InfoVis:Wiki - User contributions [en]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 3

2010-01-11T09:11:42Z

UE-InfoVis0910 0625100:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe3.html Beschreibung der Aufgabe 3]
=== Zu verbessernde Grafik ===
------------------------------- 
[[Image:geo5_2.jpg]]

=== Review of the Existing Graphic ===

* The current graphic contains many non-data-ink elements which should be reduced to no more that what is necessary to make the data ink understandable [Few, 2004]. Examples of such non-data-ink elements are
** The yellow/brown border around the real graphic
** Border lines
** Box around heading
** Shadow below heading and legend
* The main topic of the graph is to recognize the connection between the CO2 emissions (total and per capita) and the gross domestic product of countries. The region totals displayed in light gray in the background can be omitted, as this data is more distracting than useful.
* The data point labels distract the reader from the actual data as the black font color stands out too much. Furthermore, data points are categorized into several regions by using different colors, whereas the corresponding labels are always black, making the connection between the data point and its label difficult. Also, for very small data points, the color is unrecognizable, making the distinction between different regions impossible.
* The world map in the legend is also drawing attention away from the main data of the graph, a simple legend stating the different regions and their respective color would be enough. Also, the size of the map is too small to be actually useful.
* The main focus of the graph is the comparison between the CO2 emissions per capita and GDP per capita, so this information is represented as the 2d position of the data points, as position is the most accurate visual variable [Cleveland and McGill, 1984].
* Representing the total CO2 emissions for each country using the size of the data point helps understanding the impact of a particular country on the global CO2 emissions. Without this information, it would not be obvious that although Luxembourg has higher CO2 emissions per capita that the USA, its total CO2 emissions are far lower.
* Encoding the total CO2 emissions in the area of the data point is less accurate than using position [Cleveland and McGill, 1984], but nevertheless allows for easy comparison between two countries (the graph shows that the USA and China have roughly the same total CO2 emissions, but their CO2 emissions per capita vary greatly).
* Encoding the population size using the font size of the country label adds another variable to the dataset. This information enables the viewer to make comparisons between different countries based on their population size. The graph shows that although China and India have roughly the same population size, India has much lower total CO2 emissions.

=== Improvements ===

* All non-necessary non-data-ink has been removed, which includes
** The yellow border around the graph
** Border lines
** The box around the heading
** Shadows below the heading and the legend box
* The remaining non-data-ink has been de-emphasized by using a lighter gray for the grid lines, the axes, the axes labels and the legend. Furthermore, non-data-ink has been regularized by using consistent font sizes throughout the graph. Unnecessary bold text in the legend has also been removed.
* In addition to coloring the data points also their respective labels have been color coded. This makes it easier to associate the right labels with the data points. In addition, for small data points, coloring the label as well as the data point makes the distinction between different regions much easier. It also removes the distraction caused by the formerly all black labels as the labels now carry additional information themselves. This additional color coding immediately shows that the majority of African countries is located in the bottom left corner (low GDP, low CO2 emissions), the majority of Latin American countries is located in the center of the graph (average GDP, average CO2 emissions) and that almost all European countries are located on the top right corner of the graph (high GDP, high CO2 emissions), a fact that was not immediately visible in the original graph.
* The legend for region color coding has been simplified by replacing the world map by an alphabetical list of regions.
* Both the encoding of the total CO2 emissions per country using the area of the data points and the population size using the font size of the label have been kept in the improved graph, as both information is valuable to the viewer (as described in the review of the existing graph). Using the size of each mark to add an additional variable is also suggested by Few [2007].

[[Image:ue-infovis0910-group9-ue-3.png]]

=== Further Improvements ===
The population size could be deleted and the overall CO2-emission could be displayed by the size of the country name.

== References ==
[Cleveland and McGill, 1984] W. S. Cleveland and R. McGill. Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods. Journal of the American Statistical Association, 79:531-554, 1984

[Few, 2004] Stephen Few. Show Me the Numbers: Designing Tables and Graphs to Enlighten. Analytics Press, 2004, Chapter 7 – General Design For Communication

[Few, 2007] Stephen Few. Visualising Change: An Innovation in Time-Series Analysis. White Paper, SAS Institute, 2007

CO2 Emissions data set:
http://manyeyes.alphaworks.ibm.com/manyeyes/datasets/carbon-dioxide-emissions-co2-thousan-2/versions/1

http://manyeyes.alphaworks.ibm.com/manyeyes/datasets/carbon-dioxide-emissions-co2-kg-co/versions/1

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 4

2010-01-06T21:09:05Z

UE-InfoVis0910 0625100:

== 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.

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

== 1. Description of application domain, the data, users, tasks and goals ==

=== 1.1. Description of the application domain and the dataset ===

==== 1.1.1. Application domain analysis ====

Task 4 is about to create a pedigree of the descendants of Lisa and Bart Simpson (which means that two separate trees should be created - one for Bart and one for Lisa). Furthermore comparisons of individual sections of the trees should be possible.
 
'''The visualization should represent the following information:'''
 
• family relationships (at least parent-children)

• distinction between blood relatives and family members by marriage

• birthday, day of death and lifetime of all family members

• important events in the life of every family member (e.g. advertisements, prison visits, study time, nobel prize, unemployment, etc.)

• satisfaction of each family member (scale: very low - low - medium - high - very high), may change during the course of life.
 
The visualization should enable the interactive analysis of the data.
 
'''Mandatory:'''

• Opportunities for a better comparison of individual sections of the trees or the comparison of excerpts from Lisa's and Bart's family trees.

• Furthermore at least 2 other possibilities for interaction (e.g. details on demand, filter options)
 
'''General:'''

• the data should be visualized for analysing background stories between family relationships, important events and satisfaction.

==== 1.1.2. Dataset analysis ====

First of all we consider the underlying date as a set of multidimensional multivariate data. Mulitdimensional because of the fact that there are a few attributes in view of every person. Multivariate because we have got multiple person variables. To make the parent-child relationships visible we are going to organize the data hierarchically (like a tree). The datatypes of the attributes are:
 
• Nominal – have no ordering

• Quantitative – exact values
 
'''For each person the following attributes are available:'''
 
• birthday - exact value

• age - exact value

• date of Death - exact value

• important events (e.g. advertisements, prison visits, study time, …) - some text

• satisfaction of each family member - temporal
 
=== 1.2. Audience analysis ===

The visualization is intended for members of the Simpson family who wants to find out more about their family history. Or in other words, for people who wants to operate in the field of genealogy (in view of the Simpson family).

Specificities of the target group are those that some family data and personal data is needed. Gernally all kind of data is useful in our case, which has to do with family. Well, if we are going to create a pedigree for doctors, much more information about the health history per person is needed as the task definition mentioned.

One of the most common visualization techniques used for creating a pedigree are hierarchical ones. So we prefer to use such a technique for our purpose.

=== 1.3. The purpose of the visualization ===

What should be achieved with the visualization or which tasks should be solved?
 
• detection of family relationships

• check wheter a family member belongs to the blood relatives or not

• to find out more about important events in the life of a certain family member

• to make comparisions between some family members in view of some data

• comparison of individual sections of the trees

== 2. Concept ==

=== 2.1. Types of visualization ===
 
'''Main visualization'''

To visualize the pedigree we are going to use a hierachical tree structure where the nodes contain a photo of the corresponding person. First of all only the first person (in our case even Bart or Lisa) is to be visualized. If the user wants to go deeper into the family hierarchy then he or she selects one of the childnodes so that an expansion takes places (so that the children of the selected node are going to be visible on the screen). Well the principle works after the following one:

http://prefuse.org/gallery/treeview/

To close such an expansion the user has only to click at the corresponding node. If the screenspace is too small for further expansions the visualization will go over into a Perspektive Wall which means that the focus lies only on a certain region. Because of the fact that two pedigrees should be developed (one for Bart and one for Lisa) wie have to split the screen into two separate regions where each tree will be displayed. Furthermore a third screen region will be provided. This region works as a working panel at which the user can drop some nodes of the trees into it to make some comparisions. The explanation for this follows in a later section.

[[Image:Unbenannt3.png]]

=== 2.2. Visual Mapping ===

Next, we explain how the different data dimensions are translated into visual attributes:
 
'''Family relationships'''
 
These relationships are visualized by the edges between the nodes
 
'''Blood relatives or family members by marriage'''
 
To make a distinction between blood relatives and family members by marriage we use a different border colour of the photo. For example: if someone is a blood relative then the border of his treenode (which shows a photo from e corresponding person) looks like this:

[[Image:Unbenannt4.png]]

In addition the colour of the outgoing edges could also be in the colour of the photo border.
 
'''Dead'''
 
Next if someone is dead, then were are going to visualise the corresponding tree node like the following one so that the user will see immeadiately if someone is still alive or not.
 
[[Image:Dead.JPG]]
 
'''Relation between a couple'''
 
To see, if a couple is married, divorced or if there is only a relationship between them, serveral symbols could be used to express this. These symbols will be displayed between the corresponding persons (man and woman in general). Well, the first symbol stands for marriage and the second one for divorce. If they are leading a relationship then no icon will be used (displayed between the two corresponding tree nodes).
 
[[Image:Married.JPG]]
 
[[Image:Geschieden.JPG]]
 
=== 2.3. Description of the used techniques/applied principles ===

=== 2.4. Opportunities for interaction ===
 
'''Selection/Highlighting'''
 
To visualize the children of a certain node, the user has to click at the node. Next the childnodes are going to appear on the screen. Furthermore closing the node relationships works similar. If the place on the screen is too small after some expansions, the visualization will go over in a perspektive wall:
 
• Everytime when the user moves forward, the focus lies on this region. If the screenspace becomes too small so all the regions which are not interesting for the user at this time move into the Out-of-Focus region.

• If the user switches back without closing the front nodes, these nodes are going to move into the Out-of-Focus region.
 
'''Explore'''
 
Another possibility to get an overview of the whole tree is zooming. If the user moves the mouse wheel backwards, it will zoom out. Zoom in works in the other direction. For example, at the last zooming out level, the user sees the whole pedigree (which will look like a connected scatterplott). This overview is also useful if the user wants to mark subsets of data the purpose of comparision.

[[Image:Unbenannt2.png]]

By zooming in, the focus will move to a certain region, the will become bigger and the photos of the nodes will be visible again.

[[Image:Unbenannt.png]]

'''Abstract/Elaborate'''
 
To display detailed information about a specific person on demand, the user has to double click at a node. Afterwards a pop-up window, which we call Infobox, appears which contains some informations about the person. These informations are arranged in a table.

==== 2.4.1. Comparison between parts of the pedigree ====

The user should be able to make some comparison in view of the underlying tree data. For this purpose it is necessary to offer the user some interaction mechanism which allows him or her to make such comparisons. Furthermore comparisons among various tree nodes should also be possible. To do so some nodes have to be selected and moved into the working panel. To make various comparisons a botton list should be available for the user (e.g.: bottons for each/some person properties). If the user klicks at such a botton, a corresponding visualisation will be created.
 
'''Temporal plot of the satisfaction (one person)'''
 
In this visualisation the satisfication of some family member (because it may change during the course of life) will be plotted. For this purpose a time-series plot will be used, where the scale of the x-axis contains the time and the y-axes the scale of satisfaction (very low - low - medium - high - very high). So the user has insight about which person has changed its corresponding satisfaction over time.
 
[[Image:infobox.jpg]]
 
Well, this plot is visible in the detailed infobox of a person which means that the user has to open the normal infobox. Furthermore if the user wants to look at the plot, he or she must click at a button, so that an expansion of the infobox take place. As a result the detailed infobox with the corresponding plot appears. Furthermore a comparision between various persons is also possible. For this purpose the user will select some tree node and drop them into the working panel. As a result the infobox for each selected node will be visible in this panel.
 
'''Temporal plot of the satisfaction (more than one person)'''
 
Its like the plot in the detailed infobox, except that points for more than one persons are going to be drawn. To make a distinction between which persons belong to Lisas tree and which family members belong to Barts tree, two different colors for the points will be used. Well in this case it would be clearer if the points are going to be connected by lines so that the user can better distinguish the predecessor and successor of a point.
 
'''Comparison of major events'''
 
A comparison of the major events in view of the selected persons should be made. For this purpose a simple barplot will be drawn. Each bar stand for an appearing event (X-axes) in view of the tree node selection. The incidences of the events will be mapped on the Y-axes. If the selection contains different nodes (from Bart and from Lisas tree) then for each event two bars (with different colors) will be plotted (the one bar says, that this event has occurred in Lisas family and the other one says, the event occurred in Barts family). So the user has an overview of the major events and sees if one even occurred also in the other family. The following figure gives an example for such a barplot (which will occur in the working panel of the main window)
 
[[Image:Gegenüberstellung.JPG]]
 

=== 2.5. Mockup(s)/Fake Screenshots ===

Here is a screenshot of the pedigree visualization program. At the top there are the two pedigrees of bart and lisa simpson. On the left the zoom factor is less big than on the right side. On the bottom you can see the comparison pane and the persons who are compared in detail. To get the person out of the pane it is just necessary to drag it and then drop it outside the pane. All tables and information panes are scrollable.

[[Image:Mockup.jpg]]

At this screenshot the zoom-factor is very small to see the whole pedigree. The Pairs are viewed as one single bubble.

[[Image:Far.jpg]]

=== 2.6. User support in their tasks ===

The User can decide how detailed the view of the pedigree is and what type of information he wants to view. It is possible to view two pedigrees, e.g. of lisa and bart, at the same time. The handling is intuitive and only need clicking and scrolling. The number of generations can easily be seen by a lower number of zoom factor. The comparison pane supports the user in detailed comparison of many persons. This is possible by simply drag and drop of the person into the pane.

=== 2.7. Specificities ===

In this pedigree visualization it is possible to view the portrait of the persons. It is also possible to visualize the feeling of a single person in a chart.

=== 2.8. Pros and cons of the used technology ===

The used technologies enables the user to simply navigate throw the pedigree. The navigation techniques are mostly intuitive and easy to learn.

=== 2.9. Possible expansions and improvements ===

Well for our first version, we have only listend 3 possibilities in view of a comparision between the two pedigrees (see 2.4.1. Comparison between parts of the pedigree). A possible improvement would be to think about more such mechanism for comparisons (e.g.: lifetime-plot which shows in a plot birthday, lifetime and eventually the year of death for the selected persons. So the user would gain a temporal overview in view of the family members).

== 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 09|Gruppe 09]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 4

2010-01-06T21:07:44Z

UE-InfoVis0910 0625100:

== 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.

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

== 1. Description of application domain, the data, users, tasks and goals ==

=== 1.1. Description of the application domain and the dataset ===

==== 1.1.1. Application domain analysis ====

Task 4 is about to create a pedigree of the descendants of Lisa and Bart Simpson (which means that two separate trees should be created - one for Bart and one for Lisa). Furthermore comparisons of individual sections of the trees should be possible.
 
'''The visualization should represent the following information:'''
 
• family relationships (at least parent-children)

• distinction between blood relatives and family members by marriage

• birthday, day of death and lifetime of all family members

• important events in the life of every family member (e.g. advertisements, prison visits, study time, nobel prize, unemployment, etc.)

• satisfaction of each family member (scale: very low - low - medium - high - very high), may change during the course of life.
 
The visualization should enable the interactive analysis of the data.
 
'''Mandatory:'''

• Opportunities for a better comparison of individual sections of the trees or the comparison of excerpts from Lisa's and Bart's family trees.

• Furthermore at least 2 other possibilities for interaction (e.g. details on demand, filter options)
 
'''General:'''

• the data should be visualized for analysing background stories between family relationships, important events and satisfaction.

==== 1.1.2. Dataset analysis ====

First of all we consider the underlying date as a set of multidimensional multivariate data. Mulitdimensional because of the fact that there are a few attributes in view of every person. Multivariate because we have got multiple person variables. To make the parent-child relationships visible we are going to organize the data hierarchically (like a tree). The datatypes of the attributes are:
 
• Nominal – have no ordering

• Quantitative – exact values
 
'''For each person the following attributes are available:'''
 
• birthday - exact value

• age - exact value

• date of Death - exact value

• important events (e.g. advertisements, prison visits, study time, …) - some text

• satisfaction of each family member - temporal
 
=== 1.2. Audience analysis ===

The visualization is intended for members of the Simpson family who wants to find out more about their family history. Or in other words, for people who wants to operate in the field of genealogy (in view of the Simpson family).

Specificities of the target group are those that some family data and personal data is needed. Gernally all kind of data is useful in our case, which has to do with family. Well, if we are going to create a pedigree for doctors, much more information about the health history per person is needed as the task definition mentioned.

One of the most common visualization techniques used for creating a pedigree are hierarchical ones. So we prefer to use such a technique for our purpose.

=== 1.3. The purpose of the visualization ===

What should be achieved with the visualization or which tasks should be solved?
 
• detection of family relationships

• check wheter a family member belongs to the blood relatives or not

• to find out more about important events in the life of a certain family member

• to make comparisions between some family members in view of some data

• comparison of individual sections of the trees

== 2. Concept ==

=== 2.1. Types of visualization ===
 
'''Main visualization'''

To visualize the pedigree we are going to use a hierachical tree structure where the nodes contain a photo of the corresponding person. First of all only the first person (in our case even Bart or Lisa) is to be visualized. If the user wants to go deeper into the family hierarchy then he or she selects one of the childnodes so that an expansion takes places (so that the children of the selected node are going to be visible on the screen). Well the principle works after the following one:

http://prefuse.org/gallery/treeview/

To close such an expansion the user has only to click at the corresponding node. If the screenspace is too small for further expansions the visualization will go over into a Perspektive Wall which means that the focus lies only on a certain region. Because of the fact that two pedigrees should be developed (one for Bart and one for Lisa) wie have to split the screen into two separate regions where each tree will be displayed. Furthermore a third screen region will be provided. This region works as a working panel at which the user can drop some nodes of the trees into it to make some comparisions. The explanation for this follows in a later section.

[[Image:Unbenannt3.png]]

=== 2.2. Visual Mapping ===

Next, we explain how the different data dimensions are translated into visual attributes:
 
'''Family relationships'''
 
These relationships are visualized by the edges between the nodes
 
'''Blood relatives or family members by marriage'''
 
To make a distinction between blood relatives and family members by marriage we use a different border colour of the photo. For example: if someone is a blood relative then the border of his treenode (which shows a photo from e corresponding person) looks like this:

[[Image:Unbenannt4.png]]

In addition the colour of the outgoing edges could also be in the colour of the photo border.
 
'''Dead'''
 
Next if someone is dead, then were are going to visualise the corresponding tree node like the following one so that the user will see immeadiately if someone is still alive or not.
 
[[Image:Dead.JPG]]
 
'''Relation between a couple'''
 
To see, if a couple is married, divorced or if there is only a relationship between them, serveral symbols could be used to express this. These symbols will be displayed between the corresponding persons (man and woman in general). Well, the first symbol stands for marriage and the second one for divorce. If they are leading a relationship then no icon will be used (displayed between the two corresponding tree nodes).
 
[[Image:Married.JPG]]
 
[[Image:Geschieden.JPG]]
 
=== 2.3. Description of the used techniques/applied principles ===

=== 2.4. Opportunities for interaction ===
 
'''Selection/Highlighting'''
 
To visualize the children of a certain node, the user has to click at the node. Next the childnodes are going to appear on the screen. Furthermore closing the node relationships works similar. If the place on the screen is too small after some expansions, the visualization will go over in a perspektive wall:
 
• Everytime when the user moves forward, the focus lies on this region. If the screenspace becomes too small so all the regions which are not interesting for the user at this time move into the Out-of-Focus region.

• If the user switches back without closing the front nodes, these nodes are going to move into the Out-of-Focus region.
 
'''Explore'''
 
Another possibility to get an overview of the whole tree is zooming. If the user moves the mouse wheel backwards, it will zoom out. Zoom in works in the other direction. For example, at the last zooming out level, the user sees the whole pedigree (which will look like a connected scatterplott). This overview is also useful if the user wants to mark subsets of data the purpose of comparision.

[[Image:Unbenannt2.png]]

By zooming in, the focus will move to a certain region, the will become bigger and the photos of the nodes will be visible again.

[[Image:Unbenannt.png]]

'''Abstract/Elaborate'''
 
To display detailed information about a specific person on demand, the user has to double click at a node. Afterwards a pop-up window, which we call Infobox, appears which contains some informations about the person. These informations are arranged in a table.

==== 2.4.1. Comparison between parts of the pedigree ====

The user should be able to make some comparison in view of the underlying tree data. For this purpose it is necessary to offer the user some interaction mechanism which allows him or her to make such comparisons. Furthermore comparisons among various tree nodes should also be possible. To do so some nodes have to be selected and moved into the working panel. To make various comparisons a botton list should be available for the user (e.g.: bottons for each/some person properties). If the user klicks at such a botton, a corresponding visualisation will be created.
 
'''Temporal plot of the satisfaction (one person)'''
 
In this visualisation the satisfication of some family member (because it may change during the course of life) will be plotted. For this purpose a time-series plot will be used, where the scale of the x-axis contains the time and the y-axes the scale of satisfaction (very low - low - medium - high - very high). So the user has insight about which person has changed its corresponding satisfaction over time.
 
[[Image:infobox.jpg]]
 
Well, this plot is visible in the detailed infobox of a person which means that the user has to open the normal infobox. Furthermore if the user wants to look at the plot, he or she must click at a button, so that an expansion of the infobox take place. As a result the detailed infobox with the corresponding plot appears. Furthermore a comparision between various persons is also possible. For this purpose the user will select some tree node and drop them into the working panel. As a result the infobox for each selected node will be visible in this panel.
 
'''Temporal plot of the satisfaction (more than one person)'''
 
Its like the plot in the detailed infobox, except that points for more than one persons are going to be drawn. To make a distinction between which persons belong to Lisas tree and which family members belong to Barts tree, two different colors for the points will be used. Well in this case it would be clearer if the points are going to be connected by lines so that the user can better distinguish the predecessor and successor of a point.
 
'''Comparison of major events'''
 
A comparison of the major events in view of the selected persons should be made. For this purpose a simple barplot will be drawn. Each bar stand for an appearing event (X-axes) in view of the tree node selection. The incidences of the events will be mapped on the Y-axes. If the selection contains different nodes (from Bart and from Lisas tree) then for each event two bars (with different colors) will be plotted (the one bar says, that this event has occurred in Lisas family and the other one says, the event occurred in Barts family). So the user has an overview of the major events and sees if one even occurred also in the other family. The following figure gives an example for such a barplot (which will occur in the working panel of the main window)
 
[[Image:Gegenüberstellung.JPG]]
 

=== 2.5. Mockup(s)/Fake Screenshots ===

Here is a screenshot of the pedigree visualization program. At the top there are the two pedigrees of bart and lisa simpson. On the left the zoom factor is less big than on the right side. On the bottom you can see the comparison pane and the persons who are compared in detail. To get the person out of the pane it is just necessary to drag it and then drop it outside the pane. All tables and information panes are scrollable.
[[Image:Mockup.jpg]]
At this screenshot the zoom-factor is very small to see the whole pedigree. The Pairs are viewed as one single bubble.
[[Image:Far.jpg]]

=== 2.6. User support in their tasks ===

The User can decide how detailed the view of the pedigree is and what type of information he wants to view. It is possible to view two pedigrees, e.g. of lisa and bart, at the same time. The handling is intuitive and only need clicking and scrolling. The number of generations can easily be seen by a lower number of zoom factor. The comparison pane supports the user in detailed comparison of many persons. This is possible by simply drag and drop of the person into the pane.

=== 2.7. Specificities ===

In this pedigree visualization it is possible to view the portrait of the persons. It is also possible to visualize the feeling of a single person in a chart.

=== 2.8. Pros and cons of the used technology ===

The used technologies enables the user to simply navigate throw the pedigree. The navigation techniques are mostly intuitive and easy to learn.

=== 2.9. Possible expansions and improvements ===

Well for our first version, we have only listend 3 possibilities in view of a comparision between the two pedigrees (see 2.4.1. Comparison between parts of the pedigree). A possible improvement would be to think about more such mechanism for comparisons (e.g.: lifetime-plot which shows in a plot birthday, lifetime and eventually the year of death for the selected persons. So the user would gain a temporal overview in view of the family members).

== 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 09|Gruppe 09]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 4

2010-01-05T13:08:24Z

UE-InfoVis0910 0625100:

== 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.

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

Task 4 - Interactive Visualization

== 1. Description of application domain, the data, users, tasks and goals ==

=== 1.1. Description of the application domain and the dataset ===

==== 1.1.1. Application domain analysis ====

Task 4 is about to create a pedigree of the descendants of Lisa and Bart Simpson (which means that two separate trees should be created- one of Bart and one of Lisa) . Furthermore comparisons of individual sections of the trees should be possible.

'''The visualization should represent the following information:'''

• family relationships (at least parent-children)

• distinction between blood relatives and family members by marriage

• birthday, day of death and lifetime of all family members

• important events in the life of every family member (e.g. advertisements, prison visits, study time, nobel prize, unemployment, etc.)

• satisfaction of each family member (scale: very low - low - medium - high - very high), may change during the course of life.

The visualization should enable the interactive analysis of the data.

'''Mandatory:'''

• Opportunities for a better comparison of individual sections of the trees or the comparison of excerpts from Lisa's and Bart's family trees.

• Furthermore at least 2 other possibilities for interaction (e.g. details on demand, filter options)

'''General:'''

• the data should be visualized for analysing background stories between family relationships, important events and satisfaction.

==== 1.1.2. Dataset analysis ====

First of all we consider the underlying date as a set of multidimensional multivariate data. Mulitdimensional because of the fact that there are a few attributes in view of every person. Multivariate because we have got multiple person variables. To make the parent-child relationships visible we are going to organize the data hierarchically (like a tree). The datatypes of the attributes are

Nominal – have no ordering
Quantitative – exact values

'''All in all for person the following attributes are available:'''

birthday - exact value

age - exact value

date of Death - exact value

important events (e.g. advertisements, prison visits, study time, …) - some text

satisfaction of each family member - temporal

=== 1.2. Audience analysis ===

The visualization is intended for members of the Simpson family who wants to find out more about their family history. Or in other words, for people who wants to operate in the field of genealogy (in view of the Simpson family).

Specificities of the target group are those that no specific data is needed in view of a certain domain. For example, if we are going to create a pedigree for doctors, much more information about the health history per person is needed as the task definition mentioned.

One of the most common visualization techniques used for creating a pedigree are hierarchical ones. So we prefer to use such a technique for our purpose.

=== 1.3. The purpose of the visualization ===

What should be achieved with the visualization or which tasks should be solved?
• detection of family relationships

• check wheter a family member belongs to the blood relatives or not

• to find out more about important events in the life of a certain family member

• to make comparisions between some family members in view of some data

• comparison of individual sections of the trees

Questions that can be solved with the help of the visualization
• …

== 2. Concept ==

=== 2.1. Types of visualization ===

Main visualization
To visualize the pedigree we are going to use a hierachical tree structure where the nodes contain a photo of the corresponding person. First of all only the first person (in our case even Bart or Lisa) is to be visualized. If the user wants to go deeper into the family hierarchy then he or she selects one of the childnodes so that an expansion takes places (so that the children of the selected node are going to be visible on the screen). Well the principle works after the following one:

http://prefuse.org/gallery/treeview/

To close such an expansion the user has only to click at the corresponding node. If the screenspace is too small for further expansions the visualization will go over into a Perspektive Wall which means that the focus lies only on a certain region. Because of the fact that two pedigrees should be developed (one for Bart and one for Lisa) wie have to split the screen into two separate regions where each tree will be displayed. Furthermore a third screen region will be provided. This region works as a working panel at which the user can drop some nodes of the trees into it to make some comparisions. The explanation for this follows in a later section.

[[Image:Unbenannt3.png]]

=== 2.2. Visual Mapping ===

Next, we explain how the different data dimensions are translated into visual attributes:

Family relationships
These relationships are visualized by the edges between the nodes

Blood relatives or family members by marriage
To make a distinction between blood relatives and family members by marriage we use a different border colour of the photo. For example: if someone is a blood relative then the border of his treenode (which shows a photo from e corresponding person) looks like this:

[[Image:Unbenannt4.png]]

In addition the colour of the outgoing edges could also be in the colour of the photo border.

=== 2.3. Description of the used techniques/applied principles ===

=== 2.4. Opportunities for interaction ===

Selection/Highlighting
To visualize the children of a certain node, the user has to click at the node. Next the childnodes are going to appear on the screen. Furthermore closing the node relationships works similar. If the place on the screen is too small after some expansions, the visualization will go over in a perspektive wall:

• Everytime when the user moves forward, the focus lies on this region. If the screenspace becomes too small so all the regions which are not interesting for the user at this time move into the Out-of-Focus region.
• If the user switches back without closing the front nodes, these nodes are going to move into the Out-of-Focus region.

Explore
Another possibility to get an overview of the whole tree is zooming. If the user moves the mouse wheel backwards, it will zoom out. Zoom in works in the other direction. For example, at the last zooming out level, the user sees the whole pedigree (which will look like a connected scatterplott). This overview is also useful if the user wants to mark subsets of data the purpose of comparision.

[[Image:Unbenannt2.png]]

By zooming in, the focus will move to a certain region, the will become bigger and the photos of the nodes will be visible again.

[[Image:Unbenannt.png]]

Abstract/Elaborate – show more or less details
To display detailed information about a specific person on demand to the user, he or she has to double click at a node. Afterwards a pop-up window appears which contains some informations about the person. These informations are arranged in a table.

==== 2.4.1. Comparison between parts of the pedigree ====

The user should be able to make some comparison in view of the underlying tree data. For this purpose it is necessary to offer the user some interaction mechanism which allows him or her to make such comparisions.

Temporal plot of the satisfaction of some family member (because it may change during the course of life). For this purpose a time-series plot will be used, where the scale of the x-axis contains the time and the y-axes the scale of satisfaction (very low - low - medium - high - very high). So the user has insight about which person has changed its corresponding satisfaction. Furthermore a comparision between various persons is also possible.

=== 2.5. Mockup(s)/Fake Screenshots ===

Here is a screenshot of the pedigree visualization program. At the top there are the two pedigrees of bart and lisa simpson. On the left the zoom factor is less big than on the right side. On the bottom you can see the comparison pane and the persons who are compared in detail. To get the person out of the pane it is just necessary to drag it and then drop it outside the pane. All tables and information panes are scrollable.
[[Image:Mockup.jpg]]
[[Image:Far.jpg]]

Detailed infobox
[[Image:infobox.jpg]]

=== 2.6. User support in their tasks ===

The User can decide how detailed the view of the pedigree is and what type of information he wants to view. It is possible to view two pedigrees, e.g. of lisa and bart, at the same time. The handling is intuitive and only need clicking and scrolling. The number of generations can easily be seen by a lower number of zoom factor. The comparison pane supports the user in detailed comparison of many persons. This is possible by simply drag and drop of the person into the pane.

=== 2.7. Specificities ===

In this pedigree visualization it is possible to view the portrait of the persons. It is also possible to visualize the feeling of a single person in a chart.

=== 2.8. Pros and cons of the used technology ===

The used technologies enables the user to simply navigate throw the pedigree. The navigation techniques are mostly intuitive and easy to learn.

=== 2.9. Possible expansions and improvements ===

== 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 09|Gruppe 09]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 4

2010-01-05T13:07:45Z

UE-InfoVis0910 0625100:

== 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.

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

Task 4 - Interactive Visualization

== 1. Description of application domain, the data, users, tasks and goals ==

=== 1.1. Description of the application domain and the dataset ===

==== 1.1.1. Application domain analysis ====

Task 4 is about to create a pedigree of the descendants of Lisa and Bart Simpson (which means that two separate trees should be created- one of Bart and one of Lisa) . Furthermore comparisons of individual sections of the trees should be possible.

'''The visualization should represent the following information:'''

• family relationships (at least parent-children)

• distinction between blood relatives and family members by marriage

• birthday, day of death and lifetime of all family members

• important events in the life of every family member (e.g. advertisements, prison visits, study time, nobel prize, unemployment, etc.)

• satisfaction of each family member (scale: very low - low - medium - high - very high), may change during the course of life.

The visualization should enable the interactive analysis of the data.

'''Mandatory:'''

• Opportunities for a better comparison of individual sections of the trees or the comparison of excerpts from Lisa's and Bart's family trees.

• Furthermore at least 2 other possibilities for interaction (e.g. details on demand, filter options)

'''General:'''

• the data should be visualized for analysing background stories between family relationships, important events and satisfaction.

==== 1.1.2. Dataset analysis ====

First of all we consider the underlying date as a set of multidimensional multivariate data. Mulitdimensional because of the fact that there are a few attributes in view of every person. Multivariate because we have got multiple person variables. To make the parent-child relationships visible we are going to organize the data hierarchically (like a tree). The datatypes of the attributes are

Nominal – have no ordering
Quantitative – exact values

'''All in all for person the following attributes are available:'''

birthday - exact value

age - exact value

date of Death - exact value

important events (e.g. advertisements, prison visits, study time, …) - some text

satisfaction of each family member - temporal

=== 1.2. Audience analysis ===

The visualization is intended for members of the Simpson family who wants to find out more about their family history. Or in other words, for people who wants to operate in the field of genealogy (in view of the Simpson family).

Specificities of the target group are those that no specific data is needed in view of a certain domain. For example, if we are going to create a pedigree for doctors, much more information about the health history per person is needed as the task definition mentioned.

One of the most common visualization techniques used for creating a pedigree are hierarchical ones. So we prefer to use such a technique for our purpose.

=== 1.3. The purpose of the visualization ===

What should be achieved with the visualization or which tasks should be solved?
• detection of family relationships

• check wheter a family member belongs to the blood relatives or not

• to find out more about important events in the life of a certain family member

• to make comparisions between some family members in view of some data

• comparison of individual sections of the trees

Questions that can be solved with the help of the visualization
• …

== 2. Concept ==

=== 2.1. Types of visualization ===

Main visualization
To visualize the pedigree we are going to use a hierachical tree structure where the nodes contain a photo of the corresponding person. First of all only the first person (in our case even Bart or Lisa) is to be visualized. If the user wants to go deeper into the family hierarchy then he or she selects one of the childnodes so that an expansion takes places (so that the children of the selected node are going to be visible on the screen). Well the principle works after the following one:

http://prefuse.org/gallery/treeview/

To close such an expansion the user has only to click at the corresponding node. If the screenspace is too small for further expansions the visualization will go over into a Perspektive Wall which means that the focus lies only on a certain region. Because of the fact that two pedigrees should be developed (one for Bart and one for Lisa) wie have to split the screen into two separate regions where each tree will be displayed. Furthermore a third screen region will be provided. This region works as a working panel at which the user can drop some nodes of the trees into it to make some comparisions. The explanation for this follows in a later section.

[[Image:Unbenannt3.png]]

=== 2.2. Visual Mapping ===

Next, we explain how the different data dimensions are translated into visual attributes:

Family relationships
These relationships are visualized by the edges between the nodes

Blood relatives or family members by marriage
To make a distinction between blood relatives and family members by marriage we use a different border colour of the photo. For example: if someone is a blood relative then the border of his treenode (which shows a photo from e corresponding person) looks like this:

[[Image:Unbenannt4.png]]

In addition the colour of the outgoing edges could also be in the colour of the photo border.

=== 2.3. Description of the used techniques/applied principles ===

=== 2.4. Opportunities for interaction ===

Selection/Highlighting
To visualize the children of a certain node, the user has to click at the node. Next the childnodes are going to appear on the screen. Furthermore closing the node relationships works similar. If the place on the screen is too small after some expansions, the visualization will go over in a perspektive wall:

• Everytime when the user moves forward, the focus lies on this region. If the screenspace becomes too small so all the regions which are not interesting for the user at this time move into the Out-of-Focus region.
• If the user switches back without closing the front nodes, these nodes are going to move into the Out-of-Focus region.

Explore
Another possibility to get an overview of the whole tree is zooming. If the user moves the mouse wheel backwards, it will zoom out. Zoom in works in the other direction. For example, at the last zooming out level, the user sees the whole pedigree (which will look like a connected scatterplott). This overview is also useful if the user wants to mark subsets of data the purpose of comparision.

[[Image:Unbenannt2.png]]

By zooming in, the focus will move to a certain region, the will become bigger and the photos of the nodes will be visible again.

[[Image:Unbenannt.png]]

Abstract/Elaborate – show more or less details
To display detailed information about a specific person on demand to the user, he or she has to double click at a node. Afterwards a pop-up window appears which contains some informations about the person. These informations are arranged in a table.

==== 2.4.1. Comparison between parts of the pedigree ====

The user should be able to make some comparison in view of the underlying tree data. For this purpose it is necessary to offer the user some interaction mechanism which allows him or her to make such comparisions.

Temporal plot of the satisfaction of some family member (because it may change during the course of life). For this purpose a time-series plot will be used, where the scale of the x-axis contains the time and the y-axes the scale of satisfaction (very low - low - medium - high - very high). So the user has insight about which person has changed its corresponding satisfaction. Furthermore a comparision between various persons is also possible.

=== 2.5. Mockup(s)/Fake Screenshots ===

Here is a screenshot of the pedigree visualization program. At the top there are the two pedigrees of bart and lisa simpson. On the left the zoom factor is less big than on the right side. On the bottom you can see the comparison pane and the persons who are compared in detail. To get the person out of the pane it is just necessary to drag it and then drop it outside the pane. All tables and information panes are scrollable.
[[Image:Mockup.jpg]]
[[Image:Far.jpg]]

Detailed infobox
[[Image:infobox.jpg]]

=== 2.6. User support in their tasks ===

The User can decide how detailed the view of the pedigree is and what type of information he wants to view. It is possible to view two pedigrees, e.g. of lisa and bart, at the same time. The handling is intuitive and only need clicking and scrolling. The number of generations can easily be seen by a lower number of zoom factor. The comparison pane supports the user in detailed comparison of many persons. This is possible by simply drag and drop of the person into the pane.

=== 2.7. Specificities ===

In this pedigree visualization it is possible to view the portrait of the persons. It is also possible to visualize the feeling of a single person in a chart.

=== 2.8. Pros and cons of the used technology ===

The used technologies enables the user to simply navigate throw the pedigree. The navigation techniques are mostly intuitive and easy to learn.

=== 2.9. Possible expansions and improvements ===

== 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 09|Gruppe 09]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 4

2010-01-05T13:06:22Z

UE-InfoVis0910 0625100:

== 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.

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

Task 4 - Interactive Visualization

== 1. Description of application domain, the data, users, tasks and goals ==

=== 1.1. Description of the application domain and the dataset ===

==== 1.1.1. Application domain analysis ====

Task 4 is about to create a pedigree of the descendants of Lisa and Bart Simpson (which means that two separate trees should be created- one of Bart and one of Lisa) . Furthermore comparisons of individual sections of the trees should be possible.

'''The visualization should represent the following information:'''

• family relationships (at least parent-children)

• distinction between blood relatives and family members by marriage

• birthday, day of death and lifetime of all family members

• important events in the life of every family member (e.g. advertisements, prison visits, study time, nobel prize, unemployment, etc.)

• satisfaction of each family member (scale: very low - low - medium - high - very high), may change during the course of life.

The visualization should enable the interactive analysis of the data.

'''Mandatory:'''

• Opportunities for a better comparison of individual sections of the trees or the comparison of excerpts from Lisa's and Bart's family trees.

• Furthermore at least 2 other possibilities for interaction (e.g. details on demand, filter options)

'''General:'''

• the data should be visualized for analysing background stories between family relationships, important events and satisfaction.

==== 1.1.2. Dataset analysis ====

First of all we consider the underlying date as a set of multidimensional multivariate data. Mulitdimensional because of the fact that there are a few attributes in view of every person. Multivariate because we have got multiple person variables. To make the parent-child relationships visible we are going to organize the data hierarchically (like a tree). The datatypes of the attributes are

Nominal – have no ordering
Quantitative – exact values

'''All in all for person the following attributes are available:'''

birthday exact value

age exact value

date of Death exact value

important events (e.g. advertisements, prison visits, study time, …) some text

satisfaction of each family member temporal

=== 1.2. Audience analysis ===

The visualization is intended for members of the Simpson family who wants to find out more about their family history. Or in other words, for people who wants to operate in the field of genealogy (in view of the Simpson family).

Specificities of the target group are those that no specific data is needed in view of a certain domain. For example, if we are going to create a pedigree for doctors, much more information about the health history per person is needed as the task definition mentioned.

One of the most common visualization techniques used for creating a pedigree are hierarchical ones. So we prefer to use such a technique for our purpose.

=== 1.3. The purpose of the visualization ===

What should be achieved with the visualization or which tasks should be solved?
• detection of family relationships
• check wheter a family member belongs to the blood relatives or not
• to find out more about important events in the life of a certain family member
• to make comparisions between some family members in view of some data
• comparison of individual sections of the trees

Questions that can be solved with the help of the visualization
• …

== 2. Concept ==

=== 2.1. Types of visualization ===

Main visualization
To visualize the pedigree we are going to use a hierachical tree structure where the nodes contain a photo of the corresponding person. First of all only the first person (in our case even Bart or Lisa) is to be visualized. If the user wants to go deeper into the family hierarchy then he or she selects one of the childnodes so that an expansion takes places (so that the children of the selected node are going to be visible on the screen). Well the principle works after the following one:

http://prefuse.org/gallery/treeview/

To close such an expansion the user has only to click at the corresponding node. If the screenspace is too small for further expansions the visualization will go over into a Perspektive Wall which means that the focus lies only on a certain region. Because of the fact that two pedigrees should be developed (one for Bart and one for Lisa) wie have to split the screen into two separate regions where each tree will be displayed. Furthermore a third screen region will be provided. This region works as a working panel at which the user can drop some nodes of the trees into it to make some comparisions. The explanation for this follows in a later section.

[[Image:Unbenannt3.png]]

=== 2.2. Visual Mapping ===

Next, we explain how the different data dimensions are translated into visual attributes:

Family relationships
These relationships are visualized by the edges between the nodes

Blood relatives or family members by marriage
To make a distinction between blood relatives and family members by marriage we use a different border colour of the photo. For example: if someone is a blood relative then the border of his treenode (which shows a photo from e corresponding person) looks like this:

[[Image:Unbenannt4.png]]

In addition the colour of the outgoing edges could also be in the colour of the photo border.

=== 2.3. Description of the used techniques/applied principles ===

=== 2.4. Opportunities for interaction ===

Selection/Highlighting
To visualize the children of a certain node, the user has to click at the node. Next the childnodes are going to appear on the screen. Furthermore closing the node relationships works similar. If the place on the screen is too small after some expansions, the visualization will go over in a perspektive wall:

• Everytime when the user moves forward, the focus lies on this region. If the screenspace becomes too small so all the regions which are not interesting for the user at this time move into the Out-of-Focus region.
• If the user switches back without closing the front nodes, these nodes are going to move into the Out-of-Focus region.

Explore
Another possibility to get an overview of the whole tree is zooming. If the user moves the mouse wheel backwards, it will zoom out. Zoom in works in the other direction. For example, at the last zooming out level, the user sees the whole pedigree (which will look like a connected scatterplott). This overview is also useful if the user wants to mark subsets of data the purpose of comparision.

[[Image:Unbenannt2.png]]

By zooming in, the focus will move to a certain region, the will become bigger and the photos of the nodes will be visible again.

[[Image:Unbenannt.png]]

Abstract/Elaborate – show more or less details
To display detailed information about a specific person on demand to the user, he or she has to double click at a node. Afterwards a pop-up window appears which contains some informations about the person. These informations are arranged in a table.

==== 2.4.1. Comparison between parts of the pedigree ====

The user should be able to make some comparison in view of the underlying tree data. For this purpose it is necessary to offer the user some interaction mechanism which allows him or her to make such comparisions.

Temporal plot of the satisfaction of some family member (because it may change during the course of life). For this purpose a time-series plot will be used, where the scale of the x-axis contains the time and the y-axes the scale of satisfaction (very low - low - medium - high - very high). So the user has insight about which person has changed its corresponding satisfaction. Furthermore a comparision between various persons is also possible.

=== 2.5. Mockup(s)/Fake Screenshots ===

Here is a screenshot of the pedigree visualization program. At the top there are the two pedigrees of bart and lisa simpson. On the left the zoom factor is less big than on the right side. On the bottom you can see the comparison pane and the persons who are compared in detail. To get the person out of the pane it is just necessary to drag it and then drop it outside the pane. All tables and information panes are scrollable.
[[Image:Mockup.jpg]]
[[Image:Far.jpg]]

Detailed infobox
[[Image:infobox.jpg]]

=== 2.6. User support in their tasks ===

The User can decide how detailed the view of the pedigree is and what type of information he wants to view. It is possible to view two pedigrees, e.g. of lisa and bart, at the same time. The handling is intuitive and only need clicking and scrolling. The number of generations can easily be seen by a lower number of zoom factor. The comparison pane supports the user in detailed comparison of many persons. This is possible by simply drag and drop of the person into the pane.

=== 2.7. Specificities ===

In this pedigree visualization it is possible to view the portrait of the persons. It is also possible to visualize the feeling of a single person in a chart.

=== 2.8. Pros and cons of the used technology ===

The used technologies enables the user to simply navigate throw the pedigree. The navigation techniques are mostly intuitive and easy to learn.

=== 2.9. Possible expansions and improvements ===

== 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 09|Gruppe 09]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 4

2010-01-05T13:03:29Z

UE-InfoVis0910 0625100:

== 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.

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

== 1. Description of application domain, the data, users, tasks and goals ==

=== 1.1. Description of the application domain and the dataset ===

==== 1.1.1. Application domain analysis ====

Task 4 is about to create a pedigree of the descendants of Lisa and Bart Simpson (which means that two separate trees should be created- one of Bart and one of Lisa) . Furthermore comparisons of individual sections of the trees should be possible.

The visualization should represent the following information:

• family relationships (at least parent-children)
• distinction between blood relatives and family members by marriage
• birthday, day of death and lifetime of all family members
• important events in the life of every family member (e.g. advertisements, prison visits, study time, nobel prize, unemployment, etc.)
• satisfaction of each family member (scale: very low - low - medium - high - very high), may change during the course of life.

The visualization should enable the interactive analysis of the data.

Mandatory:

• Opportunities for a better comparison of individual sections of the trees or the comparison of excerpts from Lisa's and Bart's family trees.
• Furthermore at least 2 other possibilities for interaction (e.g. details on demand, filter options)

General:

• the data should be visualized for analysing background stories between family relationships, important events and satisfaction.

==== 1.1.2. Dataset analysis ====

First of all we consider the underlying date as a set of multidimensional multivariate data. Mulitdimensional because of the fact that there are a few attributes in view of every person. Multivariate because we have got multiple person variables. To make the parent-child relationships visible we are going to organize the data hierarchically (like a tree). The datatypes of the attributes are

Nominal – have no ordering
Quantitative – exact values

All in all for person the following attributes are available:

birthday exact value
age exact value
date of Death exact value
important events (e.g. advertisements, prison visits, study time, …) some text
satisfaction of each family member temporal

=== 1.2. Audience analysis ===

The visualization is intended for members of the Simpson family who wants to find out more about their family history. Or in other words, for people who wants to operate in the field of genealogy (in view of the Simpson family).

Specificities of the target group are those that no specific data is needed in view of a certain domain. For example, if we are going to create a pedigree for doctors, much more information about the health history per person is needed as the task definition mentioned.

One of the most common visualization techniques used for creating a pedigree are hierarchical ones. So we prefer to use such a technique for our purpose.

=== 1.3. The purpose of the visualization ===

What should be achieved with the visualization or which tasks should be solved?
• detection of family relationships
• check wheter a family member belongs to the blood relatives or not
• to find out more about important events in the life of a certain family member
• to make comparisions between some family members in view of some data
• comparison of individual sections of the trees

Questions that can be solved with the help of the visualization
• …

== 2. Concept ==

=== 2.1. Types of visualization ===

Main visualization
To visualize the pedigree we are going to use a hierachical tree structure where the nodes contain a photo of the corresponding person. First of all only the first person (in our case even Bart or Lisa) is to be visualized. If the user wants to go deeper into the family hierarchy then he or she selects one of the childnodes so that an expansion takes places (so that the children of the selected node are going to be visible on the screen). Well the principle works after the following one:

http://prefuse.org/gallery/treeview/

To close such an expansion the user has only to click at the corresponding node. If the screenspace is too small for further expansions the visualization will go over into a Perspektive Wall which means that the focus lies only on a certain region. Because of the fact that two pedigrees should be developed (one for Bart and one for Lisa) wie have to split the screen into two separate regions where each tree will be displayed. Furthermore a third screen region will be provided. This region works as a working panel at which the user can drop some nodes of the trees into it to make some comparisions. The explanation for this follows in a later section.

[[Image:Unbenannt3.png]]

=== 2.2. Visual Mapping ===

Next, we explain how the different data dimensions are translated into visual attributes:

Family relationships
These relationships are visualized by the edges between the nodes

Blood relatives or family members by marriage
To make a distinction between blood relatives and family members by marriage we use a different border colour of the photo. For example: if someone is a blood relative then the border of his treenode (which shows a photo from e corresponding person) looks like this:

[[Image:Unbenannt4.png]]

In addition the colour of the outgoing edges could also be in the colour of the photo border.

=== 2.3. Description of the used techniques/applied principles ===

=== 2.4. Opportunities for interaction ===

Selection/Highlighting
To visualize the children of a certain node, the user has to click at the node. Next the childnodes are going to appear on the screen. Furthermore closing the node relationships works similar. If the place on the screen is too small after some expansions, the visualization will go over in a perspektive wall:

• Everytime when the user moves forward, the focus lies on this region. If the screenspace becomes too small so all the regions which are not interesting for the user at this time move into the Out-of-Focus region.
• If the user switches back without closing the front nodes, these nodes are going to move into the Out-of-Focus region.

Explore
Another possibility to get an overview of the whole tree is zooming. If the user moves the mouse wheel backwards, it will zoom out. Zoom in works in the other direction. For example, at the last zooming out level, the user sees the whole pedigree (which will look like a connected scatterplott). This overview is also useful if the user wants to mark subsets of data the purpose of comparision.

[[Image:Unbenannt2.png]]

By zooming in, the focus will move to a certain region, the will become bigger and the photos of the nodes will be visible again.

[[Image:Unbenannt.png]]

Abstract/Elaborate – show more or less details
To display detailed information about a specific person on demand to the user, he or she has to double click at a node. Afterwards a pop-up window appears which contains some informations about the person. These informations are arranged in a table.

==== 2.4.1. Comparison between parts of the pedigree ====

The user should be able to make some comparison in view of the underlying tree data. For this purpose it is necessary to offer the user some interaction mechanism which allows him or her to make such comparisions.

Temporal plot of the satisfaction of some family member (because it may change during the course of life). For this purpose a time-series plot will be used, where the scale of the x-axis contains the time and the y-axes the scale of satisfaction (very low - low - medium - high - very high). So the user has insight about which person has changed its corresponding satisfaction. Furthermore a comparision between various persons is also possible.

=== 2.5. Mockup(s)/Fake Screenshots ===

Here is a screenshot of the pedigree visualization program. At the top there are the two pedigrees of bart and lisa simpson. On the left the zoom factor is less big than on the right side. On the bottom you can see the comparison pane and the persons who are compared in detail. To get the person out of the pane it is just necessary to drag it and then drop it outside the pane. All tables and information panes are scrollable.
[[Image:Mockup.jpg]]
[[Image:Far.jpg]]

Detailed infobox
[[Image:infobox.jpg]]

=== 2.6. User support in their tasks ===

The User can decide how detailed the view of the pedigree is and what type of information he wants to view. It is possible to view two pedigrees, e.g. of lisa and bart, at the same time. The handling is intuitive and only need clicking and scrolling. The number of generations can easily be seen by a lower number of zoom factor. The comparison pane supports the user in detailed comparison of many persons. This is possible by simply drag and drop of the person into the pane.

=== 2.7. Specificities ===

In this pedigree visualization it is possible to view the portrait of the persons. It is also possible to visualize the feeling of a single person in a chart.

=== 2.8. Pros and cons of the used technology ===

The used technologies enables the user to simply navigate throw the pedigree. The navigation techniques are mostly intuitive and easy to learn.

=== 2.9. Possible expansions and improvements ===

== 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 09|Gruppe 09]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 4

2010-01-05T12:59:43Z

UE-InfoVis0910 0625100:

== 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.

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

1. Description of application domain, the data, users, tasks and goals

1.1. Description of the application domain and the dataset

1.1.1. Application domain analysis

Task 4 is about to create a pedigree of the descendants of Lisa and Bart Simpson (which means that two separate trees should be created- one of Bart and one of Lisa) . Furthermore comparisons of individual sections of the trees should be possible.

The visualization should represent the following information:

• family relationships (at least parent-children)
• distinction between blood relatives and family members by marriage
• birthday, day of death and lifetime of all family members
• important events in the life of every family member (e.g. advertisements, prison visits, study time, nobel prize, unemployment, etc.)
• satisfaction of each family member (scale: very low - low - medium - high - very high), may change during the course of life.

The visualization should enable the interactive analysis of the data.

Mandatory:

• Opportunities for a better comparison of individual sections of the trees or the comparison of excerpts from Lisa's and Bart's family trees.
• Furthermore at least 2 other possibilities for interaction (e.g. details on demand, filter options)

General:

• the data should be visualized for analysing background stories between family relationships, important events and satisfaction.

1.1.2. Dataset analysis

First of all we consider the underlying date as a set of multidimensional multivariate data. Mulitdimensional because of the fact that there are a few attributes in view of every person. Multivariate because we have got multiple person variables. To make the parent-child relationships visible we are going to organize the data hierarchically (like a tree). The datatypes of the attributes are

Nominal – have no ordering
Quantitative – exact values

All in all for person the following attributes are available:

birthday exact value
age exact value
date of Death exact value
important events (e.g. advertisements, prison visits, study time, …) some text
satisfaction of each family member temporal

1.2. Audience analysis

The visualization is intended for members of the Simpson family who wants to find out more about their family history. Or in other words, for people who wants to operate in the field of genealogy (in view of the Simpson family).

Specificities of the target group are those that no specific data is needed in view of a certain domain. For example, if we are going to create a pedigree for doctors, much more information about the health history per person is needed as the task definition mentioned.

One of the most common visualization techniques used for creating a pedigree are hierarchical ones. So we prefer to use such a technique for our purpose.

1.3. The purpose of the visualization

What should be achieved with the visualization or which tasks should be solved?
• detection of family relationships
• check wheter a family member belongs to the blood relatives or not
• to find out more about important events in the life of a certain family member
• to make comparisions between some family members in view of some data
• comparison of individual sections of the trees

Questions that can be solved with the help of the visualization
• …

2. Concept

2.1. Types of visualization

Main visualization
To visualize the pedigree we are going to use a hierachical tree structure where the nodes contain a photo of the corresponding person. First of all only the first person (in our case even Bart or Lisa) is to be visualized. If the user wants to go deeper into the family hierarchy then he or she selects one of the childnodes so that an expansion takes places (so that the children of the selected node are going to be visible on the screen). Well the principle works after the following one:

http://prefuse.org/gallery/treeview/

To close such an expansion the user has only to click at the corresponding node. If the screenspace is too small for further expansions the visualization will go over into a Perspektive Wall which means that the focus lies only on a certain region. Because of the fact that two pedigrees should be developed (one for Bart and one for Lisa) wie have to split the screen into two separate regions where each tree will be displayed. Furthermore a third screen region will be provided. This region works as a working panel at which the user can drop some nodes of the trees into it to make some comparisions. The explanation for this follows in a later section.

[[Image:Unbenannt3.png]]

2.2. Visual Mapping

Next, we explain how the different data dimensions are translated into visual attributes:

Family relationships
These relationships are visualized by the edges between the nodes

Blood relatives or family members by marriage
To make a distinction between blood relatives and family members by marriage we use a different border colour of the photo. For example: if someone is a blood relative then the border of his treenode (which shows a photo from e corresponding person) looks like this:

[[Image:Unbenannt4.png]]

In addition the colour of the outgoing edges could also be in the colour of the photo border.

2.3. Description of the used techniques/applied principles

2.4. Opportunities for interaction

Selection/Highlighting
To visualize the children of a certain node, the user has to click at the node. Next the childnodes are going to appear on the screen. Furthermore closing the node relationships works similar. If the place on the screen is too small after some expansions, the visualization will go over in a perspektive wall:

• Everytime when the user moves forward, the focus lies on this region. If the screenspace becomes too small so all the regions which are not interesting for the user at this time move into the Out-of-Focus region.
• If the user switches back without closing the front nodes, these nodes are going to move into the Out-of-Focus region.

Explore
Another possibility to get an overview of the whole tree is zooming. If the user moves the mouse wheel backwards, it will zoom out. Zoom in works in the other direction. For example, at the last zooming out level, the user sees the whole pedigree (which will look like a connected scatterplott). This overview is also useful if the user wants to mark subsets of data the purpose of comparision.

[[Image:Unbenannt2.png]]

By zooming in, the focus will move to a certain region, the will become bigger and the photos of the nodes will be visible again.

[[Image:Unbenannt.png]]

Abstract/Elaborate – show more or less details
To display detailed information about a specific person on demand to the user, he or she has to double click at a node. Afterwards a pop-up window appears which contains some informations about the person. These informations are arranged in a table.

2.4.1. Comparison between parts of the pedigree

The user should be able to make some comparison in view of the underlying tree data. For this purpose it is necessary to offer the user some interaction mechanism which allows him or her to make such comparisions.

Temporal plot of the satisfaction of some family member (because it may change during the course of life). For this purpose a time-series plot will be used, where the scale of the x-axis contains the time and the y-axes the scale of satisfaction (very low - low - medium - high - very high). So the user has insight about which person has changed its corresponding satisfaction. Furthermore a comparision between various persons is also possible.

2.5. Mockup(s)/Fake Screenshots

Here is a screenshot of the pedigree visualization program. At the top there are the two pedigrees of bart and lisa simpson. On the left the zoom factor is less big than on the right side. On the bottom you can see the comparison pane and the persons who are compared in detail. To get the person out of the pane it is just necessary to drag it and then drop it outside the pane. All tables and information panes are scrollable.
[[Image:Mockup.jpg]]
[[Image:Far.jpg]]
[[Image:infobox.jpg]]

2.6. User support in their tasks

The User can decide how detailed the view of the pedigree is and what type of information he wants to view. It is possible to view two pedigrees, e.g. of lisa and bart, at the same time. The handling is intuitive and only need clicking and scrolling. The number of generations can easily be seen by a lower number of zoom factor. The comparison pane supports the user in detailed comparison of many persons. This is possible by simply drag and drop of the person into the pane.

2.7. Specificities

In this pedigree visualization it is possible to view the portrait of the persons. It is also possible to visualize the feeling of a single person in a chart.

2.8. Pros and cons of the used technology

The used technologies enables the user to simply navigate throw the pedigree. The navigation techniques are mostly intuitive and easy to learn.

2.9. Possible expansions and improvements

Detailed infobox

== 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 09|Gruppe 09]]

File:Unbenannt4.png

2010-01-05T12:57:53Z

UE-InfoVis0910 0625100: bart red

== Beschreibung ==
bart red
== Copyright status ==

== Source ==

File:Unbenannt3.png

2010-01-05T12:57:36Z

UE-InfoVis0910 0625100: main visualization

== Beschreibung ==
main visualization
== Copyright status ==

== Source ==

File:Unbenannt2.png

2010-01-05T12:57:01Z

UE-InfoVis0910 0625100: Exploring

== Beschreibung ==
Exploring
== Copyright status ==

== Source ==

File:Unbenannt.png

2010-01-05T12:56:44Z

UE-InfoVis0910 0625100: Zooming in region

== Beschreibung ==
Zooming in region
== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 4

2010-01-05T12:52:02Z

UE-InfoVis0910 0625100:

== 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.

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

1. Description of application domain, the data, users, tasks and goals

1.1. Description of the application domain and the dataset

1.1.1. Application domain analysis

Task 4 is about to create a pedigree of the descendants of Lisa and Bart Simpson (which means that two separate trees should be created- one of Bart and one of Lisa) . Furthermore comparisons of individual sections of the trees should be possible.

The visualization should represent the following information:

• family relationships (at least parent-children)
• distinction between blood relatives and family members by marriage
• birthday, day of death and lifetime of all family members
• important events in the life of every family member (e.g. advertisements, prison visits, study time, nobel prize, unemployment, etc.)
• satisfaction of each family member (scale: very low - low - medium - high - very high), may change during the course of life.

The visualization should enable the interactive analysis of the data.

Mandatory:

• Opportunities for a better comparison of individual sections of the trees or the comparison of excerpts from Lisa's and Bart's family trees.
• Furthermore at least 2 other possibilities for interaction (e.g. details on demand, filter options)

General:

• the data should be visualized for analysing background stories between family relationships, important events and satisfaction.

1.1.2. Dataset analysis

First of all we consider the underlying date as a set of multidimensional multivariate data. Mulitdimensional because of the fact that there are a few attributes in view of every person. Multivariate because we have got multiple person variables. To make the parent-child relationships visible we are going to organize the data hierarchically (like a tree). The datatypes of the attributes are

Nominal – have no ordering
Quantitative – exact values

All in all for person the following attributes are available:

birthday exact value
age exact value
date of Death exact value
important events (e.g. advertisements, prison visits, study time, …) some text
satisfaction of each family member temporal

1.2. Audience analysis

The visualization is intended for members of the Simpson family who wants to find out more about their family history. Or in other words, for people who wants to operate in the field of genealogy (in view of the Simpson family).

Specificities of the target group are those that no specific data is needed in view of a certain domain. For example, if we are going to create a pedigree for doctors, much more information about the health history per person is needed as the task definition mentioned.

One of the most common visualization techniques used for creating a pedigree are hierarchical ones. So we prefer to use such a technique for our purpose.

1.3. The purpose of the visualization

What should be achieved with the visualization or which tasks should be solved?
• detection of family relationships
• check wheter a family member belongs to the blood relatives or not
• to find out more about important events in the life of a certain family member
• to make comparisions between some family members in view of some data
• comparison of individual sections of the trees

Questions that can be solved with the help of the visualization
• …

2. Concept

2.1. Types of visualization

Main visualization
To visualize the pedigree we are going to use a hierachical tree structure where the nodes contain a photo of the corresponding person. First of all only the first person (in our case even Bart or Lisa) is to be visualized. If the user wants to go deeper into the family hierarchy then he or she selects one of the childnodes so that an expansion takes places (so that the children of the selected node are going to be visible on the screen). Well the principle works after the following one:

http://prefuse.org/gallery/treeview/

To close such an expansion the user has only to click at the corresponding node. If the screenspace is too small for further expansions the visualization will go over into a Perspektive Wall which means that the focus lies only on a certain region. Because of the fact that two pedigrees should be developed (one for Bart and one for Lisa) wie have to split the screen into two separate regions where each tree will be displayed. Furthermore a third screen region will be provided. This region works as a working panel at which the user can drop some nodes of the trees into it to make some comparisions. The explanation for this follows in a later section.

2.2. Visual Mapping

Next, we explain how the different data dimensions are translated into visual attributes:

Family relationships
These relationships are visualized by the edges between the nodes

Blood relatives or family members by marriage
To make a distinction between blood relatives and family members by marriage we use a different border colour of the photo. For example: if someone is a blood relative then the border of his treenode (which shows a photo from e corresponding person) looks like this:
In addition the colour of the outgoing edges could also be in the colour of the photo border.

2.3. Description of the used techniques/applied principles

2.4. Opportunities for interaction

Selection/Highlighting
To visualize the children of a certain node, the user has to click at the node. Next the childnodes are going to appear on the screen. Furthermore closing the node relationships works similar. If the place on the screen is too small after some expansions, the visualization will go over in a perspektive wall:

• Everytime when the user moves forward, the focus lies on this region. If the screenspace becomes too small so all the regions which are not interesting for the user at this time move into the Out-of-Focus region.
• If the user switches back without closing the front nodes, these nodes are going to move into the Out-of-Focus region.

Explore
Another possibility to get an overview of the whole tree is zooming. If the user moves the mouse wheel backwards, it will zoom out. Zoom in works in the other direction. For example, at the last zooming out level, the user sees the whole pedigree (which will look like a connected scatterplott). This overview is also useful if the user wants to mark subsets of data the purpose of comparision.

By zooming in, the focus will move to a certain region, the will become bigger and the photos of the nodes will be visible again.

Abstract/Elaborate – show more or less details
To display detailed information about a specific person on demand to the user, he or she has to double click at a node. Afterwards a pop-up window appears which contains some informations about the person. These informations are arranged in a table.

2.4.1. Comparison between parts of the pedigree

The user should be able to make some comparison in view of the underlying tree data. For this purpose it is necessary to offer the user some interaction mechanism which allows him or her to make such comparisions.

Temporal plot of the satisfaction of some family member (because it may change during the course of life). For this purpose a time-series plot will be used, where the scale of the x-axis contains the time and the y-axes the scale of satisfaction (very low - low - medium - high - very high). So the user has insight about which person has changed its corresponding satisfaction. Furthermore a comparision between various persons is also possible.

2.5. Mockup(s)/Fake Screenshots

Here is a screenshot of the pedigree visualization program. At the top there are the two pedigrees of bart and lisa simpson. On the left the zoom factor is less big than on the right side. On the bottom you can see the comparison pane and the persons who are compared in detail. To get the person out of the pane it is just necessary to drag it and then drop it outside the pane. All tables and information panes are scrollable.
[[Image:Mockup.jpg]]
[[Image:Far.jpg]]
[[Image:infobox.jpg]]

2.6. User support in their tasks

The User can decide how detailed the view of the pedigree is and what type of information he wants to view. It is possible to view two pedigrees, e.g. of lisa and bart, at the same time. The handling is intuitive and only need clicking and scrolling. The number of generations can easily be seen by a lower number of zoom factor. The comparison pane supports the user in detailed comparison of many persons. This is possible by simply drag and drop of the person into the pane.

2.7. Specificities

In this pedigree visualization it is possible to view the portrait of the persons. It is also possible to visualize the feeling of a single person in a chart.

2.8. Pros and cons of the used technology

The used technologies enables the user to simply navigate throw the pedigree. The navigation techniques are mostly intuitive and easy to learn.

2.9. Possible expansions and improvements

Detailed infobox

== 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 09|Gruppe 09]]

File:Mockup.jpg

2010-01-05T12:50:39Z

UE-InfoVis0910 0625100: The screenshot with higher detail

== Beschreibung ==
The screenshot with higher detail
== Copyright status ==

== Source ==

File:Infobox.jpg

2010-01-05T12:50:18Z

UE-InfoVis0910 0625100: Infox in detail

== Beschreibung ==
Infox in detail
== Copyright status ==

== Source ==

File:Far.jpg

2010-01-05T12:50:01Z

UE-InfoVis0910 0625100: Screenshot with low zoom

== Beschreibung ==
Screenshot with low zoom
== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 4

2010-01-05T12:49:06Z

UE-InfoVis0910 0625100:

== 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.

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

1. Description of application domain, the data, users, tasks and goals

1.1. Description of the application domain and the dataset

1.1.1. Application domain analysis

Task 4 is about to create a pedigree of the descendants of Lisa and Bart Simpson (which means that two separate trees should be created- one of Bart and one of Lisa) . Furthermore comparisons of individual sections of the trees should be possible.

The visualization should represent the following information:

• family relationships (at least parent-children)
• distinction between blood relatives and family members by marriage
• birthday, day of death and lifetime of all family members
• important events in the life of every family member (e.g. advertisements, prison visits, study time, nobel prize, unemployment, etc.)
• satisfaction of each family member (scale: very low - low - medium - high - very high), may change during the course of life.

The visualization should enable the interactive analysis of the data.

Mandatory:

• Opportunities for a better comparison of individual sections of the trees or the comparison of excerpts from Lisa's and Bart's family trees.
• Furthermore at least 2 other possibilities for interaction (e.g. details on demand, filter options)

General:

• the data should be visualized for analysing background stories between family relationships, important events and satisfaction.

1.1.2. Dataset analysis

First of all we consider the underlying date as a set of multidimensional multivariate data. Mulitdimensional because of the fact that there are a few attributes in view of every person. Multivariate because we have got multiple person variables. To make the parent-child relationships visible we are going to organize the data hierarchically (like a tree). The datatypes of the attributes are

Nominal – have no ordering
Quantitative – exact values

All in all for person the following attributes are available:

birthday exact value
age exact value
date of Death exact value
important events (e.g. advertisements, prison visits, study time, …) some text
satisfaction of each family member temporal

1.2. Audience analysis

The visualization is intended for members of the Simpson family who wants to find out more about their family history. Or in other words, for people who wants to operate in the field of genealogy (in view of the Simpson family).

Specificities of the target group are those that no specific data is needed in view of a certain domain. For example, if we are going to create a pedigree for doctors, much more information about the health history per person is needed as the task definition mentioned.

One of the most common visualization techniques used for creating a pedigree are hierarchical ones. So we prefer to use such a technique for our purpose.

1.3. The purpose of the visualization

What should be achieved with the visualization or which tasks should be solved?
• detection of family relationships
• check wheter a family member belongs to the blood relatives or not
• to find out more about important events in the life of a certain family member
• to make comparisions between some family members in view of some data
• comparison of individual sections of the trees

Questions that can be solved with the help of the visualization
• …

2. Concept

2.1. Types of visualization

Main visualization
To visualize the pedigree we are going to use a hierachical tree structure where the nodes contain a photo of the corresponding person. First of all only the first person (in our case even Bart or Lisa) is to be visualized. If the user wants to go deeper into the family hierarchy then he or she selects one of the childnodes so that an expansion takes places (so that the children of the selected node are going to be visible on the screen). Well the principle works after the following one:

http://prefuse.org/gallery/treeview/

To close such an expansion the user has only to click at the corresponding node. If the screenspace is too small for further expansions the visualization will go over into a Perspektive Wall which means that the focus lies only on a certain region. Because of the fact that two pedigrees should be developed (one for Bart and one for Lisa) wie have to split the screen into two separate regions where each tree will be displayed. Furthermore a third screen region will be provided. This region works as a working panel at which the user can drop some nodes of the trees into it to make some comparisions. The explanation for this follows in a later section.

2.2. Visual Mapping

Next, we explain how the different data dimensions are translated into visual attributes:

Family relationships
These relationships are visualized by the edges between the nodes

Blood relatives or family members by marriage
To make a distinction between blood relatives and family members by marriage we use a different border colour of the photo. For example: if someone is a blood relative then the border of his treenode (which shows a photo from e corresponding person) looks like this:
In addition the colour of the outgoing edges could also be in the colour of the photo border.

2.3. Description of the used techniques/applied principles

2.4. Opportunities for interaction

Selection/Highlighting
To visualize the children of a certain node, the user has to click at the node. Next the childnodes are going to appear on the screen. Furthermore closing the node relationships works similar. If the place on the screen is too small after some expansions, the visualization will go over in a perspektive wall:

• Everytime when the user moves forward, the focus lies on this region. If the screenspace becomes too small so all the regions which are not interesting for the user at this time move into the Out-of-Focus region.
• If the user switches back without closing the front nodes, these nodes are going to move into the Out-of-Focus region.

Explore
Another possibility to get an overview of the whole tree is zooming. If the user moves the mouse wheel backwards, it will zoom out. Zoom in works in the other direction. For example, at the last zooming out level, the user sees the whole pedigree (which will look like a connected scatterplott). This overview is also useful if the user wants to mark subsets of data the purpose of comparision.

By zooming in, the focus will move to a certain region, the will become bigger and the photos of the nodes will be visible again.

Abstract/Elaborate – show more or less details
To display detailed information about a specific person on demand to the user, he or she has to double click at a node. Afterwards a pop-up window appears which contains some informations about the person. These informations are arranged in a table.

2.4.1. Comparison between parts of the pedigree

The user should be able to make some comparison in view of the underlying tree data. For this purpose it is necessary to offer the user some interaction mechanism which allows him or her to make such comparisions.

Temporal plot of the satisfaction of some family member (because it may change during the course of life). For this purpose a time-series plot will be used, where the scale of the x-axis contains the time and the y-axes the scale of satisfaction (very low - low - medium - high - very high). So the user has insight about which person has changed its corresponding satisfaction. Furthermore a comparision between various persons is also possible.

2.5. Mockup(s)/Fake Screenshots

Here is a screenshot of the pedigree visualization program. At the top there are the two pedigrees of bart and lisa simpson. On the left the zoom factor is less big than on the right side. On the bottom you can see the comparison pane and the persons who are compared in detail. To get the person out of the pane it is just necessary to drag it and then drop it outside the pane. All tables and information panes are scrollable.

2.6. User support in their tasks

The User can decide how detailed the view of the pedigree is and what type of information he wants to view. It is possible to view two pedigrees, e.g. of lisa and bart, at the same time. The handling is intuitive and only need clicking and scrolling. The number of generations can easily be seen by a lower number of zoom factor. The comparison pane supports the user in detailed comparison of many persons. This is possible by simply drag and drop of the person into the pane.

2.7. Specificities

In this pedigree visualization it is possible to view the portrait of the persons. It is also possible to visualize the feeling of a single person in a chart.

2.8. Pros and cons of the used technology

The used technologies enables the user to simply navigate throw the pedigree. The navigation techniques are mostly intuitive and easy to learn.

2.9. Possible expansions and improvements

Detailed infobox

== 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 09|Gruppe 09]]

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 3

2009-12-09T11:46:28Z

UE-InfoVis0910 0625100:

Teaching talk:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 3

2009-12-09T11:44:50Z

UE-InfoVis0910 0625100: New page: ~~~~

[[User:UE-InfoVis0910 0625100|UE-InfoVis0910 0625100]] 12:44, 9 December 2009 (CET)

File:Sheet 2.jpg

2009-12-09T11:41:29Z

UE-InfoVis0910 0625100: New page: == Beschreibung == == Copyright status == == Source ==

== Beschreibung ==

== Copyright status ==

== Source ==

File:Sheet 1.jpg

2009-12-09T11:41:14Z

UE-InfoVis0910 0625100: New page: == Beschreibung == == Copyright status == == Source ==

== Beschreibung ==

== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 3

2009-12-08T16:07:03Z

UE-InfoVis0910 0625100:

File:Sheet 4.jpg

2009-12-08T15:23:29Z

UE-InfoVis0910 0625100: New page: == Beschreibung == == Copyright status == == Source ==

== Beschreibung ==

== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 2

2009-12-06T23:28:42Z

UE-InfoVis0910 0625100:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
=== Zu beurteilende Tabelle ===
[[Image:table3.gif]]

=== Review of the Existing Table ===
We have reviewed the table above based on Stephen Few's work "Show Me the Numbers: Designing Tables and Graphs to Enlighten" which contains some important rules and advices in view of designing tables.

* A grid is used to delineate columns and rows of the table, which should be avoided as grids break up the data.
* Rules are used to form a boundary around the entire table, which should be avoided if white space permits.
* Numbers in scientific notation are hard to read and not easily comparable to each other.
* Numbers are not aligned properly (numbers that represent quantitative values should always be aligned to the right)
* The headers should be aligned with the associated data. This is international.
* Placing a comma to the left of every three whole-number digits would improve the readability.
* The readability would also be improved if for each value the same number of decimal digits is going to be used, even when they are zeroes.

=== Enhanced Table ===
[[Image:uebung_2_n2.jpg]]

=== Changes to the Table ===
* The table has been split into two separate tables, as the numbers of the two blocks are not comparable.
* The grid has been removed, as delineation of columns and rows is its least effective use [Few, 2004]. Only the header areas are separated from the body of the tables using rules.
* Columns and rows are delineated using white space only, which enhances readability [Few, 2004].
* The U-235 enrichment column is delineated from the rest of the body, as it is a calculated value based on the other columns.
* A percent sign was added to each value in the U-235 enrichment column because percentages are used less often than other units of measure, so it’s easy when reading down columns of numbers to forget that you’re looking at percentages [Few, 2004].
* Numbers are aligned to the right.
* The Unit-column has been removed, because they should be part of the headers [Wallace, 2005]. In our case the units are now part of the spanner headers.
* In general, text should always be aligned to the left! Furthermore one exception to the practice of left alignment works well for columns of text: when the entries each consist of the same number of characters and the column header consists of several more characters than the text entries [Few, 2004]. So I think it also works very well in view of numbers.

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

[Wallace, 2005] Rosa Wallace. Designing Tables.
http://www.ncsu.edu/labwrite/res/gh/gh-tables.html

== 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 09|Gruppe 09]]

File:Uebung 2 n2.jpg

2009-12-06T23:28:16Z

UE-InfoVis0910 0625100: New page: == Beschreibung == == Copyright status == == Source ==

== Beschreibung ==

== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 2

2009-12-01T08:54:37Z

UE-InfoVis0910 0625100:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
=== Zu beurteilende Tabelle ===
[[Image:table3.gif]]

=== Review of the Existing Table ===
We have reviewed the table above based on Stephen Few's work "Show Me the Numbers: Designing Tables and Graphs to Enlighten" which contains some important rules and advices in view of designing tables.

* A grid is used to delineate columns and rows of the table, which should be avoided as grids break up the data.
* Rules are used to form a boundary around the entire table, which should be avoided if white space permits.
* Numbers in scientific notation are hard to read and not easily comparable to each other.
* Numbers are not aligned properly (numbers that represent quantitative values should always be aligned to the right)
* The headers should be aligned with the associated data. This is international.
* Placing a comma to the left of every three whole-number digits would improve the readability.
* The readability would also be improved if for each value the same number of decimal digits is going to be used, even when they are zeroes.

=== Enhanced Table ===
[[Image:uebung_2_n.jpg]]

=== Changes to the Table ===
* The table has been split into two separate tables, as the numbers of the two blocks are not comparable.
* The grid has been removed, as delineation of columns and rows is its least effective use [Few, 2004]. Only the header areas are separated from the body of the tables using rules.
* Columns and rows are delineated using white space only, which enhances readability [Few, 2004].
* The U-235 enrichment column is delineated from the rest of the body, as it is a calculated value based on the other columns.
* A percent sign was added to each value in the U-235 enrichment column because percentages are used less often than other units of measure, so it’s easy when reading down columns of numbers to forget that you’re looking at percentages [Few, 2004].
* Numbers are aligned to the right.
* The Unit-column has been removed, because they should be part of the headers [Wallace, 2005]. In our case the units are now part of the spanner headers.
* In general, text should always be aligned to the left! Furthermore one exception to the practice of left alignment works well for columns of text: when the entries each consist of the same number of characters and the column header consists of several more characters than the text entries [Few, 2004]. So I think it also works very well in view of numbers.

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

[Wallace, 2005] Rosa Wallace. Designing Tables.
http://www.ncsu.edu/labwrite/res/gh/gh-tables.html

== 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 09|Gruppe 09]]

File:Uebung 2 n.jpg

2009-12-01T08:53:49Z

UE-InfoVis0910 0625100: Übung 2 update

== Beschreibung ==
Übung 2 update
== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 3

2009-11-23T20:45:40Z

UE-InfoVis0910 0625100:

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 3

2009-11-23T20:36:59Z

UE-InfoVis0910 0625100:

Teaching talk:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 2

2009-11-16T14:41:36Z

UE-InfoVis0910 0625100:

--[[User:UE-InfoVis0910 0625847|UE-InfoVis0910 0625847]] 15:20, 15 November 2009 (CET)
 
'''Assumption'''
 
I have been looking on http://sti.srs.gov/fulltext/tr2002506/tr2002506.html to learn more about the topic of this table. Decontaminated liquid waste has to be disposed! Well, samples of solids were removed from Tank 50H during October of 2002 and sent to the Savannah River Technology Center for analysis [Wilmarth et al., 2002]. Three core samples were sent to SRTC (labeled as TK50-HTF-E-195, TK50-HTF-E-196, and TK50-HTF-E-197). So our table contains the results from radiochemical analysis of three samples from Tank 50H using Aqua Regia Digestion. And the samples were analyzed in duplicate.
 
'''Inprovement propositions'''
 
'''White Space'''
 
White space can be intentionally manipulated to direct your readers’ eyes to either scan predominantly across the columns or down the rows [Few, 2004]. So I would prefer to direct the readers to scan predominantly across the rows so that comparision between the three samples in view of a certain element could be done easier. Hence the the vertical white space between the rows should be bigger. But be careful: This balance between white space and overall data
density is upset when the vertical white space between the rows exceeds the vertical space used by the rows of data themselves [Few, 2004].
 
'''Rules and Grids'''
 
Grids are useless in view of delineating columns and rows [Few, 2004]. Als rules have only a limited usefulness. The problem with rules and grids is that they break up the data (the lines distract the eye, promoting a strong perception of individual cells through the Gestalt principle of enclosure rather than a seamless flow of information). So I would delete the whole grids. Furthermore I would only use rules to separate the header and footer from the body.
 
'''Columns and rows'''
 
You should almost always arrange the categorical subdivisions bidirectionally when you can fit one or more sets of categorical subdivisions across the columns [Few, 2004]. So I wouldn’t do any changes.
 
'''Data Sequence Alignment'''
 
Numbers that represent quantitative values, as opposed to those that are merely identifiers (e.g., customer numbers), should always be aligned to the right [Few, 2004] So I would do so instead of aligning it to the centre. Furthermore I would align both the decimal point and the final digit to the right. This can be accomplished by expressing each value using the same number of decimal digits, even when they are zeroes [Few., 2004]. Now lets have a look at the text. Text that expresses neither numbers nor dates works best when aligned to the left because of the historical conventions of printing [Few, 2004]. So changing into this would be adviseable.
 
Furthermore the headers should be aligned like their associated data, because this is international [Few, 2004]. E.g.: ff the column’s data are left aligned, its header is left aligned as well, and so on.
 
'''Number Precision'''
 
The level of precision should not exceed the level needed to serve your
communication objectives and the needs of your readers [Few, 2004].
 
'''Measuring Units'''
 
Columns should be titled with the name of the variables followed by the units of measure in parentheses[Wallace, 2005]. I woud do so and delete the column called unit.
 
'''Spanner Headers'''
 
We could use a spanner header per sample e.g.: TK50-HTK-E-195 for the first sample and 1 and 2 as columnheaders for the two columns below the spanner header which stands for the duplicate analysis of one sample.
 
'''Ambiguities'''
 
* I don’t know but are the units dgm/g and microg/g compatible or comparative? If not, then I would break the sets of data into smaller groups in view of their unit
* No americium-241 was detected in the solid samples [Wilmarth et al., 2002] . So if there is no americium-241 I think it should be announced in the table
*Furthermore the table contains the results from radiochemical analysis using gamma spectroscopy, alpha spectroscopy and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) Few., 2004. Does this mean that for every sample another method (e.g.: gamma analysis) has been used? If so then I think we should note this fact in the table.
 
'''Refereces'''
 
[Few, 2004] Stephen Few. Show Me the Numbers: Designing Tables and Graphs to Enlighten. Analytics Press, 2004, Chapter 8 – Table Design
 
[Wallace, 2005] Rosa Wallace. Designing Tables.
http://www.ncsu.edu/labwrite/res/gh/gh-tables.html
 
[Wilmarth et al., 2002] W. R. Wilmarth, C. J. Coleman, F. F. Fondeur, V. H. Dukes, M. P. Bussey, M. S. Blume, and A. V. Bowman. Results of Sample Analysis from Solids Removed from Tank 50H. http://sti.srs.gov/fulltext/tr2002506/tr2002506.html

----

=== Units ===
* ''dpm/g'' are disintegrations per minute per gram.
* ''microg/g'' are micrograms per gram.

I suggest adding footnotes describing the abbreviations.

The two units are not comparable, I suggest splitting the information into two separate tables. The first should contain data about Sb-125, Cs-137, Sr-90, Pu-239/240 and Pu-238, the second table data about the different Uranium isotopes.

=== Data Rows ===
* Sb is Antimony, Sb-125 is a synthetic radioisotope.
* Cs is Caesium, Cs-137 occurs naturally only in trace amounts.
* Sr is Strontium, Sr-90 occurs naturally only in trace amounts.
* Pu is Plutonium, Pu-239 occurs naturally only in trace amounts, Pu-238 and Pu-240 are synthetic radioisotopes.
* 232, 235, 236, 238 and 239 are different isotopes of Uranium, so I'd suggest naming them U-232, U-235, U-236, U-238 and U-239 respectively for consistency reasons. U-232 and U-239 are synthetic radioisotopes; U-236 occurs naturally only in trace amounts; U-235 has a natural abundance of 0,72%; U-238 of 99,27%.
* ''% U Enrichment'' measures the fraction of U-235 (which is fissile), the natural concentration of which is 0,71%.

Should we mark synthetic radioisotopes to distinguish them from naturally occuring isotopes?

=== Other ===
The percentage sign should be placed to the right of ''each'' value. [Few, 2004]

--[[User:UE-InfoVis0910 9930270|UE-InfoVis0910 9930270]] 14:27, 16 November 2009 (CET)

[[User:UE-InfoVis0910 0625100|UE-InfoVis0910 0625100]] 15:40, 16 November 2009 (CET)

I think the abbreviations are not necessary, because if you know what they mean you won't need a description.

Teaching talk:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 2

2009-11-16T14:41:12Z

UE-InfoVis0910 0625100:

Teaching talk:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 2

2009-11-16T14:40:57Z

UE-InfoVis0910 0625100:

Teaching talk:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 2

2009-11-16T14:40:39Z

UE-InfoVis0910 0625100:

--[[User:UE-InfoVis0910 0625847|UE-InfoVis0910 0625847]] 15:20, 15 November 2009 (CET)
 
'''Assumption'''
 
I have been looking on http://sti.srs.gov/fulltext/tr2002506/tr2002506.html to learn more about the topic of this table. Decontaminated liquid waste has to be disposed! Well, samples of solids were removed from Tank 50H during October of 2002 and sent to the Savannah River Technology Center for analysis [Wilmarth et al., 2002]. Three core samples were sent to SRTC (labeled as TK50-HTF-E-195, TK50-HTF-E-196, and TK50-HTF-E-197). So our table contains the results from radiochemical analysis of three samples from Tank 50H using Aqua Regia Digestion. And the samples were analyzed in duplicate.
 
'''Inprovement propositions'''
 
'''White Space'''
 
White space can be intentionally manipulated to direct your readers’ eyes to either scan predominantly across the columns or down the rows [Few, 2004]. So I would prefer to direct the readers to scan predominantly across the rows so that comparision between the three samples in view of a certain element could be done easier. Hence the the vertical white space between the rows should be bigger. But be careful: This balance between white space and overall data
density is upset when the vertical white space between the rows exceeds the vertical space used by the rows of data themselves [Few, 2004].
 
'''Rules and Grids'''
 
Grids are useless in view of delineating columns and rows [Few, 2004]. Als rules have only a limited usefulness. The problem with rules and grids is that they break up the data (the lines distract the eye, promoting a strong perception of individual cells through the Gestalt principle of enclosure rather than a seamless flow of information). So I would delete the whole grids. Furthermore I would only use rules to separate the header and footer from the body.
 
'''Columns and rows'''
 
You should almost always arrange the categorical subdivisions bidirectionally when you can fit one or more sets of categorical subdivisions across the columns [Few, 2004]. So I wouldn’t do any changes.
 
'''Data Sequence Alignment'''
 
Numbers that represent quantitative values, as opposed to those that are merely identifiers (e.g., customer numbers), should always be aligned to the right [Few, 2004] So I would do so instead of aligning it to the centre. Furthermore I would align both the decimal point and the final digit to the right. This can be accomplished by expressing each value using the same number of decimal digits, even when they are zeroes [Few., 2004]. Now lets have a look at the text. Text that expresses neither numbers nor dates works best when aligned to the left because of the historical conventions of printing [Few, 2004]. So changing into this would be adviseable.
 
Furthermore the headers should be aligned like their associated data, because this is international [Few, 2004]. E.g.: ff the column’s data are left aligned, its header is left aligned as well, and so on.
 
'''Number Precision'''
 
The level of precision should not exceed the level needed to serve your
communication objectives and the needs of your readers [Few, 2004].
 
'''Measuring Units'''
 
Columns should be titled with the name of the variables followed by the units of measure in parentheses[Wallace, 2005]. I woud do so and delete the column called unit.
 
'''Spanner Headers'''
 
We could use a spanner header per sample e.g.: TK50-HTK-E-195 for the first sample and 1 and 2 as columnheaders for the two columns below the spanner header which stands for the duplicate analysis of one sample.
 
'''Ambiguities'''
 
* I don’t know but are the units dgm/g and microg/g compatible or comparative? If not, then I would break the sets of data into smaller groups in view of their unit
* No americium-241 was detected in the solid samples [Wilmarth et al., 2002] . So if there is no americium-241 I think it should be announced in the table
*Furthermore the table contains the results from radiochemical analysis using gamma spectroscopy, alpha spectroscopy and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) Few., 2004. Does this mean that for every sample another method (e.g.: gamma analysis) has been used? If so then I think we should note this fact in the table.
 
'''Refereces'''
 
[Few, 2004] Stephen Few. Show Me the Numbers: Designing Tables and Graphs to Enlighten. Analytics Press, 2004, Chapter 8 – Table Design
 
[Wallace, 2005] Rosa Wallace. Designing Tables.
http://www.ncsu.edu/labwrite/res/gh/gh-tables.html
 
[Wilmarth et al., 2002] W. R. Wilmarth, C. J. Coleman, F. F. Fondeur, V. H. Dukes, M. P. Bussey, M. S. Blume, and A. V. Bowman. Results of Sample Analysis from Solids Removed from Tank 50H. http://sti.srs.gov/fulltext/tr2002506/tr2002506.html

----

=== Units ===
* ''dpm/g'' are disintegrations per minute per gram.
* ''microg/g'' are micrograms per gram.

I suggest adding footnotes describing the abbreviations.

The two units are not comparable, I suggest splitting the information into two separate tables. The first should contain data about Sb-125, Cs-137, Sr-90, Pu-239/240 and Pu-238, the second table data about the different Uranium isotopes.

=== Data Rows ===
* Sb is Antimony, Sb-125 is a synthetic radioisotope.
* Cs is Caesium, Cs-137 occurs naturally only in trace amounts.
* Sr is Strontium, Sr-90 occurs naturally only in trace amounts.
* Pu is Plutonium, Pu-239 occurs naturally only in trace amounts, Pu-238 and Pu-240 are synthetic radioisotopes.
* 232, 235, 236, 238 and 239 are different isotopes of Uranium, so I'd suggest naming them U-232, U-235, U-236, U-238 and U-239 respectively for consistency reasons. U-232 and U-239 are synthetic radioisotopes; U-236 occurs naturally only in trace amounts; U-235 has a natural abundance of 0,72%; U-238 of 99,27%.
* ''% U Enrichment'' measures the fraction of U-235 (which is fissile), the natural concentration of which is 0,71%.

Should we mark synthetic radioisotopes to distinguish them from naturally occuring isotopes?

=== Other ===
The percentage sign should be placed to the right of ''each'' value. [Few, 2004]

--[[User:UE-InfoVis0910 9930270|UE-InfoVis0910 9930270]] 14:27, 16 November 2009 (CET)

[[User:UE-InfoVis0910 0625100|UE-InfoVis0910 0625100]]
I think the abbreviations are not necessary, because if you know what they mean you also won't need a description.

Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 2

2009-11-16T14:35:50Z

UE-InfoVis0910 0625100:

== Aufgabenstellung ==
[http://ieg.ifs.tuwien.ac.at/~gschwand/teaching/infovis_ue_ws09/infovis_ue_aufgabe2.html Beschreibung der Aufgabe 2]
=== Zu beurteilende Tabelle ===
[[Image:table3.gif]]

=== Verbesserte Tabelle ===
[[Image:uebung_2.gif]]

== 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 09|Gruppe 09]]

File:Uebung 2.gif

2009-11-16T14:34:34Z

UE-InfoVis0910 0625100: Gruppe 9, WS09/10

== Beschreibung ==
Gruppe 9, WS09/10
== Copyright status ==

== Source ==

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 07 - Aufgabe 1 - Pie Chart

2009-11-06T17:16:54Z

UE-InfoVis0910 0625100:

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 1 | Zurueck zu Aufgabe 1]]

== Pie Charts==

=== Definition ===
{{Quotation | A '''pie chart''' (or a '''circle graph''') is a circular chart divided into sectors, illustrating relative magnitudes or frequencies. In a pie chart, the arc length of each sector (and consequently its central angle and area), is proportional to the quantity it represents. Together, the sectors create a full disk. It is named for its resemblance to a pie which has been sliced.| [Wikipedia, 2008]}}

----

===How to use it===
Pie charts are used to show percentages. The circle provides a visual concept of the whole (100%). Despite its popularity, pie charts should be used sparingly for two reasons [Statistics Canada, 2008]:
 
* Use less than six components - otherwise, the resulting picture will be too complex to understand.
* Not useful when the values of each component are similar because it is difficult to see the differences between slice sizes.
 
To present certain values in a pie chart it is necessary to determine how many degrees represent this share of data in comparison to the whole circle. This calculation is done by developing the equation:

percent ÷ 100 x 360 degrees = the number of degrees

This ratio works because the total percent of the pie chart represents 100% and there are 360 degrees in a circle [Statistics Canada, 2008].
 
To construct a pie chart the following steps are necessary [Concordia University, 1999]:
* '''Determine the proportions:''' find the total value for the entire category being studied and calculate the percentage for each segment or part.
* '''Calculate degrees:''' convert the percentage values for each segment into degrees relative to the 360 degrees in the circle.
* '''Construct the chart:''' draw a circle and divide it into appropriately sized segments.
* '''Add labels and a title:''' label each segment or add a legend to identify the segments. Then clearly title the chart.

----

=== Variants of the Pie Chart ===

There are different variants of pie charts [Wikipedia, 2008]:
* '''Exploded Pie Chart:''' One ore more sectors are separated from the rest, to highlight it.
* '''Perspective (3D) pie chart:''' Mainly for aesthetic reasons the pie chart is displayed in 3D. But the third dimension does not improve the reading of the data. On the contrary, these plots are difficult to interpret because of the distorted effect of perspective associated with the third dimension. In general use of superfluous dimensions not used to display the data of interest is discouraged for charts in general, not only for pie charts.
* '''Polar area diagram:''' The polar area diagram is similar to a usual pie chart, except that the sectors are each of an equal angle and differ rather in how far each sector extends from the centre of the circle, enabling multiple comparisons on one diagram.
* '''Multi-Level Pie Chart:''' Such charts are used for representing hierarchical data. The hierarchical structure of data is depicted by means of concentric circles.

----

=== Criticism on the Pie Chart ===

[[image:PiechartsAndBars.png| thumb | Comparison of Pie Chart vs. Bar Chart]]
While pie charts are common in business and journalism, they are uncommon in scientific literature. Pie charts can be an effective way of displaying information in some cases, in particular if the intent is to compare the size of a slice with the whole pie, rather than comparing the slices among them. It has been also shown that comparison by angle was less accurate than comparison by length. Also a comparison by angle (as in pie charts) was shown to be perceived less accurate than comparison by length. The Usage of bars instead of slices improves the capability to compare the different segments of data [Wikipedia, 2008].
----

=== Other Forms of Charts ===
Among pie charts, used to display percentages, other forms of charts can be used for different purposes [French, 2008]:

* '''Column Charts''' – are used to show comparisons between items of data. A column in the chart represents the value of one item of data.
* '''Bar Charts''' - are very similar to column charts, except they run horizontally on the page instead of vertically like column charts.
* '''Line Charts''' – are used to show trends over time. Each line in the graph shows the changes in the value of one item of data.

----

=== References ===
*[Concordia University, 1999] Unknown, Pie Chart. Last Modified at: 1999. Retrieved at: November 4, 2008 http://web2.concordia.ca/Quality/tools/21piechart.pdf
*[French, 2008] Ted French. Chart. http://spreadsheets.about.com/od/c/g/chart_def.htm
*[Wikipedia, 2008] Wikipedia. Pie chart. Created at: June 15, 2004. Retrieved at: November 2008. http://en.wikipedia.org/wiki/Pie_chart
*[Statistics Canada, 2008] Statistics Canada. Pie charts. Retrieved at: November 19, 2008. http://www.statcan.ca/english/edu/power/ch9/piecharts/pie.htm

Teaching:TUW - UE InfoVis WS 2006/07 - Gruppe 03 - Aufgabe 1 - Data Density

2009-11-06T17:16:15Z

UE-InfoVis0910 0625100: struktur

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 1 | Zurueck zu Aufgabe 1]]

== Data Density ==

=== Definition ===
{{Quotation|Number of Data Points means the number of discrete data values represented on screen at an instant. |[Barth, 1997]}}

=== Overview ===
The cognitive complexity of an image can be measured by data density (which can be measured by the number of points in a graph) [Dal Sasso Freitas et al., 2002].
 
So data density provides information about how many information elements can be displayed on a defined panel. Therefore you need numerical values which relate the number of maximal at the same time presentable information elements to a display panel [Edlinger, 2006].

=== Charts and Graphics ===
In general, Tufte assumes that the greater amount of data represented per square centimeter of print, the more effective the resulting representation [Barth, 1997].
Hence he discussed in his work "The Visual Display of Quantitative Information", which is a milestone in the theory of graph design, principles of graph design. One of them is: Try to maximize the data density and the size of the data matrix, within reason. Furthermore as the volume of data increases, data measures must shrink and the graphics can be shrunk way down [Tufte, 1999].
 
So graphics are at their best when they represents very dense and rich datasets because the human eye/brain can select, filter, edit, group, structure, highlight, focus, blend, outline, cluster, itemize, winnow, sort, abstract, smooth, isolate, idealize, summarize, etc. Give people the data so they can exercise their full powers -- don't limit them.
Note that low data densities on computer displays force us to view information sequentially, rather than spatially, which is bad for comprehension [Smith, 2005].
 

Example for data densities include [Smith, 2005]:
* 110,000 numbers/sq-inch for an astronomical graph. This is the maximum known density for a graph to compare. For most scientific journals we get about 50-200 numbers/sq-inch.
* 150 Mbits = human eye
:8 Mbits = typical computer screen
:25 Mbits = color slide
:150 Mbits = large foldout map
:28,000 Characters = Reference book
:18,000 Characters = phone book
:15,000 Characters = non-fiction

=== Example ===
To better understand this term, we show two graphs and compute their data density. Consider the result of a survey in which the gender, height and weight were recorded for 92 students. The charts are 5.6cm by 7.4cm, an area of 41.4cm2 [Hunt and Tyrrell, 1995].

[[Image:Data1.10.gif]]
[[Image:Data1.11.gif]]

Above you see a bar graph showing the breakdown into males and females.
According to the definition you have 2 (female and male) areas with 2 kind of information (gender and number of students), what makes 4 data points. By dividing this over the size of its area, you get the data density of this graph [Barth, 1997].

data density = 4 / 41.4 = 0.1 (to 1 dp)

The computation of the second example works similar to the first one. The second graph shows a labeled XY-chart, which additionally shows the relationship between height and weight of the students. As a result you have 3 kind of information on 92 areas, what results 276 data points [Barth, 1997].

data density = 276 / 41.4 = 6.7 (to 1 dp)

'''Another Example:''' 50 information elements on a 200x200 display panel delivers
50/(200*200) = 0,00125 information elements/pixel
 
----

== References ==

[Barth, 1997] R. Barth. Metrics for effective information visualization. In ''Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97)'', pages 0–108, DC, USA, October 1997. IEEE Computer Society Washington

[Dal Sasso Freitas et al., 2002] Carla M. Dal Sasso Freitas, Paulo R. G. Luzzardi, Ricardo A. Cava, Marco A. A. Winckler, Marcelo S. Pimenta, Luciana P. Nedel. Evaluating Usability of Information Visualization Techniques. In ''Proceedings of 5th Symposium on Human Factors in Computer Systems (IHC)'', pages 10-11, Fortaleza, CE, 2002. Fortaleza:SBC

[Edlinger, 2006] Karl Edlinger, Informationsvisualisierung im Wissensmanagement – Eine Analyse unterschiedlicher Visualisierungstechniken auf ihre Eignung für das Wissensmanagement, Master's thesis, Fachhochschul-Studiengang Informationsberufe, Eisenstadt, 2006

[Hunt and Tyrrell, 1995] Neville Hunt and Sidney Tyrrell, Discovering Important Statistical Concepts Using SpreadSheets. Retrieved at: April 07, 2008. http://www.coventry.ac.uk/ec/research/discus/discus_home.html

[Smith, 2005] Waynes Smith. Graphics and Web Design Based on Edward Tufte's Principles. Created at: January 17, 2005. Retrieved at: October 29, 2006. http://www.washington.edu/computing/training/560/zz-tufte.html

[Tufte, 1999] Edward R. Tufte. The Visual Display of Quantitative Information. Created at: January 26, 1999. Retrieved at: October 29, 2006. http://ldt.stanford.edu/ldt1999/Students/mizuno/Portfolio/Work/reports/tufte/ed229c-tufte-outline.html

Teaching:TUW - UE InfoVis WS 2006/07 - Gruppe 03 - Aufgabe 1 - Data Density

2009-11-05T21:22:20Z

UE-InfoVis0910 0625100: line

== Data Density ==

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 1 | Zurueck zu Aufgabe 1]]

{{Quotation|Number of Data Points means the number of discrete data values represented on screen at an instant. |[Barth, 1997]}}

=== Charts and Graphs ===
The cognitive complexity of an image can be measured by data density (which can be measured by the number of points in a graph) [Dal Sasso Freitas et al., 2002].
 
So data density provides information about how many information elements can be displayed on a defined panel. Therefore you need numerical values which relate the number of maximal at the same time presentable information elements to a display panel [Edlinger, 2006].
 
'''Example:''' 50 information elements on a 200x200 display panel delivers
50/(200*200) = 0,00125 information elements/pixel
 
In general, Tufte assumes that the greater amount of data represented per square centimeter of print, the more effective the resulting representation [Barth, 1997].
Hence he discussed in his work "The Visual Display of Quantitative Information", which is a milestone in the theory of graph design, principles of graph design .One of them is: Try to maximise the data density and the size of the data matrix, within reason. Furthermore as the volume of data increases, data measures must shrink and the graphics can be shrunk way down [Tufte, 1999].
 
So graphics are at their best when they represents very dense and rich datasets because the human eye/brain can select, filter, edit, group, structure, highlight, focus, blend, outline, cluster, itemize, winnow, sort, abstract, smooth, isolate, idealize, summarize, etc. Give people the data so they can exercise their full powers -- don't limit them.
Note that low data densities on computer displays force us to view information sequentially, rather than spatially, which is bad for comprehension [Smith, 2005].
 

Example for data densities include [Smith, 2005]:
* 110,000 numbers/sq-inch for an astronomical graph. This is the maximum known density for a graph to compare. For most scientific journals we get about 50-200 numbers/sq-inch.
* 150 Mbits = human eye
:8 Mbits = typical computer screen
:25 Mbits = color slide
:150 Mbits = large foldout map
:28,000 Characters = Reference book
:18,000 Characters = phone book
:15,000 Characters = non-fiction

=== Example ===
To better understand this term, we show two graphs and compute their data density. Consider the result of a survey in which the gender, height and weight were recorded for 92 students. The charts are 5.6cm by 7.4cm, an area of 41.4cm2. [Hunt and Mashhoudy, 2002]

[[Image:Data1.10.gif]]
[[Image:Data1.11.gif]]

Above you see a bar graph showing the breakdown into males and females.
According to the definition you've 2 (female and male) areas with 2 kind of information (gender and number of students), what makes 4 data points. By deviding this over the size of its area, you get the data density of this graph. [Barth, 1997]

data density = 4 / 41.4 = 0.1 (to 1 dp)
[Hunt and Mashhoudy, 2002]

The computation of the second example works similiar to the first one. The second graph shows a labeled XY-chart, which additonaly shows the relationship between height and weight of the students. As a result you've 3 kind of information on 92 areas, what results 276 data points. [Barth, 1997]

data density = 276 / 41.4 = 6.7 (to 1 dp)
[Hunt and Mashhoudy, 2002]

----

== References ==

[Barth, 1997] R. Barth. Metrics for effective information visualization. In ''Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97)'', pages 0–108, DC, USA, October 1997. IEEE Computer Society Washington

[Dal Sasso Freitas et al., 2002] Carla M. Dal Sasso Freitas, Paulo R. G. Luzzardi, Ricardo A. Cava, Marco A. A. Winckler, Marcelo S. Pimenta, Luciana P. Nedel. Evaluating Usability of Information Visualization Techniques. In ''Proceedings of 5th Symposium on Human Factors in Computer Systems (IHC)'', pages 10-11, Fortaleza, CE, 2002. Fortaleza:SBC

[Edlinger, 2006] Karl Edlinger, Informationsvisualisierung im Wissensmanagement – Eine Analyse unterschiedlicher Visualisierungstechniken auf ihre Eignung für das Wissensmanagement, Master's thesis, Fachhochschul-Studiengang Informationsberufe, Eisenstadt, 2006

[Hunt and Mashhoudy, 2002] Neville Hunt and Housh Mashhoudy, Discovering Important Statistical Concepts Using SpreadSheets. Created at: January 29, 2002. Retrieved at: October 28, 2006. http://www.coventry.ac.uk/ec/research/discus/discus_home.html

[Smith, 2005] Waynes Smith. Graphics and Web Design Based on Edward Tufte's Principles. Created at: January 17, 2005. Retrieved at: October 29, 2006. http://www.washington.edu/computing/training/560/zz-tufte.html

[Tufte, 1999] Edward R. Tufte. The Visual Display of Quantitative Information. Created at: January 26, 1999. Retrieved at: October 29, 2006. http://ldt.stanford.edu/ldt1999/Students/mizuno/Portfolio/Work/reports/tufte/ed229c-tufte-outline.html

Teaching talk:TUW - UE InfoVis WS 2008/09 - Gruppe 07 - Aufgabe 1 - Pie Chart

2009-11-05T19:05:04Z

UE-InfoVis0910 0625100:

--[[User:UE-InfoVis0910 0625100|UE-InfoVis0910 0625100]] 20:04, 5 November 2009 (CET) 
zu lange sätze mit lückenfüllern habe ich gekürzt

der erste link in der referenzangabe ist wieder ein toter Link (würde ich daher wegkicken) 
eine defintion von pie charts ist genügend (finde ich) 
das beispiel ... weiß nicht ... könnte man weglassen (obsolent) .. referenzangabe fehlt auch

Teaching talk:TUW - UE InfoVis WS 2008/09 - Gruppe 07 - Aufgabe 1 - Pie Chart

2009-11-05T19:04:46Z

UE-InfoVis0910 0625100:

--[[User:UE-InfoVis0910 0625100|UE-InfoVis0910 0625100]] 20:04, 5 November 2009 (CET)
zu lange sätze mit lückenfüllern habe ich gekürzt

der erste link in der referenzangabe ist wieder ein toter Link (würde ich daher wegkicken) 
eine defintion von pie charts ist genügend (finde ich) 
das beispiel ... weiß nicht ... könnte man weglassen (obsolent) .. referenzangabe fehlt auch

Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 07 - Aufgabe 1 - Pie Chart

2009-11-05T19:03:08Z

UE-InfoVis0910 0625100: formulierung

== Pie Charts==

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 1 | Zurueck zu Aufgabe 1]]

=== Definition ===
{{Quotation | A '''pie chart''' (or a '''circle graph''') is a circular chart divided into sectors, illustrating relative magnitudes or frequencies. In a pie chart, the arc length of each sector (and consequently its central angle and area), is proportional to the quantity it represents. Together, the sectors create a full disk. It is named for its resemblance to a pie which has been sliced.| [Wikipedia, 2008]}}

----

===How to use it===
Pie Charts are used to show percentages. The circle provides a visual concept of the whole (100%). Despite its popularity, pie charts should be used sparingly for two reasons [Statistics Canada, 2008]:
 
* Use less than six components - otherwise, the resulting picture will be too complex to understand.
* Not useful when the values of each component are similar because it is difficult to see the differences between slice sizes.
 
To present certain values in a pie chart it is necessary to determine how many degrees represent this share of data in comparison to the whole circle. This calculation is done by developing the equation:

percent ÷ 100 x 360 degrees = the number of degrees

This ratio works because the total percent of the pie chart represents 100% and there are 360 degrees in a circle [Statistics Canada, 2008].
 
To construct a pie chart the following steps are necessary [Concordia University, 1999]:
* '''Determine the proportions:''' find the total value for the entire category being studied and calculate the percentage for each segment or part.
* '''Calculate degrees:''' convert the percentage values for each segment into degrees relative to the 360 degrees in the circle.
* '''Construct the chart:''' draw a circle and divide it into appropriately sized segments.
* '''Add labels and a title:''' label each segment or add a legend to identify the segments. Then clearly title the chart.

----

=== Variants of the Pie Chart ===

There are different variants of Pie Charts [Wikipedia, 2008]:
* '''Exploded Pie Chart:''' One ore more sectores are seperated from the rest, to highlight it.
* '''Perspective (3D) pie chart:''' Mainly for aesthetic reasons the pie chart is displayed in 3D. But the third dimension does not improve the reading of the data. On the contrary, these plots are difficult to interpret because of the distorted effect of perspective associated with the third dimension. In generell use of superfluous dimensions not used to display the data of interest is discouraged for charts in general, not only for pie charts.
* '''Polar area diagram:''' The polar area diagram is similar to a usual pie chart, except that the sectors are each of an equal angle and differ rather in how far each sector extends from the centre of the circle, enabling multiple comparisons on one diagram.
* '''Multi-Level Pie Chart:''' Such charts are used for representing hierarchical data. The hierarchical structure of data is depicted by means of concentric circles.

----

=== Criticism on the Pie Chart ===

[[image:PiechartsAndBars.png| thumb | Comparison of Pie Chart vs. Bar Chart]]
While pie charts are common in business and journalism, they are uncommon in scientific literature. Pie charts can be an effective way of displaying information in some cases, in particular if the intent is to compare the size of a slice with the whole pie, rather than comparing the slices among them. It has been also shown that comparison by angle was less accurate than comparison by length. Also a comparison by angle (as in pie charts) was shown to be percieved less accurate than comparison by length. The Usage of bars instead of slices improves the capability to compare the different segments of data [Wikipedia, 2008].

----

===Example===
[[image:pie_chart_example.jpg|picture]]
==== Data ====
A student's life.
Hours per week.
* '''Sleeping''' '''40%'''
* '''Partying''' '''15%'''
* '''Eating''' '''10%'''
* '''Slacking''' '''20%'''
* '''Working''' '''30%'''
* '''Studying''' '''20%'''

----
=== Other Forms of Charts ===
Among Pie Charts, used to display percentages, other forms of charts can be used for different purposes [French, 2008]:

* '''Column Charts''' – are used to show comparisons between items of data. A column in the chart represents the value of one item of data.
* '''Bar Charts''' - are very similar to column charts, except they run horizontally on the page instead of vertically like column charts.
* '''Line Charts''' – are used to show trends over time. Each line in the graph shows the changes in the value of one item of data.

----

=== References ===
*[Hull, 1998] Stephen Hull, BusinessObjects Glossary. Last Modified at: November 5, 1998. Retreived at: November 4, 2008 http://planning.ucsc.edu/IRPS/dwh/BOBGLOSS.HTM
*[Concordia University, 1999] Unknown, Pie Chart. Last Modified at: 1999. Retrieved at: November 4, 2008 http://web2.concordia.ca/Quality/tools/21piechart.pdf
*[French, 2008] Ted French. Chart. http://spreadsheets.about.com/od/c/g/chart_def.htm
*[Wikipedia, 2008] Wikipedia. Pie chart. Created at: June 15, 2004. Retrieved at: November 2008. http://en.wikipedia.org/wiki/Pie_chart
*[Statistics Canada, 2008] Statistics Canada. Pie charts. Retrieved at: November 19, 2008. http://www.statcan.ca/english/edu/power/ch9/piecharts/pie.htm

Teaching:TUW - UE InfoVis WS 2006/07 - Gruppe 03 - Aufgabe 1 - Data Density

2009-11-05T18:19:44Z

UE-InfoVis0910 0625100: quotation not necessary

== Data Density ==

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 1 | Zurueck zu Aufgabe 1]]

{{Quotation|Number of Data Points means the number of discrete data values represented on screen at an instant. |[Barth, 1997]}}

=== Charts and Graphs ===
The cognitive complexity of an image can be measured by data density (which can be measured by the number of points in a graph) [Dal Sasso Freitas et al., 2002].
 
So data density provides information about how many information elements can be displayed on a defined panel. Therefore you need numerical values which relate the number of maximal at the same time presentable information elements to a display panel [Edlinger, 2006].
 
'''Example:''' 50 information elements on a 200x200 display panel delivers
50/(200*200) = 0,00125 information elements/pixel
 
In general, Tufte assumes that the greater amount of data represented per square centimeter of print, the more effective the resulting representation [Barth, 1997].
Hence he discussed in his work "The Visual Display of Quantitative Information", which is a milestone in the theory of graph design, principles of graph design .One of them is: Try to maximise the data density and the size of the data matrix, within reason. Furthermore as the volume of data increases, data measures must shrink and the graphics can be shrunk way down [Tufte, 1999].
 
So graphics are at their best when they represents very dense and rich datasets because the human eye/brain can select, filter, edit, group, structure, highlight, focus, blend, outline, cluster, itemize, winnow, sort, abstract, smooth, isolate, idealize, summarize, etc. Give people the data so they can exercise their full powers -- don't limit them.
Note that low data densities on computer displays force us to view information sequentially, rather than spatially, which is bad for comprehension [Smith, 2005].
 

Example for data densities include [Smith, 2005]:
* 110,000 numbers/sq-inch for an astronomical graph. This is the maximum known density for a graph to compare. For most scientific journals we get about 50-200 numbers/sq-inch.
* 150 Mbits = human eye
:8 Mbits = typical computer screen
:25 Mbits = color slide
:150 Mbits = large foldout map
:28,000 Characters = Reference book
:18,000 Characters = phone book
:15,000 Characters = non-fiction

=== Example ===
To better understand this term, we show two graphs and compute their data density. Consider the result of a survey in which the gender, height and weight were recorded for 92 students. The charts are 5.6cm by 7.4cm, an area of 41.4cm2. [Hunt and Mashhoudy, 2002]

[[Image:Data1.10.gif]]
[[Image:Data1.11.gif]]

Above you see a bar graph showing the breakdown into males and females.
According to the definition you've 2 (female and male) areas with 2 kind of information (gender and number of students), what makes 4 data points. By deviding this over the size of its area, you get the data density of this graph. [Barth, 1997]

data density = 4 / 41.4 = 0.1 (to 1 dp)
[Hunt and Mashhoudy, 2002]

The computation of the second example works similiar to the first one. The second graph shows a labeled XY-chart, which additonaly shows the relationship between height and weight of the students. As a result you've 3 kind of information on 92 areas, what results 276 data points. [Barth, 1997]

data density = 276 / 41.4 = 6.7 (to 1 dp)
[Hunt and Mashhoudy, 2002]

== References ==

[Barth, 1997] R. Barth. Metrics for effective information visualization. In ''Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97)'', pages 0–108, DC, USA, October 1997. IEEE Computer Society Washington

[Dal Sasso Freitas et al., 2002] Carla M. Dal Sasso Freitas, Paulo R. G. Luzzardi, Ricardo A. Cava, Marco A. A. Winckler, Marcelo S. Pimenta, Luciana P. Nedel. Evaluating Usability of Information Visualization Techniques. In ''Proceedings of 5th Symposium on Human Factors in Computer Systems (IHC)'', pages 10-11, Fortaleza, CE, 2002. Fortaleza:SBC

[Edlinger, 2006] Karl Edlinger, Informationsvisualisierung im Wissensmanagement – Eine Analyse unterschiedlicher Visualisierungstechniken auf ihre Eignung für das Wissensmanagement, Master's thesis, Fachhochschul-Studiengang Informationsberufe, Eisenstadt, 2006

[Hunt and Mashhoudy, 2002] Neville Hunt and Housh Mashhoudy, Discovering Important Statistical Concepts Using SpreadSheets. Created at: January 29, 2002. Retrieved at: October 28, 2006. http://www.coventry.ac.uk/ec/research/discus/discus_home.html

[Smith, 2005] Waynes Smith. Graphics and Web Design Based on Edward Tufte's Principles. Created at: January 17, 2005. Retrieved at: October 29, 2006. http://www.washington.edu/computing/training/560/zz-tufte.html

[Tufte, 1999] Edward R. Tufte. The Visual Display of Quantitative Information. Created at: January 26, 1999. Retrieved at: October 29, 2006. http://ldt.stanford.edu/ldt1999/Students/mizuno/Portfolio/Work/reports/tufte/ed229c-tufte-outline.html

Teaching:TUW - UE InfoVis WS 2006/07 - Gruppe 03 - Aufgabe 1 - Data Density

2009-11-05T18:17:54Z

UE-InfoVis0910 0625100: sections changed

== Data Density ==

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 1 | Zurueck zu Aufgabe 1]]

{{Quotation|Number of Data Points means the number of discrete data values represented on screen at an instant. |[Barth, 1997]}}

{{Quotation|Data Density means the number of data points / number of pixels in the display where number of pixels does not include the pixels in the window borders, menus, etc..|[Barth, 1997]}}

=== Charts and Graphs ===
 
The cognitive complexity of an image can be measured by data density (which can be measured by the number of points in a graph) [Dal Sasso Freitas et al., 2002].
 
So data density provides information about how many information elements can be displayed on a defined panel. Therefore you need numerical values which relate the number of maximal at the same time presentable information elements to a display panel [Edlinger, 2006].
 
'''Example:''' 50 information elements on a 200x200 display panel delivers
50/(200*200) = 0,00125 information elements/pixel
 
In general, Tufte assumes that the greater amount of data represented per square centimeter of print, the more effective the resulting representation [Barth, 1997].
Hence he discussed in his work "The Visual Display of Quantitative Information", which is a milestone in the theory of graph design, principles of graph design .One of them is: Try to maximise the data density and the size of the data matrix, within reason. Furthermore as the volume of data increases, data measures must shrink and the graphics can be shrunk way down [Tufte, 1999].
 
So graphics are at their best when they represents very dense and rich datasets because the human eye/brain can select, filter, edit, group, structure, highlight, focus, blend, outline, cluster, itemize, winnow, sort, abstract, smooth, isolate, idealize, summarize, etc. Give people the data so they can exercise their full powers -- don't limit them.
Note that low data densities on computer displays force us to view information sequentially, rather than spatially, which is bad for comprehension [Smith, 2005].
 

Example for data densities include [Smith, 2005]:
* 110,000 numbers/sq-inch for an astronomical graph. This is the maximum known density for a graph to compare. For most scientific journals we get about 50-200 numbers/sq-inch.
* 150 Mbits = human eye
:8 Mbits = typical computer screen
:25 Mbits = color slide
:150 Mbits = large foldout map
:28,000 Characters = Reference book
:18,000 Characters = phone book
:15,000 Characters = non-fiction

=== Example ===
To better understand this term, we show two graphs and compute their data density. Consider the result of a survey in which the gender, height and weight were recorded for 92 students. The charts are 5.6cm by 7.4cm, an area of 41.4cm2. [Hunt and Mashhoudy, 2002]

[[Image:Data1.10.gif]]
[[Image:Data1.11.gif]]

Above you see a bar graph showing the breakdown into males and females.
According to the definition you've 2 (female and male) areas with 2 kind of information (gender and number of students), what makes 4 data points. By deviding this over the size of its area, you get the data density of this graph. [Barth, 1997]

data density = 4 / 41.4 = 0.1 (to 1 dp)
[Hunt and Mashhoudy, 2002]

The computation of the second example works similiar to the first one. The second graph shows a labeled XY-chart, which additonaly shows the relationship between height and weight of the students. As a result you've 3 kind of information on 92 areas, what results 276 data points. [Barth, 1997]

data density = 276 / 41.4 = 6.7 (to 1 dp)
[Hunt and Mashhoudy, 2002]

== References ==

[Barth, 1997] R. Barth. Metrics for effective information visualization. In ''Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97)'', pages 0–108, DC, USA, October 1997. IEEE Computer Society Washington

[Dal Sasso Freitas et al., 2002] Carla M. Dal Sasso Freitas, Paulo R. G. Luzzardi, Ricardo A. Cava, Marco A. A. Winckler, Marcelo S. Pimenta, Luciana P. Nedel. Evaluating Usability of Information Visualization Techniques. In ''Proceedings of 5th Symposium on Human Factors in Computer Systems (IHC)'', pages 10-11, Fortaleza, CE, 2002. Fortaleza:SBC

[Edlinger, 2006] Karl Edlinger, Informationsvisualisierung im Wissensmanagement – Eine Analyse unterschiedlicher Visualisierungstechniken auf ihre Eignung für das Wissensmanagement, Master's thesis, Fachhochschul-Studiengang Informationsberufe, Eisenstadt, 2006

[Hunt and Mashhoudy, 2002] Neville Hunt and Housh Mashhoudy, Discovering Important Statistical Concepts Using SpreadSheets. Created at: January 29, 2002. Retrieved at: October 28, 2006. http://www.coventry.ac.uk/ec/research/discus/discus_home.html

[Smith, 2005] Waynes Smith. Graphics and Web Design Based on Edward Tufte's Principles. Created at: January 17, 2005. Retrieved at: October 29, 2006. http://www.washington.edu/computing/training/560/zz-tufte.html

[Tufte, 1999] Edward R. Tufte. The Visual Display of Quantitative Information. Created at: January 26, 1999. Retrieved at: October 29, 2006. http://ldt.stanford.edu/ldt1999/Students/mizuno/Portfolio/Work/reports/tufte/ed229c-tufte-outline.html

Teaching talk:TUW - UE InfoVis WS 2006/07 - Gruppe 03 - Aufgabe 1 - Data Density

2009-11-05T18:12:25Z

UE-InfoVis0910 0625100:

--[[User:UE-InfoVis0910 0625100|UE-InfoVis0910 0625100]] 19:02, 5 November 2009 (CET)

Bei "Example for data densities include" sind es eigentlich nur 2 Punkte, wie in der Referenz.
Die Datapoints sind bereits im Text beschrieben und daher habe ich sie weggelassen und die Formel herausgehoben

--[[User:UE-InfoVis0910 0625100|UE-InfoVis0910 0625100]] 18:48, 5 November 2009 (CET)

Ich habe ganz oben im Zitat die Referenz von Brath auf Barth geändert. Der Link auf die Seite von Neville Hunt war fehlerhaft. Der passt jetzt auch.

Teaching:TUW - UE InfoVis WS 2006/07 - Gruppe 03 - Aufgabe 1 - Data Density

2009-11-05T18:11:27Z

UE-InfoVis0910 0625100: number of datapoints deleted

== Data Density ==

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 1 | Zurueck zu Aufgabe 1]]

{{Quotation|Number of Data Points means the number of discrete data values represented on screen at an instant. |[Barth, 1997]}}

{{Quotation|Data Density means the number of data points / number of pixels in the display where number of pixels does not include the pixels in the window borders, menus, etc..|[Barth, 1997]}}

== Charts and Graphs ==
 
The cognitive complexity of an image can be measured by data density (which can be measured by the number of points in a graph) [Dal Sasso Freitas et al., 2002].
 
So data density provides information about how many information elements can be displayed on a defined panel. Therefore you need numerical values which relate the number of maximal at the same time presentable information elements to a display panel [Edlinger, 2006].
 
'''Example:''' 50 information elements on a 200x200 display panel delivers
50/(200*200) = 0,00125 information elements/pixel
 
In general, Tufte assumes that the greater amount of data represented per square centimeter of print, the more effective the resulting representation [Barth, 1997].
Hence he discussed in his work "The Visual Display of Quantitative Information", which is a milestone in the theory of graph design, principles of graph design .One of them is: Try to maximise the data density and the size of the data matrix, within reason. Furthermore as the volume of data increases, data measures must shrink and the graphics can be shrunk way down [Tufte, 1999].
 
So graphics are at their best when they represents very dense and rich datasets because the human eye/brain can select, filter, edit, group, structure, highlight, focus, blend, outline, cluster, itemize, winnow, sort, abstract, smooth, isolate, idealize, summarize, etc. Give people the data so they can exercise their full powers -- don't limit them.
Note that low data densities on computer displays force us to view information sequentially, rather than spatially, which is bad for comprehension [Smith, 2005].
 

Example for data densities include [Smith, 2005]:
* 110,000 numbers/sq-inch for an astronomical graph. This is the maximum known density for a graph to compare. For most scientific journals we get about 50-200 numbers/sq-inch.
* 150 Mbits = human eye
:8 Mbits = typical computer screen
:25 Mbits = color slide
:150 Mbits = large foldout map
:28,000 Characters = Reference book
:18,000 Characters = phone book
:15,000 Characters = non-fiction

== Example ==
To better understand this term, we show two graphs and compute their data density. Consider the result of a survey in which the gender, height and weight were recorded for 92 students. The charts are 5.6cm by 7.4cm, an area of 41.4cm2. [Hunt and Mashhoudy, 2002]

[[Image:Data1.10.gif]]
[[Image:Data1.11.gif]]

Above you see a bar graph showing the breakdown into males and females.
According to the definition you've 2 (female and male) areas with 2 kind of information (gender and number of students), what makes 4 data points. By deviding this over the size of its area, you get the data density of this graph. [Barth, 1997]

data density = 4 / 41.4 = 0.1 (to 1 dp)
[Hunt and Mashhoudy, 2002]

The computation of the second example works similiar to the first one. The second graph shows a labeled XY-chart, which additonaly shows the relationship between height and weight of the students. As a result you've 3 kind of information on 92 areas, what results 276 data points. [Barth, 1997]

data density = 276 / 41.4 = 6.7 (to 1 dp)
[Hunt and Mashhoudy, 2002]

== References ==

[Barth, 1997] R. Barth. Metrics for effective information visualization. In ''Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97)'', pages 0–108, DC, USA, October 1997. IEEE Computer Society Washington

[Dal Sasso Freitas et al., 2002] Carla M. Dal Sasso Freitas, Paulo R. G. Luzzardi, Ricardo A. Cava, Marco A. A. Winckler, Marcelo S. Pimenta, Luciana P. Nedel. Evaluating Usability of Information Visualization Techniques. In ''Proceedings of 5th Symposium on Human Factors in Computer Systems (IHC)'', pages 10-11, Fortaleza, CE, 2002. Fortaleza:SBC

[Edlinger, 2006] Karl Edlinger, Informationsvisualisierung im Wissensmanagement – Eine Analyse unterschiedlicher Visualisierungstechniken auf ihre Eignung für das Wissensmanagement, Master's thesis, Fachhochschul-Studiengang Informationsberufe, Eisenstadt, 2006

[Hunt and Mashhoudy, 2002] Neville Hunt and Housh Mashhoudy, Discovering Important Statistical Concepts Using SpreadSheets. Created at: January 29, 2002. Retrieved at: October 28, 2006. http://www.coventry.ac.uk/ec/research/discus/discus_home.html

[Smith, 2005] Waynes Smith. Graphics and Web Design Based on Edward Tufte's Principles. Created at: January 17, 2005. Retrieved at: October 29, 2006. http://www.washington.edu/computing/training/560/zz-tufte.html

[Tufte, 1999] Edward R. Tufte. The Visual Display of Quantitative Information. Created at: January 26, 1999. Retrieved at: October 29, 2006. http://ldt.stanford.edu/ldt1999/Students/mizuno/Portfolio/Work/reports/tufte/ed229c-tufte-outline.html

Teaching talk:TUW - UE InfoVis WS 2006/07 - Gruppe 03 - Aufgabe 1 - Data Density

2009-11-05T18:02:48Z

UE-InfoVis0910 0625100:

--[[User:UE-InfoVis0910 0625100|UE-InfoVis0910 0625100]] 19:02, 5 November 2009 (CET)

Bei "Example for data densities include" sind es eigentlich nur 2 Punkte, wie in der Referenz.

--[[User:UE-InfoVis0910 0625100|UE-InfoVis0910 0625100]] 18:48, 5 November 2009 (CET)

Ich habe ganz oben im Zitat die Referenz von Brath auf Barth geändert. Der Link auf die Seite von Neville Hunt war fehlerhaft. Der passt jetzt auch.

Teaching:TUW - UE InfoVis WS 2006/07 - Gruppe 03 - Aufgabe 1 - Data Density

2009-11-05T18:01:01Z

UE-InfoVis0910 0625100:

== Data Density ==

[[Teaching:TUW - UE InfoVis WS 2009/10 - Gruppe 09 - Aufgabe 1 | Zurueck zu Aufgabe 1]]

{{Quotation|Number of Data Points means the number of discrete data values represented on screen at an instant. |[Barth, 1997]}}

{{Quotation|Data Density means the number of data points / number of pixels in the display where number of pixels does not include the pixels in the window borders, menus, etc..|[Barth, 1997]}}

== Charts and Graphs ==
 
The cognitive complexity of an image can be measured by data density (which can be measured by the number of points in a graph) [Dal Sasso Freitas et al., 2002].
 
So data density provides information about how many information elements can be displayed on a defined panel. Therefore you need numerical values which relate the number of maximal at the same time presentable information elements to a display panel [Edlinger, 2006].
 
'''Example:''' 50 information elements on a 200x200 display panel delivers
50/(200*200) = 0,00125 information elements/pixel
 
In general, Tufte assumes that the greater amount of data represented per square centimeter of print, the more effective the resulting representation [Barth, 1997].
Hence he discussed in his work "The Visual Display of Quantitative Information", which is a milestone in the theory of graph design, principles of graph design .One of them is: Try to maximise the data density and the size of the data matrix, within reason. Furthermore as the volume of data increases, data measures must shrink and the graphics can be shrunk way down [Tufte, 1999].
 
So graphics are at their best when they represents very dense and rich datasets because the human eye/brain can select, filter, edit, group, structure, highlight, focus, blend, outline, cluster, itemize, winnow, sort, abstract, smooth, isolate, idealize, summarize, etc. Give people the data so they can exercise their full powers -- don't limit them.
Note that low data densities on computer displays force us to view information sequentially, rather than spatially, which is bad for comprehension [Smith, 2005].
 

Example for data densities include [Smith, 2005]:
* 110,000 numbers/sq-inch for an astronomical graph. This is the maximum known density for a graph to compare. For most scientific journals we get about 50-200 numbers/sq-inch.
* 150 Mbits = human eye
:8 Mbits = typical computer screen
:25 Mbits = color slide
:150 Mbits = large foldout map
:28,000 Characters = Reference book
:18,000 Characters = phone book
:15,000 Characters = non-fiction

== Example ==
To better understand this term, we show two graphs and compute their data density. Consider the result of a survey in which the gender, height and weight were recorded for 92 students. The charts are 5.6cm by 7.4cm, an area of 41.4cm2. [Hunt and Mashhoudy, 2002]

[[Image:Data1.10.gif]]
[[Image:Data1.11.gif]]

Above you see a bar graph showing the breakdown into males and females.
According to the definition you've 2 (female and male) areas with 2 kind of information (gender and number of students), what makes 4 data points. By deviding this over the size of its area, you get the data density of this graph. [Barth, 1997]

number of data points = 4

data density = 4 / 41.4 = 0.1 (to 1 dp)
[Hunt and Mashhoudy, 2002]

The computation of the second example works similiar to the first one. The second graph shows a labeled XY-chart, which additonaly shows the relationship between height and weight of the students. As a result you've 3 kind of information on 92 areas, what results 276 data points. [Barth, 1997]

number of data points = 92 x 3 = 276

data density = 276 / 41.4 = 6.7 (to 1 dp)
[Hunt and Mashhoudy, 2002]

== References ==

[Barth, 1997] R. Barth. Metrics for effective information visualization. In ''Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97)'', pages 0–108, DC, USA, October 1997. IEEE Computer Society Washington

[Dal Sasso Freitas et al., 2002] Carla M. Dal Sasso Freitas, Paulo R. G. Luzzardi, Ricardo A. Cava, Marco A. A. Winckler, Marcelo S. Pimenta, Luciana P. Nedel. Evaluating Usability of Information Visualization Techniques. In ''Proceedings of 5th Symposium on Human Factors in Computer Systems (IHC)'', pages 10-11, Fortaleza, CE, 2002. Fortaleza:SBC

[Edlinger, 2006] Karl Edlinger, Informationsvisualisierung im Wissensmanagement – Eine Analyse unterschiedlicher Visualisierungstechniken auf ihre Eignung für das Wissensmanagement, Master's thesis, Fachhochschul-Studiengang Informationsberufe, Eisenstadt, 2006

[Hunt and Mashhoudy, 2002] Neville Hunt and Housh Mashhoudy, Discovering Important Statistical Concepts Using SpreadSheets. Created at: January 29, 2002. Retrieved at: October 28, 2006. http://www.coventry.ac.uk/ec/research/discus/discus_home.html

[Smith, 2005] Waynes Smith. Graphics and Web Design Based on Edward Tufte's Principles. Created at: January 17, 2005. Retrieved at: October 29, 2006. http://www.washington.edu/computing/training/560/zz-tufte.html

[Tufte, 1999] Edward R. Tufte. The Visual Display of Quantitative Information. Created at: January 26, 1999. Retrieved at: October 29, 2006. http://ldt.stanford.edu/ldt1999/Students/mizuno/Portfolio/Work/reports/tufte/ed229c-tufte-outline.html

Teaching talk:TUW - UE InfoVis WS 2006/07 - Gruppe 03 - Aufgabe 1 - Data Density

2009-11-05T17:48:03Z

UE-InfoVis0910 0625100:

--[[User:UE-InfoVis0910 0625100|UE-InfoVis0910 0625100]] 18:48, 5 November 2009 (CET)

Ich habe ganz oben im Zitat die Referenz von Brath auf Barth geändert. Der Link auf die Seite von Neville Hunt war fehlerhaft. Der passt jetzt auch.

Teaching talk:TUW - UE InfoVis WS 2006/07 - Gruppe 03 - Aufgabe 1 - Data Density

2009-11-05T17:36:08Z

UE-InfoVis0910 0625100: New page: Ich habe ganz oben im Zitat die Referenz von Brath auf Barth geändert. Der Link auf die Seite von Neville Hunt war fehlerhaft. Der passt jetzt auch.

Ich habe ganz oben im Zitat die Referenz von Brath auf Barth geändert. Der Link auf die Seite von Neville Hunt war fehlerhaft. Der passt jetzt auch.

User talk:UE-InfoVis0910 0625100

2009-11-05T17:34:37Z

UE-InfoVis0910 0625100: New page: Ich habe ganz oben im Zitat die Referenz von Brath auf Barth geändert. Der Link auf die Seite von Neville Hunt war fehlerhaft. Der passt jetzt auch.

Ich habe ganz oben im Zitat die Referenz von Brath auf Barth geändert. Der Link auf die Seite von Neville Hunt war fehlerhaft. Der passt jetzt auch.