]
=== Zu verbessernde Grafik ===
------------------------------- 
[[Image:geo1.jpg]]

== Ausarbeitung ==

=== Criticism ===

==== Steven Few, Show me the numbers: ====
* Some of the circles cover the map behind which are supposed to convey important information. Thus decreasing or putting next to the map with a line connected to the country it is concerned to.
* The shape of a circle covers way too much information. The usage of a bar would give the same information without blocking that much.
* The real message/data is not supported in the Graph, which is against the task of visualizing quantitative information.
* It is not clear, which data has priority. TOE/capita? The sources of energy?
* There is no direction for order in which data should be read.
* The information-scale on the left can´t be taken as a referenc, because it is too far away from the circles.To decode the size of the circles it takes several steps: first compare the size with the scale, which is hard to tell, when the circles have no extreme. Secondly you have to look for an explanation for the shortcut "TOE". It is put somewhere under a title insted of underneath or put in parenthesis next to the TOE.
* The many colors are not necessary. It is better to work with forms and sizes.
* We are more sensitive to the vertical and horizontal alignment than we might imagine. Therefor we should use it to give more weight to the real content of the graphic.
* The unstrucstured ordering of the circled makes it difficult to separately scan the major content.

==== Steven Few, Elegance Through Simplicity: ====
* There is too much unnecessary ink used for the graphic, because the important values need less place in contrary to the borders around them. The greater the ratio of the ink that you use to communicate the data to the total amount of ink in the table or graph, the better you´ve highlighted the data.

=== Corrections ===
* The graph is reorganized by dividing the graph in three parts:
** TOE/capita plot in bars
** Types of energy by colors. Besides is the color scale - not round.
** Some explaning lines are added.
* The essential message of the graph and additional information is clarified.
** Main message: Most of the sources of energy is based on Fossil Fuel.
** Additional Message: Does the size of the country has a bigger effect on the used energy or does it more depend on the richness there or the mental relation to energy.
* The TOE/capita scale on the left side of the bars helps to read the scale. It does not go until infinity, but until the highest information we have. There is no need for an y-axis.
** Additionally the bars are ordered by their size. That way it is easier to compare and to read the content.
* Objects positioned on the right are less seen that objects positioned on the top. Therefor we put the titles underneath each other to introduce the graph.

=== New Table ===

[[Image:EnergyProductionV2.png]]

=== References ===
* Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 7 - General Design for Communication.
* Stephen Few, Elegance Through Simplicity, intelligent enterprise, Oct 16, 2004.

File:EnergyProductionV2.png

2010-01-06T13:16:22Z

UE-InfoVis0910 0401099: New page: == Summary == == Copyright status == == Source ==

== Summary ==

== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 3

2009-12-09T15:35:44Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe3.html Beschreibung der Aufgabe 3]
=== Zu verbessernde Grafik ===
------------------------------- 
[[Image:geo1.jpg]]

== Ausarbeitung ==

=== Criticism ===

==== Steven Few, Show me the numbers: ====
* Some of the circles cover the map behind which are supposed to convey important information. Thus decreasing or putting next to the map with a line connected to the country it is concerned to.
* The shape of a circle covers way too much information. The usage of a bar would give the same information without blocking that much.
* The real message/data is not supported in the Graph, which is against the task of visualizing quantitative information.
* It is not clear, which data has priority. TOE/capita? The sources of energy?
* There is no direction for order in which data should be read.
* The information-scale on the left can´t be taken as a referenc, because it is too far away from the circles.To decode the size of the circles it takes several steps: first compare the size with the scale, which is hard to tell, when the circles have no extreme. Secondly you have to look for an explanation for the shortcut "TOE". It is put somewhere under a title insted of underneath or put in parenthesis next to the TOE.
* The many colors are not necessary. It is better to work with forms and sizes.
* We are more sensitive to the vertical and horizontal alignment than we might imagine. Therefor we should use it to give more weight to the real content of the graphic.
* The unstrucstured ordering of the circled makes it difficult to separately scan the major content.

==== Steven Few, Elegance Through Simplicity: ====
* There is too much unnecessary ink used for the graphic, because the important values need less place in contrary to the borders around them. The greater the ratio of the ink that you use to communicate the data to the total amount of ink in the table or graph, the better you´ve highlighted the data.

=== Corrections ===
* The graph is reorganized by dividing the graph in three parts:
** TOE/capita plot in bars
** Types of energy by colors. Besides is the color scale - not round.
** Some explaning lines are added.
* The essential message of the graph and additional information is clarified.
** Main message: Most of the sources of energy is based on Fossil Fuel.
** Additional Message: Does the size of the country has a bigger effect on the used energy or does it more depend on the richness there or the mental relation to energy.
* The TOE/capita scale on the left side of the bars helps to read the scale. It does not go until infinity, but until the highest information we have. There is no need for an y-axis.
** Additionally the bars are ordered by their size. That way it is easier to compare and to read the content.
* Objects positioned on the right are less seen that objects positioned on the top. Therefor we put the titles underneath each other to introduce the graph.

=== New Table ===

[[Image:EnergyProduction.png]]

=== References ===
* Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 7 - General Design for Communication.
* Stephen Few, Elegance Through Simplicity, intelligent enterprise, Oct 16, 2004.

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 3

2009-12-09T15:34:57Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe3.html Beschreibung der Aufgabe 3]
=== Zu verbessernde Grafik ===
------------------------------- 
[[Image:geo1.jpg]]

== Ausarbeitung ==

=== Criticism ===

==== Steven Few, Show me the numbers: ====
* Some of the circles cover the map behind which are supposed to convey important information. Thus decreasing or putting next to the map with a line connected to the country it is concerned to.
* The shape of a circle covers way too much information. The usage of a bar would give the same information without blocking that much.
* The real message/data is not supported in the Graph, which is against the task of visualizing quantitative information.
* It is not clear, which data has priority. TOE/capita? The sources of energy?
* There is no direction for order in which data should be read.
* The information-scale on the left can´t be taken as a referenc, because it is too far away from the circles.To decode the size of the circles it takes several steps: first compare the size with the scale, which is hard to tell, when the circles have no extreme. Secondly you have to look for an explanation for the shortcut "TOE". It is put somewhere under a title insted of underneath or put in parenthesis next to the TOE.
* The many colors are not necessary. It is better to work with forms and sizes.
* We are more sensitive to the vertical and horizontal alignment than we might imagine. Therefor we should use it to give more weight to the real content of the graphic.
* The unstrucstured ordering of the circled makes it difficult to separately scan the major content.

==== Steven Few, Elegance Through Simplicity: ====
* There is too much unnecessary ink used for the graphic, because the important values need less place in contrary to the borders around them. The greater the ratio of the ink that you use to communicate the data to the total amount of ink in the table or graph, the better you´ve highlighted the data.

=== Corrections ===
* The graph is reorganized by dividing the graph in three parts:
** TOE/capita plot in bars
** Types of energy by colors. Besides is the color scale - not round.
** Some explaning lines are added.
* The essential message of the graph and additional information is clarified.
** Main message: Most of the sources of energy is based on Fossil Fuel.
** Additional Message: Does the size of the country has a bigger effect on the used energy or does it more depend on the richness there or the mental relation to energy.
* The TOE/capita scale on the left side of the bars helps to read the scale. It does not go until infinity, but until the highest information we have. There is no need for an y-axis.
** Additionally the bars are ordered by their size. That way it is easier to compare and to read the content.
* Objects positioned on the right are less seen that objects positioned on the top. Therefor we put the titles underneath each other to introduce the graph.

=== New Table ===

==== Energy Production per Capita (2004) ====

[[Image:EnergyProduction.png]]

=== References ===
* Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 7 - General Design for Communication.
* Stephen Few, Elegance Through Simplicity, intelligent enterprise, Oct 16, 2004.

File:EnergyProduction.png

2009-12-09T15:34:12Z

UE-InfoVis0910 0401099: New page: == Summary == == Copyright status == == Source ==

== Summary ==

== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 3

2009-12-07T15:17:14Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe3.html Beschreibung der Aufgabe 3]
=== Zu verbessernde Grafik ===
------------------------------- 
[[Image:geo1.jpg]]

== Ausarbeitung ==

=== Criticism ===

==== Steven Few, Show me the numbers: ====
* Some of the circles cover the map behind which are supposed to convey important information. Thus decreasing or putting next to the map with a line connected to the country it is concerned to.
* The shape of a circle covers way too much information. The usage of a bar would give the same information without blocking that much.
* The real message/data is not supported in the Graph, which is against the task of visualizing quantitative information.
* It is not clear, which data has priority. TOE/capita? The sources of energy?
* There is no direction for order in which data should be read.
* The information-scale on the left can´t be taken as a referenc, because it is too far away from the circles.To decode the size of the circles it takes several steps: first compare the size with the scale, which is hard to tell, when the circles have no extreme. Secondly you have to look for an explanation for the shortcut "TOE". It is put somewhere under a title insted of underneath or put in parenthesis next to the TOE.
* The many colors are not necessary. It is better to work with forms and sizes.
* We are more sensitive to the vertical and horizontal alignment than we might imagine. Therefor we should use it to give more weight to the real content of the graphic.
* The unstrucstured ordering of the circled makes it difficult to separately scan the major content.

==== Steven Few, Elegance Through Simplicity: ====
* There is too much unnecessary ink used for the graphic, because the important values need less place in contrary to the borders around them. The greater the ratio of the ink that you use to communicate the data to the total amount of ink in the table or graph, the better you´ve highlighted the data.

=== Corrections ===
* The graph is reorganized by dividing the graph in three parts:
** TOE/capita plot in bars
** Types of energy by colors. Besides is the color scale - not round.
** Some explaning lines are added.
* The essential message of the graph and additional information is clarified.
** Main message: Most of the sources of energy is based on Fossil Fuel.
** Additional Message: Does the size of the country has a bigger effect on the used energy or does it more depend on the richness there or the mental relation to energy.
* The TOE/capita scale on the left side of the bars helps to read the scale. It does not go until infinity, but until the highest information we have. There is no need for an y-axis.
** Additionally the bars are ordered by their size. That way it is easier to compare and to read the content.
* Objects positioned on the right are less seen that objects positioned on the top. Therefor we put the titles underneath each other to introduce the graph.

=== References ===
* Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 7 - General Design for Communication.
* Stephen Few, Elegance Through Simplicity, intelligent enterprise, Oct 16, 2004.

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 3

2009-12-07T15:15:11Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe3.html Beschreibung der Aufgabe 3]
=== Zu verbessernde Grafik ===
------------------------------- 
[[Image:geo1.jpg]]

== Ausarbeitung ==

=== Criticism ===

==== Steven Few, Show me the numbers: ====
* Some of the circles cover the map behind which are supposed to convey important information. Thus decreasing or putting next to the map with a line connected to the country it is concerned to.
* The shape of a circle covers way too much information. The usage of a bar would give the same information without blocking that much.
* The real message/data is not supported in the Graph, which is against the task of visualizing quantitative information.
* It is not clear, which data has priority. TOE/capita? The sources of energy?
* There is no direction for order in which data should be read.
* The information-scale on the left can´t be taken as a referenc, because it is too far away from the circles.To decode the size of the circles it takes several steps: first compare the size with the scale, which is hard to tell, when the circles have no extreme. Secondly you have to look for an explanation for the shortcut "TOE". It is put somewhere under a title insted of underneath or put in parenthesis next to the TOE.
* The many colors are not necessary. It is better to work with forms and sizes.
We are more sensitive to the vertical and horizontal alignment than we might imagine. Therefor we should use it to give more weight to the real content of the graphic.
* The unstrucstured ordering of the circled makes it difficult to separately scan the major content.

==== Steven Few, Elegance Through Simplicity: ====
* There is too much unnecessary ink used for the graphic, because the important values need less place in contrary to the borders around them. The greater the ratio of the ink that you use to communicate the data to the total amount of ink in the table or graph, the better you´ve highlighted the data.

=== Corrections ===
* The graph is reorganized by dividing the graph in three parts:
** TOE/capita plot in bars
** Types of energy by colors. Besides is the color scale - not round.
** Some explaning lines are added.
* The essential message of the graph and additional information is clarified.
** Main message: Most of the sources of energy is based on Fossil Fuel.
** Additional Message: Does the size of the country has a bigger effect on the used energy or does it more depend on the richness there or the mental relation to energy.
* The TOE/capita scale on the left side of the bars helps to read the scale. It does not go until infinity, but until the highest information we have. There is no need for an y-axis.
** Additionally the bars are ordered by their size. That way it is easier to compare and to read the content.
* Objects positioned on the right are less seen that objects positioned on the top. Therefor we put the titles underneath each other to introduce the graph.

**

=== References ===
* Stephen Few, Show Me the Numbers: Designing Tables and Graphs to Enlighten, Analytics Press, 2004, Chapter 7 - General Design for Communication.
* Stephen Few, Elegance Through Simplicity, intelligent enterprise, Oct 16, 2004.

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 2

2009-12-07T15:07:07Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
=== Zu beurteilende Tabelle ===
[[Image:imageRRH.JPG]]

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2009/10|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04|Gruppe 04]]

== Ausarbeitung ==

=== Improved Table ===

[[Image:Mean News Source Credibility Rankings.jpg]]

=== Criticism ===
* The column "Rank" is used too often. Multiple "Rank" columns would be necessary if the table spreads over more pages, but this is not the case.
* It is not obvious what "t" and "alpha" means.
**Same with the title "All Ss", as long as there is no column called "S". The reader can just guess what "S" means.
* Rankings should always be sorted, so that the reader needs less time to read the table.
* The allignment of the columns could be better arranged.
* Headers should usualy not be much longer than the longest entry in their column.
** Missing headers are very bad, so hardly none can imagine what the content means. If the first column doesn´t use any header, the font-style should be at least different to the rest, i.e. just big letters.
** By the way you can argue about the title of the first column, but no title of the second one. You can summarize the two columns, if you chose a title that includes the information that the lines are ordered by a rank.
* Abbreviations should not be used. They cant be understood by someone who is not familiar with the table's content.
* The grid is not necessary. A wisely chosen white-space would be enough.
* Numbers should have the same format, so its easier for the reader.
* Calculations within the table should always be displayed next to the column which is used for calculation.
** The use of a separated space for explanations could also be used for definitions, what HN, t,... means.

=== Explanation of Improvements ===
* Our opinion is, that the table displays the Top 9 of something. So we sorted the table accordingly to their ranking.
* We put the Ranking in the first column, because its better for the reader, so he can quickly see how the ranking is and its not that irritating when reading the table.
* We alligned the columns correctly.
** Numbers should be alligned to the right, because thats easier to read
** Ranking should also be alligned to the right, because the only thing that should be center alligned are values which always have the same size (e.g. "Y", "N").
* All numbers have now the same format. (-xx,yy)
* The usage of alpha is not obvious to an average reader.
**It would be readable for a whider spread if you used % instead --> by the way a nicer format
**Instead of footnotes you could define alpha in the seperated space
* The column "t=" is the only number column which is alligned to the left, because the "*" at the end varies and so its easier for the reader.
* The calculation of the difference between Hard and Soft News is now next to the columns Hard News and Soft News. That way it´s easier to see a connection between them.
** Instead of M1 and M2 we useIt is easier to find a connection if you use HN and SN for Hard and Soft Use instead of new letters (M1, M2). The column "M1-M2" should be better named "difference (HN-SN)". This way you also see how it is calculated.
* We removed the grid, because its not needed. Instead of it we made a light grey line underneath the headers.
* For the readability we sepparated the columns and rows through white-spaces.

File:Mean News Source Credibility Rankings.jpg

2009-12-07T15:03:18Z

UE-InfoVis0910 0401099: New page: == Summary == == Copyright status == == Source ==

== Summary ==

== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 2

2009-11-20T14:07:33Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
=== Zu beurteilende Tabelle ===
[[Image:imageRRH.JPG]]

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2009/10|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04|Gruppe 04]]

== Ausarbeitung ==

=== Improved Table ===

[[Image:Tabelle4.jpg]]

=== Criticism ===
* The column "Rank" is used too often. Multiple "Rank" columns would be necessary if the table spreads over more pages, but this is not the case.
* It is not obvious what "t" and "alpha" means.
**Same with the title "All Ss", as long as there is no column called "S". The reader can just guess what "S" means.
* Rankings should always be sorted, so that the reader needs less time to read the table.
* The allignment of the columns could be better arranged.
* Headers should usualy not be much longer than the longest entry in their column.
** Missing headers are very bad, so hardly none can imagine what the content means. If the first column doesn´t use any header, the font-style should be at least different to the rest, i.e. just big letters.
** By the way you can argue about the title of the first column, but no title of the second one. You can summarize the two columns, if you chose a title that includes the information that the lines are ordered by a rank.
* Abbreviations should not be used. They cant be understood by someone who is not familiar with the table's content.
* The grid is not necessary. A wisely chosen white-space would be enough.
* Numbers should have the same format, so its easier for the reader.
* Calculations within the table should always be displayed next to the column which is used for calculation.
** The use of a separated space for explanations could also be used for definitions, what HN, t,... means.

=== Explanation of Improvements ===
* Our opinion is, that the table displays the Top 9 of something. So we sorted the table accordingly to their ranking.
* We put the Ranking in the first column, because its better for the reader, so he can quickly see how the ranking is and its not that irritating when reading the table.
* We alligned the columns correctly.
** Numbers should be alligned to the right, because thats easier to read
** Ranking should also be alligned to the right, because the only thing that should be center alligned are values which always have the same size (e.g. "Y", "N").
* All numbers have now the same format. (-xx,yy)
* The usage of alpha is not obvious to an average reader.
**It would be readable for a whider spread if you used % instead --> by the way a nicer format
**Instead of footnotes you could define alpha in the seperated space
* The column "t=" is the only number column which is alligned to the left, because the "*" at the end varies and so its easier for the reader.
* The calculation of the difference between Hard and Soft News is now next to the columns Hard News and Soft News. That way it´s easier to see a connection between them.
** Instead of M1 and M2 we useIt is easier to find a connection if you use HN and SN for Hard and Soft Use instead of new letters (M1, M2). The column "M1-M2" should be better named "difference (HN-SN)". This way you also see how it is calculated.
* We removed the grid, because its not needed. Instead of it we made a light grey line underneath the headers.
* For the readability we sepparated the columns and rows through white-spaces.

File:Tabelle4.jpg

2009-11-20T14:06:39Z

UE-InfoVis0910 0401099: New page: == Summary == == Copyright status == == Source ==

== Summary ==

== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 2

2009-11-20T14:03:32Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
=== Zu beurteilende Tabelle ===
[[Image:imageRRH.JPG]]

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2009/10|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04|Gruppe 04]]

== Ausarbeitung ==

=== Criticism ===
* The column "Rank" is used too often. Multiple "Rank" columns would be necessary if the table spreads over more pages, but this is not the case.
* It is not obvious what "t" and "alpha" means.
**Same with the title "All Ss", as long as there is no column called "S". The reader can just guess what "S" means.
* Rankings should always be sorted, so that the reader needs less time to read the table.
* The allignment of the columns could be better arranged.
* Headers should usualy not be much longer than the longest entry in their column.
** Missing headers are very bad, so hardly none can imagine what the content means. If the first column doesn´t use any header, the font-style should be at least different to the rest, i.e. just big letters.
** By the way you can argue about the title of the first column, but no title of the second one. You can summarize the two columns, if you chose a title that includes the information that the lines are ordered by a rank.
* Abbreviations should not be used. They cant be understood by someone who is not familiar with the table's content.
* The grid is not necessary. A wisely chosen white-space would be enough.
* Numbers should have the same format, so its easier for the reader.
* Calculations within the table should always be displayed next to the column which is used for calculation.
** The use of a separated space for explanations could also be used for definitions, what HN, t,... means.

=== Improved Table ===

[[Image:Tabelle3.jpg]]

=== Explanation of Improvements ===
* Our opinion is, that the table displays the Top 9 of something. So we sorted the table accordingly to their ranking.
* We put the Ranking in the first column, because its better for the reader, so he can quickly see how the ranking is and its not that irritating when reading the table.
* We alligned the columns correctly.
** Numbers should be alligned to the right, because thats easier to read
** Ranking should also be alligned to the right, because the only thing that should be center alligned are values which always have the same size (e.g. "Y", "N").
* All numbers have now the same format. (-xx,yy)
* The usage of alpha is not obvious to an average reader.
**It would be readable for a whider spread if you used % instead --> by the way a nicer format
**Instead of footnotes you could define alpha in the seperated space
* The column "t=" is the only number column which is alligned to the left, because the "*" at the end varies and so its easier for the reader.
* The calculation of the difference between Hard and Soft News is now next to the columns Hard News and Soft News. That way it´s easier to see a connection between them.
** Instead of M1 and M2 we useIt is easier to find a connection if you use HN and SN for Hard and Soft Use instead of new letters (M1, M2). The column "M1-M2" should be better named "difference (HN-SN)". This way you also see how it is calculated.
* We removed the grid, because its not needed. Instead of it we made a light grey line underneath the headers.
* For the readability we sepparated the columns and rows through white-spaces.

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 2

2009-11-20T13:53:54Z

UE-InfoVis0910 0401099:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
=== Zu beurteilende Tabelle ===
[[Image:imageRRH.JPG]]

== Links ==

* [[Teaching:TUW_-_UE_InfoVis_WS_2009/10|InfoVis:Wiki UE Homepage]]

* [http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/ UE InfoVis]

*[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04|Gruppe 04]]

== Ausarbeitung ==

=== Criticism ===
* The column "Rank" is used too often. Multiple "Rank" columns would be necessary if the table spreads over more pages, but this is not the case.
* It is not obvious what "t" and "alpha" means.
**Same with the title "All Ss", as long as there is no column called "S". The reader can just guess what "S" means.
* Rankings should always be sorted, so that the reader needs less time to read the table.
* The allignment of the columns could be better arranged.
* Headers should usualy not be much longer than the longest entry in their column.
** Missing headers are very bad, so hardly noone can imagine what the content means. If the first column doesn´t use any header, the font-style should be at least different to the rest, i.e. just big letters.
** By the way you can argue about the title of the first column, but no title of the second one. You can summarize the two columns, if you chose a title that includes the information that the lines are ordered by a rank.
* Abbreviations should not be used. They cant be understood by someone who is not familiar with the table's content.
* The grid is not necessary. A wisely chosen white-space would be enough.
* Numbers should have the same format, so its easier for the reader.
* Calculations within the table should always be displayed next to the column which is used for calculation.
** The use of a separated space for explanations could also be used for definitions, what HN, t,... means.

=== Improved Table ===

[[Image:Tabelle3.jpg]]

=== Explanation of Improvements ===
* Our opinion is, that the table displays the Top 9 of something. So we sorted the table accordingly to their ranking.
* We put the Ranking in the first column, because its better for the reader, so he can quickly see how the ranking is and its not that irritating when reading the table.
* We alligned the columns correctly.
** Numbers should be alligned to the right, because thats easier to read
** Ranking should also be alligned to the right, because the only thing that should be center alligned are values which always have the same size (e.g. "Y", "N").
* All numbers have now the same format. (-xx,yy)
* The usage of alpha is not obvious to an average reader.
**It would be readable for a whider spread if you used % instead --> by the way a nicer format
**Instead of footnotes you could define alpha in the seperated space
* The column "t=" is the only number column which is alligned to the left, because the "*" at the end varies and so its easier for the reader.
* The calculation of the difference between Hard and Soft News is now next to the columns Hard News and Soft News. That way it´s easier to see a connection between them.
** Instead of M1 and M2 we useIt is easier to find a connection if you use HN and SN for Hard and Soft Use instead of new letters (M1, M2). The column "M1-M2" should be better named "difference (HN-SN)". This way you also see how it is calculated.
* We removed the grid, because its not needed. Instead of it we made a light grey line underneath the headers.
* For the readability we sepparated the columns and rows through white-spaces.

File:Tabelle3.jpg

2009-11-20T13:53:16Z

UE-InfoVis0910 0401099: New page: == Summary == == Copyright status == == Source ==

== Summary ==

== Copyright status ==

== Source ==

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

2009-11-04T10:39:49Z

UE-InfoVis0910 0401099:

03.11.2009
*Artikel wurde auf Rechtschreibung / Groß- und Kleinschreibung überprüft
*Überarbeitung der References
**Die References haben nicht ganz den Richtlinien entsprochen. Eine dementsprechende Anpassung wurde vorgenommen
**Ein Link wurde korrigiert, welcher nicht funktioniert hat.
 
04.11.2009
*Auch hier konnte ich nach einer längeren Literaturrecherche und suche im Internet, keine wirklichen Verbesserungen finden. Natürlich könnte man noch das eine oder ander Bild hinzufügen bzw. tauschen. Allerdings sehe ich dies nicht als notwendig um den Beitrag zu verbessern und wäre letztendlich nur eine Handlung um etwas "aktiv" verändert zu haben.

Teaching talk:TUW - UE InfoVis WS 2008/09 - Gruppe 09 - Aufgabe 1 - Types of Data (quantitative vs. qualitative)

2009-11-04T10:19:37Z

UE-InfoVis0910 0401099:

02.11.2009
*Es wurden noch zwei Unterkategorien zu den quantitativen Daten hinzugefügt.
*Ansonsten schein mir das Thema als umfassend erklärt und behandelt. Auch nach ausführlicher Internetrecherche konnte ich keinen weiteren nennenswerten Informationen mehr finden.
 
03.11.2009
*Artikel wurde auf Rechtschreibung / Groß- und Kleinschreibung überprüft.
*Überarbeitung der References
**Die References haben nicht ganz den Richtlinien entsprochen.
**Ein Link war sogar komplett unformatiert.
**Neue Reference hinzugefügt.

Teaching talk:TUW - UE InfoVis WS 2008/09 - Gruppe 09 - Aufgabe 1 - Types of Data (quantitative vs. qualitative)

2009-11-02T18:40:09Z

UE-InfoVis0910 0401099: New page: Es wurden noch zwei Unterkategorien zu den quantitativen Daten hinzugefügt.

Es wurden noch zwei Unterkategorien zu den quantitativen Daten hinzugefügt.

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 09 - Aufgabe 1 - Types of Data (quantitative vs. qualitative)

2009-11-02T18:33:47Z

UE-InfoVis0910 0401099:

==Definition==
===Qualitative data===
{{Quotation | The term qualitative is used to describe certain types of information. Qualitative data are described in terms of quality (that is, 'informal' or relative characteristics such as warmth and flavour). This is the converse of quantitative, which more precisely describes data in terms of quantity and often using a numerical figure to represent something in a statement.| Wikipedia, Nov 2008 }}

===Quantitative data===
{{Quotation | [...] Quantitative data is data measured or identified on a numerical scale. Numerical data can be analysed using statistical methods, and results can be displayed using tables, charts, histograms and graphs. For example, a researcher will ask a questions to a participant that include words how often, how many or percentage. The answers from the questions will be numerical. [...] After the data is collected the researcher will make an analysis of the quantitative data and produce statistics.| Wikipedia, Nov 2008 }}
 
Additionally, quantitative data can be divided into ''discrete'' and ''continuous'' data. 
'''Discrete data''' 

They can take specific numeric values. For Example: shoe size, age,... 

'''Continuous data''' 
They can take any numerical value. For Example: weigth, width,... 
----

==Qualitative research==
Qualitative research is used when the goal is a complete and detailed description of the subject. The data is not presented in form of numbers an statistics as in quantitative data, but in the form of words, pictures and objects. Contrary to quantitative methods it is much more subjective, because the observations which are made during a research are strongly dependent on the researcher's interpretation. 
In most cases qualitative methods aim to gather an in-depth understanding of human behavior and the causes that affect human behavior. There are many different ways of doing qualitative research: Qualitative data can e.g. be gained through
*in-depth interviews with persons or groups
*direct observation
*referring to existing written papers.

[[image:689px-Piecharts.svg.png|thumb|[Wikipedia, 2004] This figure shows quantitative data represented in different ways]]
==Quantitative research==
Quantitative research is done by systematically collecting and analyzing numerical data concerning the subject. The researcher has to know clearly in advance what he/she is looking for, i.e. all aspects of the study have to be carefully designed before the data is collected. Based on the collected quantitative data statistical models can be constructed or hypotheses can be developed. One advantage of quantitative research is, that it tends to stay more objective than qualitative research. But because quantitative methods are only supplied with numerical data, the results often lack details. 
Quantitative research is widely used in both, natural and social sciences.

----

==Example: Qualitative data vs. quantitative data==
In this example the difference between qualitative and quantitative data is shown. Each bullet point describes a certain attribute of a freshman class. On the left side you can see some qualitative data of the class. Obviously this data can only be gained through a close and continuous observation of the class. On the right side quantitative data of the class is shown. It contains purely numerical and statistical data.
<table>
<tr>
<td style="padding-right:15px;">
'''Qualitative data:'''

*friendly demeanors

*civic minded

*environmentalists

*positive school spirit
</td>
<td>
'''Quantitative data:'''

*672 students

*394 girls, 278 boys

*68% on honor roll

*150 students accelerated in mathematics
</td>
</tr>
</table>
 
----

==References==
[Neill, 2007] James Neill, Qualitative versus Quantitative Research: Key Points in a Classic Debate. Created at: February 28, 2007. Retrieved at: November 24, 2008. http://wilderdom.com/research/QualitativeVersusQuantitativeResearch.html 
[Oswego City School District Regents Exam Prep Center, 1999] Donna Roberts, Qualitative vs Quantitative Data. Created at: 1999. Retrieved at: November 24, 2008. http://www.regentsprep.org/Regents/math/ALGEBRA/AD1/qualquant.htm 
[Wikipedia, 2006] Crissyd, Quantitative data. Created at: February 22, 2006. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Quantitative_data 
[Wikipedia, 2003] FirstPrinciples, Qualitative data. Created at: August 8, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Qualitative_data 
[Wikipedia, 2003] Sheldon Rampton, Quantitative research, Created at: December 05, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Quantitative_research 
[Wikipedia, 2003] Trontonian, Qualitative research. Created at: November 18, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Qualitative_research 
[Wikipedia, 2004] Chmod007, Pie Chart. Created at: June 15, 2004. Retrieved at: November 26, 2008. http://en.wikipedia.org/wiki/Pie_chart 
http://www.cimt.plymouth.ac.uk/projects/mepres/book7/bk7i11/bk7_11i1.htm

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 09 - Aufgabe 1 - Types of Data (quantitative vs. qualitative)

2009-11-02T18:30:39Z

UE-InfoVis0910 0401099:

==Definition==
===Qualitative data===
{{Quotation | The term qualitative is used to describe certain types of information. Qualitative data are described in terms of quality (that is, 'informal' or relative characteristics such as warmth and flavour). This is the converse of quantitative, which more precisely describes data in terms of quantity and often using a numerical figure to represent something in a statement.| Wikipedia, Nov 2008 }}

===Quantitative data===
{{Quotation | [...] Quantitative data is data measured or identified on a numerical scale. Numerical data can be analysed using statistical methods, and results can be displayed using tables, charts, histograms and graphs. For example, a researcher will ask a questions to a participant that include words how often, how many or percentage. The answers from the questions will be numerical. [...] After the data is collected the researcher will make an analysis of the quantitative data and produce statistics.| Wikipedia, Nov 2008 }}
 
Additionally, quantitative data can be divided into ''discrete'' and ''continuous'' data. 
'''Discrete data''' 

They take specific numeric values. For Example: shoe size, age,... 

'''Continuous data''' 
They can take any numerical value. For Example: weigth, width,... 
----

==Qualitative research==
Qualitative research is used when the goal is a complete and detailed description of the subject. The data is not presented in form of numbers an statistics as in quantitative data, but in the form of words, pictures and objects. Contrary to quantitative methods it is much more subjective, because the observations which are made during a research are strongly dependent on the researcher's interpretation. 
In most cases qualitative methods aim to gather an in-depth understanding of human behavior and the causes that affect human behavior. There are many different ways of doing qualitative research: Qualitative data can e.g. be gained through
*in-depth interviews with persons or groups
*direct observation
*referring to existing written papers.

[[image:689px-Piecharts.svg.png|thumb|[Wikipedia, 2004] This figure shows quantitative data represented in different ways]]
==Quantitative research==
Quantitative research is done by systematically collecting and analyzing numerical data concerning the subject. The researcher has to know clearly in advance what he/she is looking for, i.e. all aspects of the study have to be carefully designed before the data is collected. Based on the collected quantitative data statistical models can be constructed or hypotheses can be developed. One advantage of quantitative research is, that it tends to stay more objective than qualitative research. But because quantitative methods are only supplied with numerical data, the results often lack details. 
Quantitative research is widely used in both, natural and social sciences.

----

==Example: Qualitative data vs. quantitative data==
In this example the difference between qualitative and quantitative data is shown. Each bullet point describes a certain attribute of a freshman class. On the left side you can see some qualitative data of the class. Obviously this data can only be gained through a close and continuous observation of the class. On the right side quantitative data of the class is shown. It contains purely numerical and statistical data.
<table>
<tr>
<td style="padding-right:15px;">
'''Qualitative data:'''

*friendly demeanors

*civic minded

*environmentalists

*positive school spirit
</td>
<td>
'''Quantitative data:'''

*672 students

*394 girls, 278 boys

*68% on honor roll

*150 students accelerated in mathematics
</td>
</tr>
</table>
 
----

==References==
[Neill, 2007] James Neill, Qualitative versus Quantitative Research: Key Points in a Classic Debate. Created at: February 28, 2007. Retrieved at: November 24, 2008. http://wilderdom.com/research/QualitativeVersusQuantitativeResearch.html 
[Oswego City School District Regents Exam Prep Center, 1999] Donna Roberts, Qualitative vs Quantitative Data. Created at: 1999. Retrieved at: November 24, 2008. http://www.regentsprep.org/Regents/math/ALGEBRA/AD1/qualquant.htm 
[Wikipedia, 2006] Crissyd, Quantitative data. Created at: February 22, 2006. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Quantitative_data 
[Wikipedia, 2003] FirstPrinciples, Qualitative data. Created at: August 8, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Qualitative_data 
[Wikipedia, 2003] Sheldon Rampton, Quantitative research, Created at: December 05, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Quantitative_research 
[Wikipedia, 2003] Trontonian, Qualitative research. Created at: November 18, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Qualitative_research 
[Wikipedia, 2004] Chmod007, Pie Chart. Created at: June 15, 2004. Retrieved at: November 26, 2008. http://en.wikipedia.org/wiki/Pie_chart 
http://www.cimt.plymouth.ac.uk/projects/mepres/book7/bk7i11/bk7_11i1.htm

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 09 - Aufgabe 1 - Types of Data (quantitative vs. qualitative)

2009-11-02T15:08:07Z

UE-InfoVis0910 0401099:

==Definition==
===Qualitative data===
{{Quotation | The term qualitative is used to describe certain types of information. Qualitative data are described in terms of quality (that is, 'informal' or relative characteristics such as warmth and flavour). This is the converse of quantitative, which more precisely describes data in terms of quantity and often using a numerical figure to represent something in a statement.| Wikipedia, Nov 2008 }}

===Quantitative data===
{{Quotation | [...] Quantitative data is data measured or identified on a numerical scale. Numerical data can be analysed using statistical methods, and results can be displayed using tables, charts, histograms and graphs. For example, a researcher will ask a questions to a participant that include words how often, how many or percentage. The answers from the questions will be numerical. [...] After the data is collected the researcher will make an analysis of the quantitative data and produce statistics.| Wikipedia, Nov 2008 }}
 
Additionally, quantitative data can be divided into discrete and continuous data.
----

==Qualitative research==
Qualitative research is used when the goal is a complete and detailed description of the subject. The data is not presented in form of numbers an statistics as in quantitative data, but in the form of words, pictures and objects. Contrary to quantitative methods it is much more subjective, because the observations which are made during a research are strongly dependent on the researcher's interpretation. 
In most cases qualitative methods aim to gather an in-depth understanding of human behavior and the causes that affect human behavior. There are many different ways of doing qualitative research: Qualitative data can e.g. be gained through
*in-depth interviews with persons or groups
*direct observation
*referring to existing written papers.

[[image:689px-Piecharts.svg.png|thumb|[Wikipedia, 2004] This figure shows quantitative data represented in different ways]]
==Quantitative research==
Quantitative research is done by systematically collecting and analyzing numerical data concerning the subject. The researcher has to know clearly in advance what he/she is looking for, i.e. all aspects of the study have to be carefully designed before the data is collected. Based on the collected quantitative data statistical models can be constructed or hypotheses can be developed. One advantage of quantitative research is, that it tends to stay more objective than qualitative research. But because quantitative methods are only supplied with numerical data, the results often lack details. 
Quantitative research is widely used in both, natural and social sciences.

----

==Example: Qualitative data vs. quantitative data==
In this example the difference between qualitative and quantitative data is shown. Each bullet point describes a certain attribute of a freshman class. On the left side you can see some qualitative data of the class. Obviously this data can only be gained through a close and continuous observation of the class. On the right side quantitative data of the class is shown. It contains purely numerical and statistical data.
<table>
<tr>
<td style="padding-right:15px;">
'''Qualitative data:'''

*friendly demeanors

*civic minded

*environmentalists

*positive school spirit
</td>
<td>
'''Quantitative data:'''

*672 students

*394 girls, 278 boys

*68% on honor roll

*150 students accelerated in mathematics
</td>
</tr>
</table>
 
----

==References==
[Neill, 2007] James Neill, Qualitative versus Quantitative Research: Key Points in a Classic Debate. Created at: February 28, 2007. Retrieved at: November 24, 2008. http://wilderdom.com/research/QualitativeVersusQuantitativeResearch.html 
[Oswego City School District Regents Exam Prep Center, 1999] Donna Roberts, Qualitative vs Quantitative Data. Created at: 1999. Retrieved at: November 24, 2008. http://www.regentsprep.org/Regents/math/ALGEBRA/AD1/qualquant.htm 
[Wikipedia, 2006] Crissyd, Quantitative data. Created at: February 22, 2006. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Quantitative_data 
[Wikipedia, 2003] FirstPrinciples, Qualitative data. Created at: August 8, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Qualitative_data 
[Wikipedia, 2003] Sheldon Rampton, Quantitative research, Created at: December 05, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Quantitative_research 
[Wikipedia, 2003] Trontonian, Qualitative research. Created at: November 18, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Qualitative_research 
[Wikipedia, 2004] Chmod007, Pie Chart. Created at: June 15, 2004. Retrieved at: November 26, 2008. http://en.wikipedia.org/wiki/Pie_chart 
http://www.cimt.plymouth.ac.uk/projects/mepres/book7/bk7i11/bk7_11i1.htm

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 09 - Aufgabe 1 - Types of Data (quantitative vs. qualitative)

2009-11-02T15:07:26Z

UE-InfoVis0910 0401099:

==Definition==
===Qualitative data===
{{Quotation | The term qualitative is used to describe certain types of information. Qualitative data are described in terms of quality (that is, 'informal' or relative characteristics such as warmth and flavour). This is the converse of quantitative, which more precisely describes data in terms of quantity and often using a numerical figure to represent something in a statement.| Wikipedia, Nov 2008 }}

Additionally, quantitative data can be divided into discrete and continuous data.

===Quantitative data===
{{Quotation | [...] Quantitative data is data measured or identified on a numerical scale. Numerical data can be analysed using statistical methods, and results can be displayed using tables, charts, histograms and graphs. For example, a researcher will ask a questions to a participant that include words how often, how many or percentage. The answers from the questions will be numerical. [...] After the data is collected the researcher will make an analysis of the quantitative data and produce statistics.| Wikipedia, Nov 2008 }}
 
----

==Qualitative research==
Qualitative research is used when the goal is a complete and detailed description of the subject. The data is not presented in form of numbers an statistics as in quantitative data, but in the form of words, pictures and objects. Contrary to quantitative methods it is much more subjective, because the observations which are made during a research are strongly dependent on the researcher's interpretation. 
In most cases qualitative methods aim to gather an in-depth understanding of human behavior and the causes that affect human behavior. There are many different ways of doing qualitative research: Qualitative data can e.g. be gained through
*in-depth interviews with persons or groups
*direct observation
*referring to existing written papers.

[[image:689px-Piecharts.svg.png|thumb|[Wikipedia, 2004] This figure shows quantitative data represented in different ways]]
==Quantitative research==
Quantitative research is done by systematically collecting and analyzing numerical data concerning the subject. The researcher has to know clearly in advance what he/she is looking for, i.e. all aspects of the study have to be carefully designed before the data is collected. Based on the collected quantitative data statistical models can be constructed or hypotheses can be developed. One advantage of quantitative research is, that it tends to stay more objective than qualitative research. But because quantitative methods are only supplied with numerical data, the results often lack details. 
Quantitative research is widely used in both, natural and social sciences.

----

==Example: Qualitative data vs. quantitative data==
In this example the difference between qualitative and quantitative data is shown. Each bullet point describes a certain attribute of a freshman class. On the left side you can see some qualitative data of the class. Obviously this data can only be gained through a close and continuous observation of the class. On the right side quantitative data of the class is shown. It contains purely numerical and statistical data.
<table>
<tr>
<td style="padding-right:15px;">
'''Qualitative data:'''

*friendly demeanors

*civic minded

*environmentalists

*positive school spirit
</td>
<td>
'''Quantitative data:'''

*672 students

*394 girls, 278 boys

*68% on honor roll

*150 students accelerated in mathematics
</td>
</tr>
</table>
 
----

==References==
[Neill, 2007] James Neill, Qualitative versus Quantitative Research: Key Points in a Classic Debate. Created at: February 28, 2007. Retrieved at: November 24, 2008. http://wilderdom.com/research/QualitativeVersusQuantitativeResearch.html 
[Oswego City School District Regents Exam Prep Center, 1999] Donna Roberts, Qualitative vs Quantitative Data. Created at: 1999. Retrieved at: November 24, 2008. http://www.regentsprep.org/Regents/math/ALGEBRA/AD1/qualquant.htm 
[Wikipedia, 2006] Crissyd, Quantitative data. Created at: February 22, 2006. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Quantitative_data 
[Wikipedia, 2003] FirstPrinciples, Qualitative data. Created at: August 8, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Qualitative_data 
[Wikipedia, 2003] Sheldon Rampton, Quantitative research, Created at: December 05, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Quantitative_research 
[Wikipedia, 2003] Trontonian, Qualitative research. Created at: November 18, 2003. Retrieved at: November 24, 2008. http://en.wikipedia.org/wiki/Qualitative_research 
[Wikipedia, 2004] Chmod007, Pie Chart. Created at: June 15, 2004. Retrieved at: November 26, 2008. http://en.wikipedia.org/wiki/Pie_chart 
http://www.cimt.plymouth.ac.uk/projects/mepres/book7/bk7i11/bk7_11i1.htm

Teaching:TUW - UE InfoVis WS 2009/10

2009-10-29T08:55:32Z

UE-InfoVis0910 0401099:

[[Image:Aigner03infovis ue.gif]] <big>WS 2009/10</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_ws09/index.html

'''Leitung:''' [[Gschwandtner, Theresia|Theresia Gschwandtner]] [gschwandtner (at) ifs.tuwien.ac.at] 
'''Tutorin:''' [[User:Katharina-Anna Wendelin|Katharina-Anna Wendelin]] [e0425160 (at) student.tuwien.ac.at]

== Gruppen ==


[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 01|Gruppe 01 (Sakai, Sverak, <frei>)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 02|Gruppe 02 (Feichtinger, Rezaei, Schindelka)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 03|Gruppe 03 (Lang, Hackl, Hasslacher)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04|Gruppe 04 (Kaiser, <frei>, Ehsani)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 05|Gruppe 05 (Paizoni, Wuttej, Hudl)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 06|Gruppe 06 (Fried, Fritz, Hiller)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 07|Gruppe 07 (Schwengerer, <???>, <???>)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 08|Gruppe 08 (Bauer, Olea, <???>)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09|Gruppe 09 (Hubmann-Haidvogel, Kloibhofer, Riederer)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 10|Gruppe 10 (Kickinger, Ramsauer, Wittmann)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 11|Gruppe 11 (Gastecker, Hahn, Leeb)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 12|Gruppe 12 (Bauer, Eigner, <???>)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 13|Gruppe 13 (Sadauskas, Scheikl, Burger)]]

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 15|Gruppe 15 (Martin, Stix, Lenzhofer)]]

== News / Bemerkungen ==

Liebe TeilnehmerInnen, 
fügt bitte Gruppen mit nur einem oder zwei Mitgliedern selbstständig zusammen,
z.B., Martin Schwengerer geht zur Gruppe 08 und Gruppe 12 verteilt sich auf Gruppe 01 und Gruppe 04. 
Wie ihr euch umverteilt überlasse ich euch. Sollte das nicht funktionieren, bitte ich um
Rückmeldung bis morgen, dann muss ich "nachhelfen" ;). 
Vielen Dank! 
-- [[Gschwandtner, Theresia|Theresia Gschwandtner]] 07:27, 29 October 2009 (CEST)

Liebe TeilnehmerInnen, 
aus Datenschutz-Gründen bitte ich euch eure Martrikelnummer
nicht auf eurer InfoVis:Wiki Userseite anzugeben. 
Vielen Dank! 
-- [[Gschwandtner, Theresia|Theresia Gschwandtner]] 09:40, 27 October 2009 (CEST)

Liebe TeilnehmerInnen! 
Um diese Seite einheitlich zu gestalten (auch bezüglich der Vorjahre), schlage ich vor die Nachnamen
der Gruppenmitglieder in Klammer neben der Gruppe anzugeben, 
z.B.: Gruppe XX (Maier, Müller, Mustermann). 
-- [[Gschwandtner, Theresia|Theresia Gschwandtner]] 10:05, 01 October 2009 (CEST)

User:UE-InfoVis0910 0405144

2009-10-27T14:34:45Z

UE-InfoVis0910 0401099:

Anna Parisa EHSANI 
[[image:Istanbul.jpg|300px]]

User:UE-InfoVis0910 0401099

2009-10-27T14:31:56Z

UE-InfoVis0910 0401099:

*'''Name:''' Kaiser, Stefanie
*'''Master:''' Medieninformatik

[[Image:steffi.jpg]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 0

2009-10-20T16:23:13Z

UE-InfoVis0910 0401099:

'''Aufgabe 0: Wiki Basics'''

'''Punkte:''' 5 
'''Abgabe:''' spätestens bis zum '''28.10.2009''' über das InfoVis:Wiki

'''Ziele'''

* Erlernen von Grundkenntnissen von Wiki Systemen
* Vertrautmachen mit dem InfoVis:Wiki
* Bildung von 3er-Gruppen und Schaffung der Basis für die weiteren Übungsaufgaben

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 0

2009-10-20T16:21:49Z

UE-InfoVis0910 0401099:

'''Aufgabe 0: Wiki Basics'''
'''Punkte:''' 5 
'''Abgabe:''' spätestens bis zum 28.10.2009 über das InfoVis:Wiki

'''Ziele'''

* Erlernen von Grundkenntnissen von Wiki Systemen
* Vertrautmachen mit dem InfoVis:Wiki
* Bildung von 3er-Gruppen und Schaffung der Basis für die weiteren Übungsaufgaben

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04

2009-10-20T16:20:54Z

UE-InfoVis0910 0401099:

'''Gruppenmitglieder'''

[[User:UE-InfoVis0910_0401099|Kaiser, Stefanie]] 

'''Aufgaben'''

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 0|Aufgabe 0]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 1|Aufgabe 1]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 2|Aufgabe 2]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 3|Aufgabe 3]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 4|Aufgabe 4]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 0

2009-10-20T16:15:46Z

UE-InfoVis0910 0401099: New page: =Aufgabe 0: Wiki Basics= '''Punkte:''' 5 '''Abgabe:''' spätestens bis zum 28.10.2009 über das InfoVis:Wiki ==Ziele== * Erlernen von Grundkenntnissen von Wiki Systemen * Vertrautm...

=Aufgabe 0: Wiki Basics=
'''Punkte:''' 5 
'''Abgabe:''' spätestens bis zum 28.10.2009 über das InfoVis:Wiki

==Ziele==

* Erlernen von Grundkenntnissen von Wiki Systemen
* Vertrautmachen mit dem InfoVis:Wiki
* Bildung von 3er-Gruppen und Schaffung der Basis für die weiteren Übungsaufgaben

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04

2009-10-20T16:15:01Z

UE-InfoVis0910 0401099:

== Gruppenmitglieder ==

[[User:UE-InfoVis0910_0401099|Kaiser, Stefanie]] 

== Aufgaben ==

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 0|Aufgabe 0]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 1|Aufgabe 1]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 2|Aufgabe 2]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 3|Aufgabe 3]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04 - Aufgabe 4|Aufgabe 4]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04

2009-10-20T16:13:55Z

UE-InfoVis0910 0401099:

== Gruppenmitglieder ==

[[User:UE-InfoVis0910_0401099|Kaiser, Stefanie]] 

== Aufgaben ==

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 02 - Aufgabe 0|Aufgabe 0]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 02 - Aufgabe 1|Aufgabe 1]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 02 - Aufgabe 2|Aufgabe 2]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 02 - Aufgabe 3|Aufgabe 3]] 
[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 02 - Aufgabe 4|Aufgabe 4]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04

2009-10-20T16:12:47Z

UE-InfoVis0910 0401099:

== Gruppenmitglieder ==

[[User:UE-InfoVis0910_0401099|Kaiser, Stefanie]]

Teaching:TUW - UE InfoVis WS 2009/10

2009-10-20T16:10:52Z

UE-InfoVis0910 0401099:

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 04

2009-10-20T16:09:11Z

UE-InfoVis0910 0401099: New page: Test

Test

File:Steffi.jpg

2009-10-20T15:58:52Z

UE-InfoVis0910 0401099: Foto von Stefanie Kaiser

== Summary ==
Foto von Stefanie Kaiser
== Copyright status ==

== Source ==

User:UE-InfoVis0910 0401099

2009-10-20T15:57:23Z

UE-InfoVis0910 0401099:

*'''Name:''' Kaiser, Stefanie
*'''Matrikelnr.:''' 0401099
*'''Master:''' Medieninformatik

[[Image:steffi.jpg]]

User:UE-InfoVis0910 0401099

2009-10-20T15:52:20Z

UE-InfoVis0910 0401099:

*'''Name:''' Kaiser, Stefanie
*'''Matrikelnr.:''' 0401099
*'''Master:''' Medieninformatik

User:UE-InfoVis0910 0401099

2009-10-20T15:50:40Z

UE-InfoVis0910 0401099:

'''Name:''' Kaiser, Stefanie
Matrikelnr.: 0401099
Master: Medieninformatik

User:UE-InfoVis0910 0401099

2009-10-20T15:49:44Z

UE-InfoVis0910 0401099:

Name: Kaiser, Stefanie

Matrikelnr.: 0401099
Master: Medieninformatik

User:UE-InfoVis0910 0401099

2009-10-20T15:49:13Z

UE-InfoVis0910 0401099: New page: Name: Kaiser, Stefanie Matrikelnr.: 0401099 Master: Medieninformatik

Name: Kaiser, Stefanie
Matrikelnr.: 0401099
Master: Medieninformatik