https://infovis-wiki.net/w/api.php?action=feedcontributions&feedformat=atom&user=UE-InfoVis09-04InfoVis:Wiki - User contributions [en]2026-04-21T12:51:56ZUser contributionsMediaWiki 1.45.3https://infovis-wiki.net/w/index.php?title=Visual_Exploration_of_Multivariate_Graphs_by_Roll-Up_and_Selection&diff=21439Visual Exploration of Multivariate Graphs by Roll-Up and Selection2009-05-26T10:01:43Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:Wat_pivotgraph_overview.jpg|Rolled-up example diagram done by PivotGraph]]<br>Multivariate diagramm rolled up in two dimensions [Wattenberg, 2006]<br />
<br />
[[Wattenberg, Martin|Martin Wattenberg]] [Wattenberg, 2006] described in his paper [http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs] how Multivariate Graphs can be easily analyzed by rolling-up on certain dimensions. The paper focuses on a software tool called PivotGraph (unfortunately not available) but describes a strategy that could also be used in other tools. <br />
<br />
{{Definition|'''Multivariate Graphs''' are multi-dimensional: Each node in a graph is associated with several attributes. Common examples are social networks where the nodes might contain information about gender, age etc. or Markov chains where each node has a certain state. The paper mentioned above (as well as the software tool PivotGraph) focuses on graphs with discrete categorical dimensions in the nodes.<br />
<br>[Wattenberg, 2006]}}<br />
<br />
<br />
== Multivariate graphs - common approach ==<br />
<br />
Two visualizations of multivariate graphs are very popular: "Node-and-link diagrams" and matrix views. "Node-and-link diagrams" represent a network topography, additional information may be coded by labeling and coloring nodes, matrix views (normally only 2D) create a main-matrix of one characteristic in which the sub-characteristic is repeated. <br />
<br />
== Problems in analyzing multivariate graphs ==<br />
<br />
Both visualizations - node-and-link diagram and matrix diagram allow only poor analysis of the information contained in the nodes. Easy questions like "How many men are in the network?" may require the analysist to count every node. <br />
<br />
[[Image:Wat_pivotgraph_roll-up.jpg|thumb|Rolling up a network diagram]]<br />
== Solution: Roll-up on one (two) dimension(s) ==<br />
<br />
<br />
The main simplification in PivotGraph is to roll a graph up in any dimension(s): Replace all nodes with the same value in these dimensions with a node representing the amount of nodes by its size. Aggregate the connections in the same way. <br />
<br />
This way you can select up to two dimensions that form a grid, e.g. gender and company. Instead of the large graph, you receive a simpler graph showing the aggregated connections between nodes that correspond to a certain gender and a certain company.<br />
<br />
[[Image:Wat_pivotgraph_select.jpg|thumb|Selecting along a node attribute in a social network]]<br />
== Solution: Selection ==<br />
<br />
As addition to roll-up - parts of the diagram can be selected, e.g. all nodes representing females. <br />
<br />
== Considerations ==<br />
<br />
{{Quotation|Although the basic idea [...] is quite simple, it turns out there are a number of subtile challenges that need to be addressed for the visualization to remain legible.| [Wattenberg, 2006]}} <br />
<br />
For optimal understanding, the size of the nodes reflects the amount of aggregated data, just as the thickness of the connections. The nodes may be colored according any other attribute, but the color of the lines should be used to indicate ratio of the weight (connections per node) . <br />
<br />
Although, when using a straight grid layout as PivotGraph does, the connections should not be straight to avoid overlapping. Slightly bent arrows avoid occlusion problems. <br />
<br />
[[Image:Wat_pivotgraph_singledim.jpg|thumb|Rolling up in one dimensions leads to a one-axis graph]]<br />
<br />
The application allows the user also to roll-up in only one dimension. This leads to a graph with just one axis, nevertheless this layout can contain important information, e.g. the communication between several locations in a company. <br />
<br />
An important part of the analysis is the user-interaction. The user may chose and the dimensions to roll up at any point, the diagram is automatically updated. User testing has shown, that this transition has to smoothly interpolate between the graphs, not only calculating the straight interpolation but maybe also intermediate graphs and displaying the transitions of the most important nodes and connections. <br />
<br />
Wattenberg describes in his paper three user testings in which all user responded very positive on the transitions between different graphs. <br />
<br />
[[Image:Wat_pivotgraph_ui.jpg|thumb|User Interface of PivotGraph]]<br />
== PivotGraph user interface ==<br />
The user interface is quite simple and basic to operate. The main window displays the current scatterplot and the dimensions, the right side allows the user to change the current view by rolling-up on attributes or selecting specific attribute-values. Nodes display additional information on mouse-over. <br />
<br />
== Advantages and disadvantages ==<br />
[[Image:pgnl.png|250px|Node-and-Link Diagram]] [[Image:pgmatrix.png|250px|Matrix View]] [[Image:pgpg.png|150px|Multivariate Graph]]<br><br />
The three figures above all represent the very same dataset, from left to right: Node-and-link diagram, matrix view and a multivariate graph generated by the PivotGraph application. Matrix views tend to offer the advantage of a comprehensive overview of all individual connections over node-and-link diagrams. However, to the unexperienced user they might happen to hide some information, as due to the emphasis on the first sort dimension (namely "gender") some connections can seem obscure. Therefore, the multivariate graph view is to be preferred when inspecting relations on two dimensions at once. <br />
<br />
The multivariate graph technology also comes with some disadvantages: Roll-up and selection transformations might not allow certain aspects of graph topolgy to be preserved: Acyclic graphs might become cyclic, disconnected graphs might become connected for instance. Therefore, matrix views might be more suitable for experienced users, multivariate graphs on the other hand might prove to be more readable to an unexperienced audience.<br />
<br />
== Limitations and future work ==<br />
<br />
The tool has some limitations that must be taken into consideration. First of all, the visualization is (except for node-coloring) limited to 2D. An extension to 3D would be possible, but this might cause severe occlusion problems and destroy the simplicity of the visualization. <br />
<br />
Another limitation is that the technique works only on discrete-valued dimensions. Continuous values are more difficult to aggregate, this could lead to a large amount of connections. <br />
<br />
A last limitation that may be addressed in future (just like the continuous data) is the representation of multivariate edges. A similar approach could be used to aggregate edges that contain additional information, however these graphs are less common in practice than graphs with multivariate nodes. <br />
<br />
<br />
== References ==<br />
[http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs]<br />
<br />
[[Category: Techniques]]<br />
[[Category: Interaction_Techniques]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Visual_Exploration_of_Multivariate_Graphs_by_Roll-Up_and_Selection&diff=21438Visual Exploration of Multivariate Graphs by Roll-Up and Selection2009-05-26T09:57:37Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:Wat_pivotgraph_overview.jpg|Rolled-up example diagram done by PivotGraph]]<br>Multivariate diagramm rolled up in two dimensions [Wattenberg, 2006]<br />
<br />
[[Wattenberg, Martin|Martin Wattenberg]] [Wattenberg, 2006] described in his paper [http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs] how Multivariate Graphs can be easily analyzed by rolling-up on certain dimensions. The paper focuses on a software tool called PivotGraph (unfortunately not available) but describes a strategy that could also be used in other tools. <br />
<br />
{{Definition|'''Multivariate Graphs''' are multi-dimensional: Each node in a graph is associated with several attributes. Common examples are social networks where the nodes might contain information about gender, age etc. or Markov chains where each node has a certain state. The paper mentioned above (as well as the software tool PivotGraph) focuses on graphs with discrete categorical dimensions in the nodes.<br />
<br>[Wattenberg, 2006]}}<br />
<br />
<br />
== Multivariate graphs - common approach ==<br />
<br />
Two visualizations of multivariate graphs are very popular: "Node-and-link diagrams" and matrix views. "Node-and-link diagrams" represent a network topography, additional information may be coded by labeling and coloring nodes, matrix views (normally only 2D) create a main-matrix of one characteristic in which the sub-characteristic is repeated. <br />
<br />
== Problems in analyzing multivariate graphs ==<br />
<br />
Both visualizations - node-and-link diagram and matrix diagram allow only poor analysis of the information contained in the nodes. Easy questions like "How many men are in the network?" may require the analysist to count every node. <br />
<br />
[[Image:Wat_pivotgraph_roll-up.jpg|thumb|Rolling up a network diagram]]<br />
== Solution: Roll-up on one (two) dimension(s) ==<br />
<br />
<br />
The main simplification in PivotGraph is to roll a graph up in any dimension(s): Replace all nodes with the same value in these dimensions with a node representing the amount of nodes by its size. Aggregate the connections in the same way. <br />
<br />
This way you can select up to two dimensions that form a grid, e.g. gender and company. Instead of the large graph, you receive a simpler graph showing the aggregated connections between nodes that correspond to a certain gender and a certain company.<br />
<br />
[[Image:Wat_pivotgraph_select.jpg|thumb|Selecting along a node attribute in a social network]]<br />
== Solution: Selection ==<br />
<br />
As addition to roll-up - parts of the diagram can be selected, e.g. all nodes representing females. <br />
<br />
== Considerations ==<br />
<br />
{{Quotation|Although the basic idea [...] is quite simple, it turns out there are a number of subtile challenges that need to be addressed for the visualization to remain legible.| [Wattenberg, 2006]}} <br />
<br />
For optimal understanding, the size of the nodes reflects the amount of aggregated data, just as the thickness of the connections. The nodes may be colored according any other attribute, but the color of the lines should be used to indicate ratio of the weight (connections per node) . <br />
<br />
Although, when using a straight grid layout as PivotGraph does, the connections should not be straight to avoid overlapping. Slightly bend arrows avoid occlusion problems. <br />
<br />
[[Image:Wat_pivotgraph_singledim.jpg|thumb|Rolling up in one dimensions leads to a one-axis graph]]<br />
<br />
The application allows the user also to roll-up in only one dimension. This leads to a graph with just one axis, nevertheless this layout can contain important information, e.g. the communication between several locations in a company. <br />
<br />
An important part of the analysis is the user-interaction. The user may chose and the dimensions to roll up at any point, the diagram is the automatically updated. User testing has shown, that this transition has to smoothly interpolate between the graphs, not only calculating the straight interpolation but maybe also intermediate graphs and displaying the transitions of the most important nodes and connections. <br />
<br />
Wattenberg describes in his paper three user testings in which all user responded very positive on the transitions between different graphs. <br />
<br />
[[Image:Wat_pivotgraph_ui.jpg|thumb|User Interface of PivotGraph]]<br />
== PivotGraph user interface ==<br />
The user interface is quite simple and basic to operate. The main window displays the current scatterplot and the dimensions, the right side allows the user to change the current view by rolling-up on attributes or selecting specific attribute-values. Nodes display additional information on mouse-over. <br />
<br />
== Advantages and disadvantages ==<br />
[[Image:pgnl.png|250px|Node-and-Link Diagram]] [[Image:pgmatrix.png|250px|Matrix View]] [[Image:pgpg.png|150px|Multivariate Graph]]<br><br />
The three figures above all represent the very same dataset, from left to right: Node-and-link diagram, matrix view and a multivariate graph generated by the PivotGraph application. Matrix views tend to offer the advantage of a comprehensive overview of all individual connections over node-and-link diagrams. However, to the unexperienced user they might happen to hide some information, as due to the emphasis on the first sort dimension (namely "gender") some connections can seem obscure. Therefore, the multivariate graph view is to be preferred when inspecting relations on two dimensions at once. <br />
<br />
The multivariate graph technology also comes with some disadvantages: Roll-up and selection transformations might not allow certain aspects of graph topolgy to be preserved: Acyclic graphs might become cyclic, disconnected graphs might become connected for instance. Therefore, matrix views might be more suitable for experienced users, multivariate graphs on the other hand might prove to be more readable to an unexperienced audience.<br />
<br />
== Limitations and future work ==<br />
<br />
The tool has some limitations that must be taken into consideration. First of all, the visualization is (except for node-coloring) limited to 2D. An extension to 3D would be possible, but this might cause severe occlusion problems and destroy the simplicity of the visualization. <br />
<br />
Another limitation is that the technique works only on discrete-valued dimensions. Continuous values are more difficult to aggregate, this could lead to a large amount of connections. <br />
<br />
A last limitation that may be addressed in future (just like the continuous data) is the representation of multivariate edges. A similar approach could be used to aggregate edges that contain additional information, however these graphs are less common in practice than graphs with multivariate nodes. <br />
<br />
<br />
== References ==<br />
[http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs]<br />
<br />
[[Category: Techniques]]<br />
[[Category: Interaction_Techniques]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Visual_Exploration_of_Multivariate_Graphs_by_Roll-Up_and_Selection&diff=21435Visual Exploration of Multivariate Graphs by Roll-Up and Selection2009-05-26T09:44:08Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:Wat_pivotgraph_overview.jpg|Rolled-up example diagram done by PivotGraph]]<br>Multivariate diagramm rolled up in two dimensions [Wattenberg, 2006]<br />
<br />
[[Wattenberg, Martin|Martin Wattenberg]] [Wattenberg, 2006] described in his paper [http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs] how Multivariate Graphs can be easily analyzed by rolling-up on certain dimensions. The paper focuses on a software tool called PivotGraph (unfortunately not available) but describes a strategy that could also be used in other tools. <br />
<br />
{{Definition|'''Multivariate Graphs''' are multi-dimensional: Each node in a graph is associated with several attributes. Common examples are social networks where the nodes might contain information about gender, age etc. or Markov chains where each node has a certain state. The paper mentioned above (as well as the software tool PivotGraph) focuses on graphs with discrete categorical dimensions in the nodes.<br />
<br>[Wattenberg, 2006]}}<br />
<br />
<br />
== Multivariate graphs - common approach ==<br />
<br />
Two visualizations of multivariate graphs are very popular: "Node-and-link diagrams" and matrix views. "Node-and-link diagrams" represent a network topography, additional information may be coded by labeling and coloring nodes, matrix views (normally only 2D) create a main-matrix of one characteristic in which the sub-characteristic is repeated. <br />
<br />
== Problems in analyzing multivariate graphs ==<br />
<br />
Both visualizations - node-and-link diagram and matrix diagram allow only poor analysis of the information contained in the nodes. Easy questions like "How many men are in the network?" may require the analysist to count every node. <br />
<br />
[[Image:Wat_pivotgraph_roll-up.jpg|thumb|Rolling up a network diagram]]<br />
== Solution: Roll-up on one (two) dimension(s) ==<br />
<br />
<br />
The main simplification in PivotGraph is to roll a graph up in any dimension(s): Replace all nodes with the same value in these dimensions with a node representing the amount of nodes by its size. Aggregate the connections in the same way. <br />
<br />
This way you can select up to two dimensions that form a grid, e.g. gender and company. Instead of the large graph, you receive a simpler graph showing the aggregated connections between nodes that correspond to a certain gender and a certain company.<br />
<br />
[[Image:Wat_pivotgraph_select.jpg|thumb|Selecting along a node attribute in a social network]]<br />
== Solution: Selection ==<br />
<br />
As addition to roll-up - parts of the diagram can be selected, e.g. all nodes representing females. <br />
<br />
== Considerations ==<br />
<br />
{{Quotation|Although the basic idea [...] is quite simple, it turns out there are a number of subtile challenges that need to be addressed for the visualization to remain legible.| [Wattenberg, 2006]}} <br />
<br />
For optimal understanding, the size of the nodes reflects the amount of aggregated data, just as the thickness of the connections. The nodes may be colored according any other attribute, but the color of the lines should be used to indicate ratio of the weight (connections per node) . <br />
<br />
Although, when using a straight grid layout as PivotGraph does, the connections should not be straight to avoid overlapping. Slightly bend arrows avoid occlusion problems. <br />
<br />
[[Image:Wat_pivotgraph_singledim.jpg|thumb|Rolling up in one dimensions leads to a one-axis graph]]<br />
<br />
The application allows the user also to roll-up in only one dimension. This leads to a graph with just one axis, nevertheless this layout can contain important information, e.g. the communication between several locations in a company. <br />
<br />
An important part of the analysis is the user-interaction. The user may chose and the dimensions to roll up at any point, the diagram is the automatically updated. User testing has shown, that this transition has to smoothly interpolate between the graphs, not only calculating the straight interpolation but maybe also intermediate graphs and displaying the transitions of the most important nodes and connections. <br />
<br />
Wattenberg describes in his paper three user testings in which all user responded very positive on the transitions between different graphs. <br />
<br />
[[Image:Wat_pivotgraph_ui.jpg|thumb|User Interface of PivotGraph]]<br />
== PivotGraph user interface ==<br />
The user interface is quite simple and basic to operate. The main window displays the current scatterplot and the dimensions, the right side allows the user to change the current view by rolling-up on attributes or selecting specific attribute-values. Nodes display additional information on mouse-over. <br />
<br />
== Advantages and disadvantages ==<br />
[[Image:pgnl.png|200px|Node-and-Link Diagram]] [[Image:pgmatrix.png|200px|Matrix View]] [[Image:pgpg.png|180px|Multivariate Graph]]<br><br />
The three figures above all represent the very same dataset, from left to right: Node-and-link diagram, matrix view and a multivariate graph generated by the PivotGraph application. Matrix views tend to offer the advantage of a comprehensive overview of all individual connections over node-and-link diagrams. However, to the unexperienced user they might happen to hide some information, as due to the emphasis on the first sort dimension (namely "color") some connections can seem obscure. Therefore, the multivariate graph view is to be preferred when inspecting relations on two dimensions at once. <br />
<br />
The multivariate graph technology also comes with some disadvantages: Roll-up and selection transformations might not allow certain aspects of graph topolgy to be preserved: Acyclic graphs might become cyclic, disconnected graphs might become connected for instance. Therefore, matrix views might be more suitable for experienced users, multivariate graphs on the other hand might prove to be more readable to an unexperienced audience.<br />
<br />
== Limitations and future work ==<br />
<br />
The tool have some limitations that must be taken into consideration. First of all, the visualization is (except for node-coloring) limited to 2D. An extension to 3D would be possible, but this might cause severe occlusion problems and destroy the simplicity of the visualization. <br />
<br />
Another limitation is that the technique works only on discrete-valued dimensions. Continuous are more difficult to aggregate, this could led to a large amount of connections. <br />
<br />
A last limitation that may be addressed in future (just like the continuous data) is the representation of multivariate edges. A similar approach could be used to aggregate edges that contain additional information, however these graphs are less common in practice than graphs with multivariate nodes. <br />
<br />
<br />
== References ==<br />
[http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs]<br />
<br />
[[Category: Techniques]]<br />
[[Category: Interaction_Techniques]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=File:Pgpg.png&diff=21434File:Pgpg.png2009-05-26T09:40:31Z<p>UE-InfoVis09-04: Network Graph of a small company</p>
<hr />
<div>== Summary ==<br />
Network Graph of a small company<br />
== Copyright status ==<br />
taken from (Wattenberg, 2006): Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or fee. CHI 2006, April 22-28, 2006, Montreal, Quebec, Canada. Copyright 2006 ACM 1-59593-178-3/06/0004...$5.00<br />
== Source ==<br />
Wattenberg, Martin: Visual Exploration of Multivariate Graphs, Visual Communication Lab, IBM Research, 2006, Quebec, Canada</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=File:Pgnl.png&diff=21433File:Pgnl.png2009-05-26T09:40:04Z<p>UE-InfoVis09-04: PivotGraph visualisation of a small company</p>
<hr />
<div>== Summary ==<br />
PivotGraph visualisation of a small company<br />
== Copyright status ==<br />
taken from (Wattenberg, 2006): Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or fee. CHI 2006, April 22-28, 2006, Montreal, Quebec, Canada. Copyright 2006 ACM 1-59593-178-3/06/0004...$5.00<br />
== Source ==<br />
Wattenberg, Martin: Visual Exploration of Multivariate Graphs, Visual Communication Lab, IBM Research, 2006, Quebec, Canada</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=File:Pgmatrix.png&diff=21432File:Pgmatrix.png2009-05-26T09:39:28Z<p>UE-InfoVis09-04: Matrix-Diagramm of a small example company</p>
<hr />
<div>== Summary ==<br />
Matrix-Diagramm of a small example company<br />
== Copyright status ==<br />
own work - free<br />
== Source ==<br />
own work</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Visual_Exploration_of_Multivariate_Graphs_by_Roll-Up_and_Selection&diff=21431Visual Exploration of Multivariate Graphs by Roll-Up and Selection2009-05-26T09:31:32Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:Wat_pivotgraph_overview.jpg|Rolled-up example diagram done by PivotGraph]]<br>Multivariate diagramm rolled up in two dimensions [Wattenberg, 2006]<br />
<br />
[[Wattenberg, Martin|Martin Wattenberg]] [Wattenberg, 2006] described in his paper [http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs] how Multivariate Graphs can be easily analyzed by rolling-up on certain dimensions. The paper focuses on a software tool called PivotGraph (unfortunately not available) but describes a strategy that could also be used in other tools. <br />
<br />
{{Definition|'''Multivariate Graphs''' are multi-dimensional: Each node in a graph is associated with several attributes. Common examples are social networks where the nodes might contain information about gender, age etc. or Markov chains where each node has a certain state. The paper mentioned above (as well as the software tool PivotGraph) focuses on graphs with discrete categorical dimensions in the nodes.<br />
<br>[Wattenberg, 2006]}}<br />
<br />
<br />
== Multivariate graphs - common approach ==<br />
<br />
Two visualizations of multivariate graphs are very popular: "Node-and-link diagrams" and matrix views. "Node-and-link diagrams" represent a network topography, additional information may be coded by labeling and coloring nodes, matrix views (normally only 2D) create a main-matrix of one characteristic in which the sub-characteristic is repeated. <br />
<br />
== Problems in analyzing multivariate graphs ==<br />
<br />
Both visualizations - node-and-link diagram and matrix diagram allow only poor analysis of the information contained in the nodes. Easy questions like "How many men are in the network?" may require the analysist to count every node. <br />
<br />
[[Image:Wat_pivotgraph_roll-up.jpg|thumb|Rolling up a network diagram]]<br />
== Solution: Roll-up on one (two) dimension(s) ==<br />
<br />
<br />
The main simplification in PivotGraph is to roll a graph up in any dimension(s): Replace all nodes with the same value in these dimensions with a node representing the amount of nodes by its size. Aggregate the connections in the same way. <br />
<br />
This way you can select up to two dimensions that form a grid, e.g. gender and company. Instead of the large graph, you receive a simpler graph showing the aggregated connections between nodes that correspond to a certain gender and a certain company.<br />
<br />
[[Image:Wat_pivotgraph_select.jpg|thumb|Selecting along a node attribute in a social network]]<br />
== Solution: Selection ==<br />
<br />
As addition to roll-up - parts of the diagram can be selected, e.g. all nodes representing females. <br />
<br />
== Considerations ==<br />
<br />
{{Quotation|Although the basic idea [...] is quite simple, it turns out there are a number of subtile challenges that need to be addressed for the visualization to remain legible.| [Wattenberg, 2006]}} <br />
<br />
For optimal understanding, the size of the nodes reflects the amount of aggregated data, just as the thickness of the connections. The nodes may be colored according any other attribute, but the color of the lines should be used to indicate ratio of the weight (connections per node) . <br />
<br />
Although, when using a straight grid layout as PivotGraph does, the connections should not be straight to avoid overlapping. Slightly bend arrows avoid occlusion problems. <br />
<br />
[[Image:Wat_pivotgraph_singledim.jpg|thumb|Rolling up in one dimensions leads to a one-axis graph]]<br />
<br />
The application allows the user also to roll-up in only one dimension. This leads to a graph with just one axis, nevertheless this layout can contain important information, e.g. the communication between several locations in a company. <br />
<br />
An important part of the analysis is the user-interaction. The user may chose and the dimensions to roll up at any point, the diagram is the automatically updated. User testing has shown, that this transition has to smoothly interpolate between the graphs, not only calculating the straight interpolation but maybe also intermediate graphs and displaying the transitions of the most important nodes and connections. <br />
<br />
Wattenberg describes in his paper three user testings in which all user responded very positive on the transitions between different graphs. <br />
<br />
[[Image:Wat_pivotgraph_ui.jpg|thumb|User Interface of PivotGraph]]<br />
== PivotGraph user interface ==<br />
The user interface is quite simple and basic to operate. The main window displays the current scatterplot and the dimensions, the right side allows the user to change the current view by rolling-up on attributes or selecting specific attribute-values. Nodes display additional information on mouse-over. <br />
<br />
== Advantages and disadvantages ==<br />
<br />
== Limitations and future work ==<br />
<br />
The tool have some limitations that must be taken into consideration. First of all, the visualization is (except for node-coloring) limited to 2D. An extension to 3D would be possible, but this might cause severe occlusion problems and destroy the simplicity of the visualization. <br />
<br />
Another limitation is that the technique works only on discrete-valued dimensions. Continuous are more difficult to aggregate, this could led to a large amount of connections. <br />
<br />
A last limitation that may be addressed in future (just like the continuous data) is the representation of multivariate edges. A similar approach could be used to aggregate edges that contain additional information, however these graphs are less common in practice than graphs with multivariate nodes. <br />
<br />
<br />
== References ==<br />
[http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs]<br />
<br />
[[Category: Techniques]]<br />
[[Category: Interaction_Techniques]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Visual_Exploration_of_Multivariate_Graphs_by_Roll-Up_and_Selection&diff=21430Visual Exploration of Multivariate Graphs by Roll-Up and Selection2009-05-26T09:25:33Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:Wat_pivotgraph_overview.jpg|Rolled-up example diagram done by PivotGraph]]<br>Multivariate diagramm rolled up in two dimensions [Wattenberg, 2006]<br />
<br />
[[Wattenberg, Martin|Martin Wattenberg]] [Wattenberg, 2006] described in his paper [http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs] how Multivariate Graphs can be easily analyzed by rolling-up on certain dimensions. The paper focuses on a software tool called PivotGraph (unfortunately not available) but describes a strategy that could also be used in other tools. <br />
<br />
{{Definition|'''Multivariate Graphs''' are multi-dimensional: Each node in a graph is associated with several attributes. Common examples are social networks where the nodes might contain information about gender, age etc. or Markov chains where each node has a certain state. The paper mentioned above (as well as the software tool PivotGraph) focuses on graphs with discrete categorical dimensions in the nodes.<br />
<br>[Wattenberg, 2006]}}<br />
<br />
<br />
== Multivariate graphs - common approach ==<br />
<br />
Two visualizations of multivariate graphs are very popular: "Node-and-link diagrams" and matrix views. "Node-and-link diagrams" represent a network topography, additional information may be coded by labeling and coloring nodes, matrix views (normally only 2D) create a main-matrix of one characteristic in which the sub-characteristic is repeated. <br />
<br />
== Problems in analyzing multivariate graphs ==<br />
<br />
Both visualizations - node-and-link diagram and matrix diagram allow only poor analysis of the information contained in the nodes. Easy questions like "How many men are in the network?" may require the analysist to count every node. <br />
<br />
[[Image:Wat_pivotgraph_roll-up.jpg|thumb|Rolling up a network diagram]]<br />
== Solution: Roll-up on one (two) dimension(s) ==<br />
<br />
<br />
The main simplification in PivotGraph is to roll a graph up in any dimension(s): Replace all nodes with the same value in these dimensions with a node representing the amount of nodes by its size. Aggregate the connections in the same way. <br />
<br />
This way you can select up to two dimensions that form a grid, e.g. gender and company. Instead of the large graph, you receive a simpler graph showing the aggregated connections between nodes that correspond to a certain gender and a certain company.<br />
<br />
[[Image:Wat_pivotgraph_select.jpg|thumb|Selecting along a node attribute in a social network]]<br />
== Solution: Selection ==<br />
<br />
As addition to roll-up - parts of the diagram can be selected, e.g. all nodes representing females. <br />
<br />
== Considerations ==<br />
<br />
{{Quotation|Although the basic idea [...] is quite simple, it turns out there are a number of subtile challenges that need to be addressed for the visualization to remain legible.| [Wattenberg, 2006]}} <br />
<br />
For optimal understanding, the size of the nodes reflects the amount of aggregated data, just as the thickness of the connections. The nodes may be colored according any other attribute, but the color of the lines should be used to indicate ratio of the weight (connections per node) . <br />
<br />
Although, when using a straight grid layout as PivotGraph does, the connections should not be straight to avoid overlapping. Slightly bend arrows avoid occlusion problems. <br />
<br />
[[Image:Wat_pivotgraph_singledim.jpg|thumb|Rolling up in one dimensions leads to a one-axis graph]]<br />
<br />
The application allows the user also to roll-up in only one dimension. This leads to a graph with just one axis, nevertheless this layout can contain important information, e.g. the communication between several locations in a company. <br />
<br />
An important part of the analysis is the user-interaction. The user may chose and the dimensions to roll up at any point, the diagram is the automatically updated. User testing has shown, that this transition has to smoothly interpolate between the graphs, not only calculating the straight interpolation but maybe also intermediate graphs and displaying the transitions of the most important nodes and connections. <br />
<br />
Wattenberg describes in his paper three user testings in which all user responded very positive on the transitions between different graphs. <br />
<br />
[[Image:Wat_pivotgraph_ui.jpg|thumb|User Interface of PivotGraph]]<br />
== PivotGraph user interface ==<br />
The user interface is quite simple and basic to operate. The main window displays the current scatterplot and the dimensions, the right side allows the user to change the current view by rolling-up on attributes or selecting specific attribute-values. Nodes display additional information on mouse-over. <br />
<br />
== Advantages and disadvantages ==<br />
<br />
== Limitations and feature work ==<br />
<br />
The tool have some limitations that must be taken into consideration. First of all, the visualization is (except for node-coloring) limited to 2D. An extension to 3D would be possible, but this might cause severe occlusion problems and destroy the simplicity of the visualization. <br />
<br />
Another limitation is that the technique works only on discrete-valued dimensions. Continuous are more difficult to aggregate, this could led to a large amount of connections. <br />
<br />
A last limitation that may be addressed in future (just like the continuous data) is the representation of multivariate edges. A similar approach could be used to aggregate edges that contain additional information, however these graphs are less common in practice than graphs with multivariate nodes. <br />
<br />
<br />
== References ==<br />
[http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs]<br />
<br />
[[Category: Techniques]]<br />
[[Category: Interaction_Techniques]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Visual_Exploration_of_Multivariate_Graphs_by_Roll-Up_and_Selection&diff=21429Visual Exploration of Multivariate Graphs by Roll-Up and Selection2009-05-26T09:23:56Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:Wat_pivotgraph_overview.jpg|Rolled-up example diagram done by PivotGraph]]<br>Multivariate diagramm rolled up in two dimensions [Wattenberg, 2006]<br />
<br />
[[Wattenberg, Martin|Martin Wattenberg]] [Wattenberg, 2006] described in his paper [http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs] how Multivariate Graphs can be easily analyzed by rolling-up on certain dimensions. The paper focuses on a software tool called PivotGraph (unfortunately not available) but describes a strategy that could also be used in other tools. <br />
<br />
{{Definition|'''Multivariate Graphs''' are multi-dimensional: Each node in a graph is associated with several attributes. Common examples are social networks where the nodes might contain information about gender, age etc. or Markov chains where each node has a certain state. The paper mentioned above (as well as the software tool PivotGraph) focuses on graphs with discrete categorical dimensions in the nodes.<br />
<br>[Wattenberg, 2006]}}<br />
<br />
<br />
== Multivariate graphs - common approach ==<br />
<br />
Two visualizations of multivariate graphs are very popular: "Node-and-link diagrams" and matrix views. "Node-and-link diagrams" represent a network topography, additional information may be coded by labeling and coloring nodes, matrix views (normally only 2D) create a main-matrix of one characteristic in which the sub-characteristic is repeated. <br />
<br />
== Problems in analyzing multivariate graphs ==<br />
<br />
Both visualizations - node-and-link diagram and matrix diagram allow only poor analysis of the information contained in the nodes. Easy questions like "How many men are in the network?" may require the analysist to count every node. <br />
<br />
[[Image:Wat_pivotgraph_roll-up.jpg|thumb|Rolling up a network diagram]]<br />
== Solution: Roll-up on one (two) dimension(s) ==<br />
<br />
<br />
The main simplification in PivotGraph is to roll a graph up in any dimension(s): Replace all nodes with the same value in these dimensions with a node representing the amount of nodes by its size. Aggregate the connections in the same way. <br />
<br />
This way you can select up to two dimensions that form a grid, e.g. gender and company. Instead of the large graph, you receive a simpler graph showing the aggregated connections between nodes that correspond to a certain gender and a certain company.<br />
<br />
[[Image:Wat_pivotgraph_select.jpg|thumb|Selecting along a node attribute in a social network]]<br />
== Solution: Selection ==<br />
<br />
As addition to roll-up - parts of the diagram can be selected, e.g. all nodes representing females. <br />
<br />
== Considerations ==<br />
<br />
{{Quotation|Although the basic idea [...] is quite simple, it turns out there are a number of subtile challenges that need to be addressed for the visualization to remain legible.| [Wattenberg, 2006]}} <br />
<br />
For optimal understanding, the size of the nodes reflects the amount of aggregated data, just as the thickness of the connections. The nodes may be colored according any other attribute, but the color of the lines should be used to indicate ratio of the weight (connections per node) . <br />
<br />
Although, when using a straight grid layout as PivotGraph does, the connections should not be straight to avoid overlapping. Slightly bend arrows avoid occlusion problems. <br />
<br />
[[Image:Wat_pivotgraph_singledim.jpg|thumb|Rolling up in one dimensions leads to a one-axis graph]]<br />
<br />
The application allows the user also to roll-up in only one dimension. This leads to a graph with just one axis, nevertheless this layout can contain important information, e.g. the communication between several locations in a company. <br />
<br />
An important part of the analysis is the user-interaction. The user may chose and the dimensions to roll up at any point, the diagram is the automatically updated. User testing has shown, that this transition has to smoothly interpolate between the graphs, not only calculating the straight interpolation but maybe also intermediate graphs and displaying the transitions of the most important nodes and connections. <br />
<br />
Wattenberg describes in his paper three user testings in which all user responded very positive on the transitions between different graphs. <br />
<br />
[[Image:Wat_pivotgraph_ui.jpg|thumb|User Interface of PivotGraph]]<br />
== PivotGraph user interface ==<br />
The user interface is quite simple and basic to operate. The main window displays the current scatterplot and the dimensions, the right side allows the user to change the current view by rolling-up on attributes or selecting specific attribute-values. Nodes display additional information on mouse-over. <br />
<br />
== Advantages and disadvantages ==<br />
<br />
== Limitations and feature work ==<br />
<br />
The tool have some limitations that must be taken into consideration. First of all, the visualization is (except for node-coloring) limited to 2D. An extension to 3D would be possible, but this might cause severe occlusion problems and destroy the simplicity of the visualization. <br />
<br />
Another limitation is that the technique works only on discrete-valued dimensions. Continuous are more difficult to aggregate, this could led to a large amount of connections. <br />
<br />
A last limitation that may be addressed in future (just like the continuous data) is the representation of multivariate edges. A similar approach could be used to aggregate edges that contain additional information, however these graphs are less common in practice than graphs with multivariate nodes. <br />
<br />
<br />
<br />
<br />
<br />
[[Category: Techniques]]<br />
[[Category: Interaction_Techniques]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Visual_Exploration_of_Multivariate_Graphs_by_Roll-Up_and_Selection&diff=21428Visual Exploration of Multivariate Graphs by Roll-Up and Selection2009-05-26T09:14:51Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:Wat_pivotgraph_overview.jpg|Rolled-up example diagram done by PivotGraph]]<br>Multivariate diagramm rolled up in two dimensions [Wattenberg, 2006]<br />
<br />
[[Wattenberg, Martin|Martin Wattenberg]] [Wattenberg, 2006] described in his paper [http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs] how Multivariate Graphs can be easily analyzed by rolling-up on certain dimensions. The paper focuses on a software tool called PivotGraph (unfortunately not available) but describes a strategy that could also be used in other tools. <br />
<br />
{{Definition|'''Multivariate Graphs''' are multi-dimensional: Each node in a graph is associated with several attributes. Common examples are social networks where the nodes might contain information about gender, age etc. or Markov chains where each node has a certain state. The paper mentioned above (as well as the software tool PivotGraph) focuses on graphs with discrete categorical dimensions in the nodes.<br />
<br>[Wattenberg, 2006]}}<br />
<br />
<br />
== Multivariate graphs - common approach ==<br />
<br />
Two visualizations of multivariate graphs are very popular: "Node-and-link diagrams" and matrix views. "Node-and-link diagrams" represent a network topography, additional information may be coded by labeling and coloring nodes, matrix views (normally only 2D) create a main-matrix of one characteristic in which the sub-characteristic is repeated. <br />
<br />
== Problems in analyzing multivariate graphs ==<br />
<br />
Both visualizations - node-and-link diagram and matrix diagram allow only poor analysis of the information contained in the nodes. Easy questions like "How many men are in the network?" may require the analysist to count every node. <br />
<br />
[[Image:Wat_pivotgraph_roll-up.jpg|thumb|Rolling up a network diagram]]<br />
== Solution: Roll-up on one (two) dimension(s) ==<br />
<br />
<br />
The main simplification in PivotGraph is to roll a graph up in any dimension(s): Replace all nodes with the same value in these dimensions with a node representing the amount of nodes by its size. Aggregate the connections in the same way. <br />
<br />
This way you can select up to two dimensions that form a grid, e.g. gender and company. Instead of the large graph, you receive a simpler graph showing the aggregated connections between nodes that correspond to a certain gender and a certain company.<br />
<br />
[[Image:Wat_pivotgraph_select.jpg|thumb|Selecting along a node attribute in a social network]]<br />
== Solution: Selection ==<br />
<br />
As addition to roll-up - parts of the diagram can be selected, e.g. all nodes representing females. <br />
<br />
== Considerations ==<br />
<br />
{{Quotation|Although the basic idea [...] is quite simple, it turns out there are a number of subtile challenges that need to be addressed for the visualization to remain legible.| [Wattenberg, 2006]}} <br />
<br />
For optimal understanding, the size of the nodes reflects the amount of aggregated data, just as the thickness of the connections. The nodes may be colored according any other attribute, but the color of the lines should be used to indicate ratio of the weight (connections per node) . <br />
<br />
Although, when using a straight grid layout as PivotGraph does, the connections should not be straight to avoid overlapping. Slightly bend arrows avoid occlusion problems. <br />
<br />
An important part of the analysis is the user-interaction. The user may chose and the dimensions to roll up at any point, the diagram is the automatically updated. User testing has shown, that this transition has to smoothly interpolate between the graphs, not only calculating the straight interpolation but maybe also intermediate graphs and displaying the transitions of the most important nodes and connections. <br />
<br />
Wattenberg describes in his paper three user testings in which all user responded very positive on the transitions between different graphs. <br />
<br />
== Advantages and disadvantages ==<br />
<br />
== Limitations and feature work ==<br />
<br />
The tool have some limitations that must be taken into consideration. First of all, the visualization is (except for node-coloring) limited to 2D. An extension to 3D would be possible, but this might cause severe occlusion problems and destroy the simplicity of the visualization. <br />
<br />
Another limitation is that the technique works only on discrete-valued dimensions. Continuous are more difficult to aggregate, this could led to a large amount of connections. <br />
<br />
A last limitation that may be addressed in future (just like the continuous data) is the representation of multivariate edges. A similar approach could be used to aggregate edges that contain additional information, however these graphs are less common in practice than graphs with multivariate nodes. <br />
<br />
<br />
<br />
<br />
<br />
[[Category: Techniques]]<br />
[[Category: Interaction_Techniques]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Visual_Exploration_of_Multivariate_Graphs_by_Roll-Up_and_Selection&diff=21427Visual Exploration of Multivariate Graphs by Roll-Up and Selection2009-05-26T08:54:54Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:Wat_pivotgraph_overview.jpg|Rolled-up example diagram done by PivotGraph]]<br>Multivariate diagramm rolled up in two dimensions [Wattenberg, 2006]<br />
<br />
[[Wattenberg, Martin|Martin Wattenberg]] [Wattenberg, 2006] described in his paper [http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs] how Multivariate Graphs can be easily analyzed by rolling-up on certain dimensions. The paper focuses on a software tool called PivotGraph (unfortunately not available) but describes a strategy that could also be used in other tools. <br />
<br />
{{Definition|'''Multivariate Graphs''' are multi-dimensional: Each node in a graph is associated with several attributes. Common examples are social networks where the nodes might contain information about gender, age etc. or Markov chains where each node has a certain state. The paper mentioned above (as well as the software tool PivotGraph) focuses on graphs with discrete categorical dimensions in the nodes.<br />
<br>[Wattenberg, 2006]}}<br />
<br />
<br />
== Multivariate graphs - common approach ==<br />
<br />
Two visualizations of multivariate graphs are very popular: "Node-and-link diagrams" and matrix views. "Node-and-link diagrams" represent a network topography, additional information may be coded by labeling and coloring nodes, matrix views (normally only 2D) create a main-matrix of one characteristic in which the sub-characteristic is repeated. <br />
<br />
== Problems in analyzing multivariate graphs ==<br />
<br />
Both visualizations - node-and-link diagram and matrix diagram allow only poor analysis of the information contained in the nodes. Easy questions like "How many men are in the network?" may require the analysist to count every node. <br />
<br />
[[Image:Wat_pivotgraph_roll-up.jpg|thumb|Rolling up a network diagram]]<br>Rolling up a simple network diagram on the “gender” dimension [Wattenberg, 2006]<br />
== Solution: Roll-up on one (two) dimension(s) ==<br />
<br />
<br />
The main simplification in PivotGraph is to roll a graph up in any dimension(s): Replace all nodes with the same value in these dimensions with a node representing the amount of nodes by its size. Aggregate the connections in the same way. <br />
<br />
This way you can select up to two dimensions that form a grid, e.g. gender and company. Instead of the large graph, you receive a simpler graph showing the aggregated connections between nodes that correspond to a certain gender and a certain company.<br />
<br />
[[Image:Wat_pivotgraph_select.jpg|thumb|Selecting along a node attribute in a social network]]<br> Selecting along a node attribute in a social network (gender=female) [Wattenberg, 2006]<br />
== Solution: Selection ==<br />
<br />
As addition to roll-up - parts of the diagram can be selected, e.g. all nodes representing females. <br />
<br />
== Considerations ==<br />
<br />
{{Quotation|Although the basic idea [...] is quite simple, it turns out there are a number of subtile challenges that need to be addressed for the visualization to remain legible.| [Wattenberg, 2006]}} <br />
<br />
== Advantages and disadvantages ==<br />
<br />
== Limitations ==<br />
<br />
Although the technique <br />
- 2D<br />
- discrite values to roll up<br />
...<br />
<br />
<br />
<br />
[[Category: Techniques]]<br />
[[Category: Interaction_Techniques]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=File:Wat_pivotgraph_ui.jpg&diff=21426File:Wat pivotgraph ui.jpg2009-05-26T08:26:38Z<p>UE-InfoVis09-04: User interface of PivotGraph</p>
<hr />
<div>== Summary ==<br />
User interface of PivotGraph<br />
== Copyright status ==<br />
taken from (Wattenberg, 2006): Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or fee. CHI 2006, April 22-28, 2006, Montreal, Quebec, Canada. Copyright 2006 ACM 1-59593-178-3/06/0004...$5.00<br />
== Source ==<br />
Wattenberg, Martin: Visual Exploration of Multivariate Graphs, Visual Communication Lab, IBM Research, 2006, Quebec, Canada</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=File:Wat_pivotgraph_singledim.jpg&diff=21425File:Wat pivotgraph singledim.jpg2009-05-26T08:26:02Z<p>UE-InfoVis09-04: on 1 dimension rolled-up multivariate graph done by PivotGraph</p>
<hr />
<div>== Summary ==<br />
on 1 dimension rolled-up multivariate graph done by PivotGraph<br />
== Copyright status ==<br />
taken from (Wattenberg, 2006): Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or fee. CHI 2006, April 22-28, 2006, Montreal, Quebec, Canada. Copyright 2006 ACM 1-59593-178-3/06/0004...$5.00<br />
== Source ==<br />
Wattenberg, Martin: Visual Exploration of Multivariate Graphs, Visual Communication Lab, IBM Research, 2006, Quebec, Canada</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=File:Wat_pivotgraph_select.jpg&diff=21424File:Wat pivotgraph select.jpg2009-05-26T08:23:05Z<p>UE-InfoVis09-04: Displaying a selection in a (multivariate) network graph</p>
<hr />
<div>== Summary ==<br />
Displaying a selection in a (multivariate) network graph<br />
== Copyright status ==<br />
taken from (Wattenberg, 2006): Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or fee. CHI 2006, April 22-28, 2006, Montreal, Quebec, Canada. Copyright 2006 ACM 1-59593-178-3/06/0004...$5.00<br />
== Source ==<br />
Wattenberg, Martin: Visual Exploration of Multivariate Graphs, Visual Communication Lab, IBM Research, 2006, Quebec, Canada</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=File:Wat_pivotgraph_roll-up.jpg&diff=21423File:Wat pivotgraph roll-up.jpg2009-05-26T08:22:06Z<p>UE-InfoVis09-04: Displaying the roll-up process in a multivariate graph.</p>
<hr />
<div>== Summary ==<br />
Displaying the roll-up process in a multivariate graph. <br />
== Copyright status ==<br />
taken from (Wattenberg, 2006): Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or fee. CHI 2006, April 22-28, 2006, Montreal, Quebec, Canada. Copyright 2006 ACM 1-59593-178-3/06/0004...$5.00<br />
== Source ==<br />
Wattenberg, Martin: Visual Exploration of Multivariate Graphs, Visual Communication Lab, IBM Research, 2006, Quebec, Canada</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=File:Wat_pivotgraph_overview.jpg&diff=21422File:Wat pivotgraph overview.jpg2009-05-26T08:18:27Z<p>UE-InfoVis09-04: Example rolled-up multivariate graph done by PivotGraph (Wattenberg, 2006)</p>
<hr />
<div>== Summary ==<br />
Example rolled-up multivariate graph done by PivotGraph (Wattenberg, 2006)<br />
== Copyright status ==<br />
part of (Wattenberg 2006): Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or fee. CHI 2006, April 22-28, 2006, Montreal, Quebec, Canada. Copyright 2006 ACM 1-59593-178-3/06/0004...$5.00<br />
== Source ==<br />
Wattenberg, Martin: Visual Exploration of Multivariate Graphs, Visual Communication Lab, IBM Research, 2006, Quebec, Canada</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Visual_Exploration_of_Multivariate_Graphs_by_Roll-Up_and_Selection&diff=21421Visual Exploration of Multivariate Graphs by Roll-Up and Selection2009-05-26T07:40:40Z<p>UE-InfoVis09-04: New page: Martin Wattenberg [Wattenberg, 2006] described in his paper [http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpa...</p>
<hr />
<div>[[Wattenberg, Martin|Martin Wattenberg]] [Wattenberg, 2006] described in his paper [http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w Visual Exploration of Multivariate Graphs] how Multivariate Graphs can be easily analyzed by rolling-up on certain dimensions. The paper focuses on a software tool called PivotGraph (unfortunately not available) but describes a strategy that could also be used in other tools. <br />
<br />
{{Definition|'''Multivariate Graphs''' are multi-dimensional: Each node in a graph is associated with several attributes. Common examples are social networks where the nodes might contain information about gender, age etc. or Markov chains where each node has a certain state. The paper mentioned above (as well as the software tool PivotGraph) focuses on graphs with discrete categorical dimensions in the nodes.<br />
<br>[Wattenberg, 2006]}}<br />
<br />
<br />
== Multivariate graphs - common approach ==<br />
<br />
Two visualizations of multivariate graphs are very popular: "Node-and-link diagrams" and matrix views. "Node-and-link diagrams" represent a network topography, additional information may be coded by labeling and colloring nodes, matrix views (normally only 2D) create a main-matrix of one characteristic in which the sub-characteristic is repeated. <br />
<br />
== Problems in analyzing multivariate graphs ==<br />
<br />
Both visualizations - node-and-link diagram and matrix diagram allow only poor analysis of the information contained in the nodes. Easy questions like "How many men are in the network?" may require the analysist to count every node. <br />
<br />
== Solution: Roll-up on one (two) dimension(s) ==<br />
<br />
The main simplification in PivotGraph is to roll a graph up in any dimension(s): Replace all nodes with the same value in these dimensions with a node representing the amount of nodes by its size. Aggregate the connections in the same way. <br />
<br />
This way you can select up to two dimensions that form a grid, e.g. gender and company. Instead of the large graph, you receive a simpler graph showing the aggregated connections between nodes that correspond to a certain gender and a certain company.<br />
<br />
<br />
== Solution: Selection ==<br />
<br />
As addition to roll-up - parts of the diagram can be selected, e.g. all nodes representing females. <br />
<br />
== Limitations ==<br />
<br />
Although the technique <br />
- 2D<br />
- discrite values to roll up<br />
...<br />
<br />
<br />
<br />
[[Category: Techniques]]<br />
[[Category: Interaction_Techniques]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Wattenberg,_Martin&diff=21420Wattenberg, Martin2009-05-26T07:23:23Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:martin_headshot_small.jpg|thumb|Martin Wattenberg]]<br />
<br />
'''Martin Wattenberg''' is a researcher at [http://www.ibm.com IBM] and founding manager of IBM's [http://www.research.ibm.com/visual/ Visual Communication Lab] whose work focuses on visual explorations of culturally significant data. His algorithmic approach is based on his background in mathematics. Wattenberg is known for his scientific and applied work in the field of information visualization and its application to collaborative computing, journalism and bioinformatics as well as for his information-based digital artwork. In his work, the mathematical underpinnings of a computer program are not simply tools used to create art; they are the core of the artworks themselves. [http://www.heise.de/kiosk/archiv/tr/2003/11/36_kiosk Technology Review] recently named him "one of the world's 100 top young innovators." <br />
<br />
<br />
Wattenberg's artwork has been exhibited at [http://www.ica.org.uk/ The London Institute of Contemporary Art], [http://whitney.org/ The Whitney Museum of American Art], [http://www.aec.at/ Ars Electronica], [http://www.newmuseum.org/ The New Museum], and at galleries and festivals internationally. Commissions include [http://americanhistory.si.edu/ The Smithsonian National Museum of American History], [http://web.mac.com/stevedean/The_Other_James_Deans_Studio_on_the_Internet/Artwork/Pages/NASA_Space_Art.html The NASA Art Program], [http://new-radio.org/ New Radio and Performing Arts Inc.], [http://www.walkerart.org/ The Walker Art Center] and others. <br />
<br />
<br />
His projects have been honored by the Columbia Journalism School Online Journalism Award and the National Magazine Award (with SmartMoney.com), the ID Magazine Interactive Media Design Review, the IDSA Industrial Design Excellence Award, and the Graz Biennale of Media and Architecture (with Marek Walczak). <br />
<br />
<br />
Martin Wattenberg and Marek Walczak started 1997 a collaboration called [http://mw2mw.com MW2MW] on which they both continue to present creative work in the field of information-based digital artwork.<br />
<br />
Previous to his work at IBM, Wattenberg was R&D Director at [http://www.smartmoney.com/ SmartMoney.com] and developed an informative market visualisation, called [http://www.smartmoney.com/map-of-the-market/ Map of the Market] in 1998.<br />
<br />
Wattenberg received his Ph.D. in mathematics from U.C. Berkeley, M.S. from Stanford University, and A.B. from Brown University.<br />
<br />
== External Links ==<br />
*[http://www.bewitched.com/ Martin Wattenberg's Home Page]<br />
<br />
== Interesting Work ==<br />
*2008 [http://transition.turbulence.org/spotlight/thinking/chess.html Thinking Machine] a chess game which visualises the thinking process of an AI opponent.<br />
*2008 [http://www.fleshmap.com Flesh Map] several visualisations of desire categorized into touch, look and listen. Tries to find answers on questions like "where would we like to be touched" or "what body parts characterise which music".<br />
*2007 [http://manyeyes.alphaworks.ibm.com/manyeyes/ Many Eyes] a platform which allows everybody to share data, create visualisations, analyze and interpret it in several ways.<br />
*2005 [http://namemapper.babynamewizard.com/namemapper/ Name Voyager] displays the popularity of names over time. <br />
*2003 [http://www.research.ibm.com/history/ history flow] Visualizing wiki web document evolution<br />
*1998 [http://www.bewitched.com/marketmap.html Map of the Market] an interactive visualisation of stock performance based on tree maps. <br />
<br />
== Related Work in InfoVisWiki ==<br />
[Wattenberg, 2006] Martin Wattenberg, Visual Exploration of Multivariate Graphs; Visual Communication Lab, IBM Research ([http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w original] - [[Visual Exploration of Multivariate Graphs by Roll-Up and Selection|InfoVisWiki]])<br />
<br />
== References ==<br />
[Wattenberg, 2005] Martin Wattenberg, www.bewitched.com - About, Retrieved at: Mai 14th, 2009. http://www.bewitched.com/about.html<br />
<br />
[[Category:Persons]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Wattenberg,_Martin&diff=21302Wattenberg, Martin2009-05-14T11:45:41Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:martin_headshot_small.jpg|thumb|Martin Wattenberg]]<br />
<br />
'''Martin Wattenberg''' is a researcher at [http://www.ibm.com IBM] and founding manager of IBM's [http://www.research.ibm.com/visual/ Visual Communication Lab] whose work focuses on visual explorations of culturally significant data. His algorithmic approach is based on his background in mathematics. Wattenberg is known for his scientific and applied work in the field of information visualization and its application to collaborative computing, journalism and bioinformatics as well as for his information-based digital artwork. In his work, the mathematical underpinnings of a computer program are not simply tools used to create art; they are the core of the artworks themselves. [http://www.heise.de/kiosk/archiv/tr/2003/11/36_kiosk Technology Review] recently named him "one of the world's 100 top young innovators." <br />
<br />
<br />
Wattenberg's artwork has been exhibited at [http://www.ica.org.uk/ The London Institute of Contemporary Art], [http://whitney.org/ The Whitney Museum of American Art], [http://www.aec.at/ Ars Electronica], [http://www.newmuseum.org/ The New Museum], and at galleries and festivals internationally. Commissions include [http://americanhistory.si.edu/ The Smithsonian National Museum of American History], [http://web.mac.com/stevedean/The_Other_James_Deans_Studio_on_the_Internet/Artwork/Pages/NASA_Space_Art.html The NASA Art Program], [http://new-radio.org/ New Radio and Performing Arts Inc.], [http://www.walkerart.org/ The Walker Art Center] and others. <br />
<br />
<br />
His projects have been honored by the Columbia Journalism School Online Journalism Award and the National Magazine Award (with SmartMoney.com), the ID Magazine Interactive Media Design Review, the IDSA Industrial Design Excellence Award, and the Graz Biennale of Media and Architecture (with Marek Walczak). <br />
<br />
<br />
Martin Wattenberg and Marek Walczak started 1997 a collaboration called [http://mw2mw.com MW2MW] on which they both continue to present creative work in the field of information-based digital artwork.<br />
<br />
Previous to his work at IBM, Wattenberg was R&D Director at [http://www.smartmoney.com/ SmartMoney.com] and developed an informative market visualisation, called [http://www.smartmoney.com/map-of-the-market/ Map of the Market] in 1998.<br />
<br />
Wattenberg received his Ph.D. in mathematics from U.C. Berkeley, M.S. from Stanford University, and A.B. from Brown University.<br />
<br />
== External Links ==<br />
*[http://www.bewitched.com/ Martin Wattenberg's Home Page]<br />
<br />
== Interesting Work ==<br />
*2008 [http://transition.turbulence.org/spotlight/thinking/chess.html Thinking Machine] a chess game which visualises the thinking process of an AI opponent.<br />
*2008 [http://www.fleshmap.com Flesh Map] several visualisations of desire categorized into touch, look and listen. Tries to find answers on questions like "where would we like to be touched" or "what body parts characterise which music".<br />
*2007 [http://manyeyes.alphaworks.ibm.com/manyeyes/ Many Eyes] a platform which allows everybody to share data, create visualisations, analyze and interpret it in several ways.<br />
*2005 [http://namemapper.babynamewizard.com/namemapper/ Name Voyager] displays the popularity of names over time. <br />
*2003 [http://www.research.ibm.com/history/ history flow] Visualizing wiki web document evolution<br />
*1998 [http://www.bewitched.com/marketmap.html Map of the Market] an interactive visualisation of stock performance based on tree maps. <br />
<br />
== Related Work in InfoVisWiki ==<br />
[Wattenberg, 2006] Martin Wattenberg, Visual Exploration of Multivariate Graphs; Visual Communication Lab, IBM Research ([http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w original] - [[Wattenberg_MultivariateGraphs|InfoVisWiki]])<br />
<br />
== References ==<br />
[Wattenberg, 2005] Martin Wattenberg, www.bewitched.com - About, Retrieved at: Mai 14th, 2009. http://www.bewitched.com/about.html<br />
<br />
[[Category:Persons]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Wattenberg,_Martin&diff=21301Wattenberg, Martin2009-05-14T11:45:06Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:martin_headshot_small.jpg|thumb|Martin Wattenberg]]<br />
<br />
'''Martin Wattenberg''' is a researcher at [http://www.ibm.com IBM] and founding manager of IBM's [http://www.research.ibm.com/visual/ Visual Communication Lab] whose work focuses on visual explorations of culturally significant data. His algorithmic approach is based on his background in mathematics. Wattenberg is known for his scientific and applied work in the field of information visualization and its application to collaborative computing, journalism and bioinformatics as well as for his information-based digital artwork. In his work, the mathematical underpinnings of a computer program are not simply tools used to create art; they are the core of the artworks themselves. [http://www.heise.de/kiosk/archiv/tr/2003/11/36_kiosk Technology Review] recently named him "one of the world's 100 top young innovators." <br />
<br />
<br />
Wattenberg's artwork has been exhibited at [http://www.ica.org.uk/ The London Institute of Contemporary Art], [http://whitney.org/ The Whitney Museum of American Art], [http://www.aec.at/ Ars Electronica], [http://www.newmuseum.org/ The New Museum], and at galleries and festivals internationally. Commissions include [http://americanhistory.si.edu/ The Smithsonian National Museum of American History], [http://web.mac.com/stevedean/The_Other_James_Deans_Studio_on_the_Internet/Artwork/Pages/NASA_Space_Art.html The NASA Art Program], [http://new-radio.org/ New Radio and Performing Arts Inc.], [http://www.walkerart.org/ The Walker Art Center] and others. <br />
<br />
<br />
His projects have been honored by the Columbia Journalism School Online Journalism Award and the National Magazine Award (with SmartMoney.com), the ID Magazine Interactive Media Design Review, the IDSA Industrial Design Excellence Award, and the Graz Biennale of Media and Architecture (with Marek Walczak). <br />
<br />
<br />
Martin Wattenberg and Marek Walczak started 1997 a collaboration called [http://mw2mw.com MW2MW] on which they both continue to present creative work in the field of information-based digital artwork.<br />
<br />
Previous to his work at IBM, Wattenberg was R&D Director at [http://www.smartmoney.com/ SmartMoney.com] and developed an informative market visualisation, called [http://www.smartmoney.com/map-of-the-market/ Map of the Market] in 1998.<br />
<br />
Wattenberg received his Ph.D. in mathematics from U.C. Berkeley, M.S. from Stanford University, and A.B. from Brown University.<br />
<br />
== External Links ==<br />
*[http://www.bewitched.com/ Martin Wattenberg's Home Page]<br />
<br />
== Interesting Work ==<br />
*2008 [http://transition.turbulence.org/spotlight/thinking/chess.html Thinking Machine] a chess game which visualises the thinking process of an AI opponent.<br />
*2008[http://www.fleshmap.com Flesh Map] several visualisations of desire categorized into touch, look and listen. Tries to find answers on questions like "where would we like to be touched" or "what body parts characterise which music".<br />
*2007 [http://manyeyes.alphaworks.ibm.com/manyeyes/ Many Eyes] a platform which allows everybody to share data, create visualisations, analyze and interpret it in several ways.<br />
*2005 [http://namemapper.babynamewizard.com/namemapper/ Name Voyager] displays the popularity of names over time. <br />
*2003 [http://www.research.ibm.com/history/ history flow] Visualizing wiki web document evolution<br />
*1998 [http://www.bewitched.com/marketmap.html Map of the Market] an interactive visualisation of stock performance based on tree maps. <br />
<br />
== Related Work in InfoVisWiki ==<br />
[Wattenberg, 2006] Martin Wattenberg, Visual Exploration of Multivariate Graphs; Visual Communication Lab, IBM Research ([http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w original] - [[Wattenberg_MultivariateGraphs|InfoVisWiki]])<br />
<br />
== References ==<br />
[Wattenberg, 2005] Martin Wattenberg, www.bewitched.com - About, Retrieved at: Mai 14th, 2009. http://www.bewitched.com/about.html<br />
<br />
[[Category:Persons]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Wattenberg_MultivariateGraphs&diff=21300Wattenberg MultivariateGraphs2009-05-14T11:44:29Z<p>UE-InfoVis09-04: New page: under construction....</p>
<hr />
<div>under construction....</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Wattenberg,_Martin&diff=21299Wattenberg, Martin2009-05-14T11:44:09Z<p>UE-InfoVis09-04: </p>
<hr />
<div>[[Image:martin_headshot_small.jpg|thumb|Martin Wattenberg]]<br />
<br />
'''Martin Wattenberg''' is a researcher at [http://www.ibm.com IBM] and founding manager of IBM's [http://www.research.ibm.com/visual/ Visual Communication Lab] whose work focuses on visual explorations of culturally significant data. His algorithmic approach is based on his background in mathematics. Wattenberg is known for his scientific and applied work in the field of information visualization and its application to collaborative computing, journalism and bioinformatics as well as for his information-based digital artwork. In his work, the mathematical underpinnings of a computer program are not simply tools used to create art; they are the core of the artworks themselves. [http://www.heise.de/kiosk/archiv/tr/2003/11/36_kiosk Technology Review] recently named him "one of the world's 100 top young innovators." <br />
<br />
<br />
Wattenberg's artwork has been exhibited at [http://www.ica.org.uk/ The London Institute of Contemporary Art], [http://whitney.org/ The Whitney Museum of American Art], [http://www.aec.at/ Ars Electronica], [http://www.newmuseum.org/ The New Museum], and at galleries and festivals internationally. Commissions include [http://americanhistory.si.edu/ The Smithsonian National Museum of American History], [http://web.mac.com/stevedean/The_Other_James_Deans_Studio_on_the_Internet/Artwork/Pages/NASA_Space_Art.html The NASA Art Program], [http://new-radio.org/ New Radio and Performing Arts Inc.], [http://www.walkerart.org/ The Walker Art Center] and others. <br />
<br />
<br />
His projects have been honored by the Columbia Journalism School Online Journalism Award and the National Magazine Award (with SmartMoney.com), the ID Magazine Interactive Media Design Review, the IDSA Industrial Design Excellence Award, and the Graz Biennale of Media and Architecture (with Marek Walczak). <br />
<br />
<br />
Martin Wattenberg and Marek Walczak started 1997 a collaboration called [http://mw2mw.com MW2MW] on which they both continue to present creative work in the field of information-based digital artwork.<br />
<br />
Previous to his work at IBM, Wattenberg was R&D Director at [http://www.smartmoney.com/ SmartMoney.com] and developed an informative market visualisation, called [http://www.smartmoney.com/map-of-the-market/ Map of the Market] in 1998.<br />
<br />
Wattenberg received his Ph.D. in mathematics from U.C. Berkeley, M.S. from Stanford University, and A.B. from Brown University.<br />
<br />
== External Links ==<br />
*[http://www.bewitched.com/ Martin Wattenberg's Home Page]<br />
<br />
<br />
== Interesting Work ==<br />
*2008 [http://transition.turbulence.org/spotlight/thinking/chess.html Thinking Machine] a chess game which visualises the thinking process of an AI opponent.<br />
*2008[http://www.fleshmap.com Flesh Map] several visualisations of desire categorized into touch, look and listen. Tries to find answers on questions like "where would we like to be touched" or "what body parts characterise which music".<br />
*2007 [http://manyeyes.alphaworks.ibm.com/manyeyes/ Many Eyes] a platform which allows everybody to share data, create visualisations, analyze and interpret it in several ways.<br />
*2005 [http://namemapper.babynamewizard.com/namemapper/ Name Voyager] displays the popularity of names over time. <br />
*2003 [http://www.research.ibm.com/history/ history flow] Visualizing wiki web document evolution<br />
*1998 [http://www.bewitched.com/marketmap.html Map of the Market] an interactive visualisation of stock performance based on tree maps. <br />
<br />
== Related Work in InfoVisWiki ==<br />
[Wattenberg, 2006] Martin Wattenberg, Visual Exploration of Multivariate Graphs; Visual Communication Lab, IBM Research ([http://www.google.at/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.research.ibm.com%2Fvisual%2Fpapers%2Fpivotgraph.pdf&ei=BgMMSoHAEMmP_QbV--ywBA&usg=AFQjCNHXHWZWVxEM8tCSNzoUxTNH50hXRg&sig2=NGoK6wAVWEoPzeeHT_Dc0w original] - [[Wattenberg_MultivariateGraphs|InfoVisWiki]])<br />
<br />
== References ==<br />
[Wattenberg, 2005] Martin Wattenberg, www.bewitched.com - About, Retrieved at: Mai 14th, 2009. http://www.bewitched.com/about.html<br />
<br />
[[Category:Persons]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=Wattenberg,_Martin&diff=21298Wattenberg, Martin2009-05-14T11:31:34Z<p>UE-InfoVis09-04: update martin wattenberg 09</p>
<hr />
<div>[[Image:Wattenberg.jpg|thumb|Martin Wattenberg]]<br />
<br />
'''Martin Wattenberg''' is a researcher at [http://www.ibm.com IBM] and founding manager of IBM's [http://www.research.ibm.com/visual/ Visual Communication Lab] whose work focuses on visual explorations of culturally significant data. His algorithmic approach is based on his background in mathematics. Wattenberg is known for his scientific and applied work in the field of information visualization and its application to collaborative computing, journalism and bioinformatics as well as for his information-based digital artwork. In his work, the mathematical underpinnings of a computer program are not simply tools used to create art; they are the core of the artworks themselves. [http://www.heise.de/kiosk/archiv/tr/2003/11/36_kiosk Technology Review] recently named him "one of the world's 100 top young innovators." <br />
<br />
Wattenberg's artwork has been exhibited at [http://www.ica.org.uk/ The London Institute of Contemporary Art], [http://whitney.org/ The Whitney Museum of American Art], [http://www.aec.at/ Ars Electronica], [http://www.newmuseum.org/ The New Museum], and at galleries and festivals internationally. Commissions include [http://americanhistory.si.edu/ The Smithsonian National Museum of American History], [http://web.mac.com/stevedean/The_Other_James_Deans_Studio_on_the_Internet/Artwork/Pages/NASA_Space_Art.html The NASA Art Program], [http://new-radio.org/ New Radio and Performing Arts Inc.], [http://www.walkerart.org/ The Walker Art Center] and others. <br />
<br />
His projects have been honored by the Columbia Journalism School Online Journalism Award and the National Magazine Award (with SmartMoney.com), the ID Magazine Interactive Media Design Review, the IDSA Industrial Design Excellence Award, and the Graz Biennale of Media and Architecture (with Marek Walczak). <br />
<br />
Martin Wattenberg and [[Marek_Walczak Marek Walczak]] started 1997 a collaboration called [http://mw2mw.com MW2MW] on which they both continue to present creative work in the field of information-based digital artwork.<br />
<br />
<br />
Previous to his work at IBM, Wattenberg was R&D Director at [http://www.smartmoney.com/ SmartMoney.com] and developed an informative market visualisation, called [http://www.smartmoney.com/map-of-the-market/ Map of the Market] in 1998.<br />
<br />
Wattenberg received his Ph.D. in mathematics from U.C. Berkeley, M.S. from Stanford University, and A.B. from Brown University.<br />
<br />
== External Links ==<br />
*[http://www.bewitched.com/ Martin Wattenberg's Home Page]<br />
*[http://www.research.ibm.com/history/ history flow] Visualizing wiki web document evolution<br />
*[http://babynamewizard.com/namevoyager/ NameVoyager] Java Applet to explore baby names' popularity histories<br />
<br />
== Interesting Work ==<br />
*2008 [http://transition.turbulence.org/spotlight/thinking/chess.html Thinking Machine] a chess game which visualises the thinking process of an AI opponent.<br />
*2008[http://www.fleshmap.com Flesh Map] several visualisations of desire categorized into touch, look and listen. Tries to find answers on questions like "where would we like to be touched" or "what body parts caracterize which music".<br />
*2007 [http://manyeyes.alphaworks.ibm.com/manyeyes/ Many Eyes] a platform which allows everybody to share data, create visualisations, analyze and interpret it in several ways.<br />
*2005 [http://namemapper.babynamewizard.com/namemapper/ Name Voyager] displays the popularity of names over time. <br />
*1998 [http://www.bewitched.com/marketmap.html Map of the Market] an interactive visualisation of stock performance vased on tree maps. <br />
<br />
<br />
== References ==<br />
[Wattenberg, 2005] Martin Wattenberg, www.bewitched.com - About, Retrieved at: August 29, 2005. http://www.bewitched.com/about.html<br />
<br />
<br />
[[Category:Persons]]</div>UE-InfoVis09-04https://infovis-wiki.net/w/index.php?title=File:Martin_headshot_small.jpg&diff=21297File:Martin headshot small.jpg2009-05-14T10:53:13Z<p>UE-InfoVis09-04: Martin Wattenberg - current Portrait from http://www.bewitched.com/</p>
<hr />
<div>== Summary ==<br />
Martin Wattenberg - current Portrait from http://www.bewitched.com/<br />
== Copyright status ==<br />
<br />
== Source ==<br />
http://www.bewitched.com/</div>UE-InfoVis09-04