InfoVis:Wiki - User contributions [en]

Web Based Visual Exploration of Patent Information

2009-05-27T21:53:22Z

UE-InfoVis09-18:

==Motivation==

On the one hand, patents are a well known instrument to protect intellectual properties. On the other hand, there are several aspects which are often neglected by the scientific community: analyzing patent information can lead to e.g. identification of the direction of technical change, forecasts of market values and getting insights into your competitors work and inventions. At present there are about 60 million patent documents existing worldwide mostly comprising natural language supplemented by figures, diagrams, formulas, etc. As a consequence of this, it is needless to allude that computer support is heavily required. Besides this, patent evaluation still takes a lot of human effort. Therefore, it is very important to explore new approaches in software supported retrieval and visualization of patent information. The main goal in this connection is to improve the users cognition processes; e.g. to faster identify potential search results/constraints etc.

==Characteristics of Patent Information==

Because of national patent laws, patent documents are following a well-defined structure arranged on a title page:

* bibliographic data and an abstract
* classificatory data
* description of the state of the art
* claims section
* images, diagrammes, formulae, etc. (optional)

As seen above, patent documents comprise some metadata such as bibliographic data and classificatory data. Nevertheless, for evaluation there often is some further information needed: The legal status and patent family information, which both have to be fetched from external data sources like the [http://www.european-patent-office.org/inpadoc/stats/ Europaean Patent Office]

===Legal Status===
The legal status specifies significant events in the lifetime of a patent like changes of the owner etc.

===Patent Family===
Patents which describe the same invention belong to the same patent family. A common definition says that a patent document belongs to a respective patent family if the claims section and priorities of this document are matching the other patents claims and priorities of this family (e.g. protecting an invention in different countries).

===Classificatory Data===
The [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] (IPC) is the number one classification scheme of patent documents for ordering them in terms of technical fields. Therefore the IPC comprises 68.000 (advanced) or 17.000 (core) categories and is hierarchically organized in 13 levels.

==Visualization Techniques==

===Mass-Spring Graphs===

[[{{ns:6}}:Massspringgraph.gif |thumb|right|300px|'''Figure 1''': A Mass-Spring Graph]]

During search, it is often a matter of concern to identify clusters or groups e.g. patents that are related to each other by different criteria (same category, same inventor, etc.) and visualize them in an appropriate manner. A common way to do this are (interactive) mass-spring graphs. They are an adequate and intuitive form of visualizing clusters and interrelations between paticular nodes. To simulate the physics of this kind of force-directed graphs, you can use the [http://en.wikipedia.org/wiki/Barnes-Hut_simulation Barnes-Hut Algorithm] that allows efficient n-body force calculations in O(n log n) time.

'''Figure 1''' shows the relationship between patents (yellow) and their corresponding priority document (brown). In the special case of patent documents it is thus possible to i.e. easily identify the priority applications that have been the groundwork for other patents. In gereral, mass-spring graphs are suitable for search through all kinds of [http://www.infovis-wiki.net/index.php?title=Category:Hierarchical_Data hierarchically data] to show their interrelationships.

====Demonstrations of Related Work and Mass-Spring Graphs====

* [http://christopherbaker.net/2007/03/22/patent-database-visualization/ Patent Database Visualization of Christopher Baker]
* [http://www.youtube.com/watch?v=m-lLPvXeCfY Demo of another Mass-Spring Graph Application]

===Patent Family Layout===

[[{{ns:6}}:patent family layout.jpg |thumb|right|300px|'''Figure 2''': Patent Family Layout]]

Next to the mass-spring graph, the patent family layout is also part of visually clustering patent sets. It is based on filling date and country in an interactive 2D matrix that are represented as red and blue nodes. The filing date of the patents and priorities are shown on the horizontal position (x-axis). On vertical position, every line describes a country or organization where the patents or priorities have been filed. Arcs will point from a patent to it's priority document and the priority relations are visualized if a node is selected. To get a quick overview of often referenced documents, the node size displays the number of ingoing arcs of the node.

===Visualization of Classificatory Information using Treemaps===

[[{{ns:6}}:Class.gif |thumb|right|300px|'''Figure 3''': Treemap of Classificatory Data of Patent Information]]

With a treemap it is possible to show the hierarchical structure of the [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] IPC. The IPC categories are rendered as nested rectangular areas, which help to keep a clear view of the used categories in large patent sets. To get more information and further details it is possible to zoom into specific parts for an enlargment of the specific labels. An alleviation in these technique is to search for keywords in the titles of IPC categories. The search results are shown as a list and in the treemap as rectangles with red and green filling. The red items are not part of the patent set, the green items are part of the patent set.

====Related Topics====

* [http://www.infovis-wiki.net/index.php?title=Treemap More Info on Treemaps]
* [http://www.infovis-wiki.net/index.php?title=Extreme_visualization:_squeezing_a_billion_records_into_a_million_pixels Squeezing a Billion Records Into a Million Pixels]

==Constraints of Web Application Development==

There exists serveral problems or constraints in developing interactive visualizations that are accessible via a web browser:

* heterogenity of client software (different browsers, plugins)
* infrastructure (low bandwidth, firewalls)
* inactive javascript

To fit this constraints and the needs of potential users as much as possible, it is necessary to implement and design a web application (especially web based graphical representations) in multiple manners:

===Java Applets===

* + rich interaction capabilities
* - Java Plugin
* - download time

===Raster Graphics with HTML Image Maps===

* + no additional client software
* + suitable for old browsers
* - less interactiv capabilities

===Rich Internet Applications with AJAX and SVG===

* + no additional client software
* + fast
* + lots of libraries and animation frameworks
* + rich interaction capabilities
* - [http://alexbosworth.backpackit.com/pub/67688 several drawbacks in using AJAX]

==Former Efforts==

In the last few years, analyzing specific areas of patent knowledge spaces by exploiting author co-citations and semantic similarities between patent documents have been important activities for data reduction and visualization. The activities are using methods like multidimensional scaling, factor analysis, or organizing maps which are related to the field of scientometrics. Moreover, there have been serveral approaches in visualizing patent e.g. representations of patent related social networks showing the relationships between inventors, applicants and companies and representations of classificatory information using treemaps.

===Commercial Products===

* [http://thomsonreuters.com/products_services/scientific/Aureka Aureka]
* [http://www.delphion.com/products/research/products-citelink Citation Link]
* [http://www.matheo-analyzer.com/ Matheo Analyzer]

==Authors & Reference==

* [http://www.infovis-wiki.net/index.php?title=Giereth%2C_Mark Mark Giereth]
* Steffen Koch
* [http://www.infovis-wiki.net/index.php?title=Rotard%2C_Martin Martin Rotard]
* Thomas Ertl

This article ist based on the paper:

Giereth, M. et. al.: ''Web Based Visual Exploration of Patent Information'', 11th International Conference Information Visualization (IV'07)

Univertity of Stuttgart, Visualization and Interactive Systems Institute, Germany, 2007

[http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Flpdocs%2Fepic03%2Fwrapper.htm%3Farnumber%3D4271975&authDecision=-203 Download on IEEE]

===PatExpert===

For further information on patent information work visit [http://www.patexpert.org www.patexpert.org]. Unfortunately it is impossible to bookmark specific links of this website. A link to a demonstration video of the visualization techniques described above can be found on the bottom of the website.
[[Category:Techniques]]

Web Based Visual Exploration of Patent Information

2009-05-27T16:42:00Z

UE-InfoVis09-18:

==Motivation==

On the one hand, patents are a well known instrument to protect intellectual properties. On the other hand, there are several aspects which are often neglected by the scientific community: analyzing patent information can lead to e.g. identification of the direction of technical change, forecasts of market values and getting insights into your competitors work and inventions. At present there are about 60 million patent documents existing worldwide mostly comprising natural language supplemented by figures, diagrams, formulas, etc. As a consequence of this, it is needless to allude that computer support is heavily required. Besides this, patent evaluation still takes a lot of human effort. Therefore, it is very important to explore new approaches in software supported retrieval and visualization of patent information. The main goal in this connection is to improve the users cognition processes; e.g. to faster identify potential search results/constraints etc.

==Characteristics of Patent Information==

Because of national patent laws, patent documents are following a well-defined structure arranged on a title page:

* bibliographic data and an abstract
* classificatory data
* description of the state of the art
* claims section
* images, diagrammes, formulae, etc. (optional)

As seen above, patent documents comprise some metadata such as bibliographic data and classificatory data. Nevertheless, for evaluation there often is some further information needed: The legal status and patent family information, which both have to be fetched from external data sources like the [http://www.european-patent-office.org/inpadoc/stats/ Europaean Patent Office]

===Legal Status===
The legal status specifies significant events in the lifetime of a patent like changes of the owner etc.

===Patent Family===
Patents which describe the same invention belong to the same patent family. A common definition says that a patent document belongs to a respective patent family if the claims section and priorities of this document are matching the other patents claims and priorities of this family (e.g. protecting an invention in different countries).

===Classificatory Data===
The [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] (IPC) is the number one classification scheme of patent documents for ordering them in terms of technical fields. Therefore the IPC comprises 68.000 (advanced) or 17.000 (core) categories and is hierarchically organized in 13 levels.

==Visualization Techniques==

===Mass-Spring Graphs===

[[{{ns:6}}:Massspringgraph.gif |thumb|right|300px|'''Figure 1''': A Mass-Spring Graph]]

During search, it is often a matter of concern to identify clusters or groups e.g. patents that are related to each other by different criteria (same category, same inventor, etc.) and visualize them in an appropriate manner. A common way to do this are (interactive) mass-spring graphs. They are an adequate and intuitive form of visualizing clusters and interrelations between paticular nodes. To simulate the physics of this kind of force-directed graphs, you can use the [http://en.wikipedia.org/wiki/Barnes-Hut_simulation Barnes-Hut Algorithm] that allows efficient n-body force calculations in O(n log n) time.

'''Figure 1''' shows the relationship between patents (yellow) and their corresponding priority document (brown). In the special case of patent documents it is thus possible to i.e. easily identify the priority applications that have been the groundwork for other patents. In gereral, mass-spring graphs are suitable for search through all kinds of [http://www.infovis-wiki.net/index.php?title=Category:Hierarchical_Data hierarchically data] to show their interrelationships.

====Demonstrations of Related Work and Mass-Spring Graphs====

* [http://christopherbaker.net/2007/03/22/patent-database-visualization/ Patent Database Visualization of Christopher Baker]
* [http://www.youtube.com/watch?v=m-lLPvXeCfY Demo of another Mass-Spring Graph Application]

===Patent Family Layout===

[[{{ns:6}}:patent family layout.jpg |thumb|right|300px|'''Figure 2''': Patent Family Layout]]

Next to the mass-spring graph, the patent family layout is also part of visually clustering patent sets. It is based on filling date and country in an interactive 2D matrix that are represented as red and blue nodes. The filing date of the patents and priorities are shown on the horizontal position (x-axis). On vertical position, every line describes a country or organization where the patents or priorities have been filed. Arcs will point from a patent to it's priority document and the priority relations are visualized if a node is selected. To get a quick overview of often referenced documents, the node size displays the number of ingoing arcs of the node.

===Visualization of Classificatory Information using Treemaps===

[[{{ns:6}}:Class.gif |thumb|right|300px|'''Figure 3''': Treemap of Classificatory Data of Patent Information]]

With a treemap it is possible to show the hierarchical structure of the [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] IPC. The IPC categories are rendered as nested rectangular areas, which help to keep a clear view of the used categories in large patent sets. To get more information and further details it is possible to zoom into specific parts for an enlargment of the specific labels. An alleviation in these technique is to search for keywords in the titles of IPC categories. The search results are shown as a list and in the treemap as rectangles with red and green filling. The red items are not part of the patent set, the green items are part of the patent set.

====Related Topics====

* [http://www.infovis-wiki.net/index.php?title=Treemap More Info on Treemaps]
* [http://www.infovis-wiki.net/index.php?title=Extreme_visualization:_squeezing_a_billion_records_into_a_million_pixels Squeezing a Billion Records Into a Million Pixels]

==Constraints of Web Application Development==

There exists serveral problems or constraints in developing interactive visualizations that are accessible via a web browser:

* heterogenity of client software (different browsers, plugins)
* infrastructure (low bandwidth, firewalls)
* inactive javascript

To fit this constraints and the needs of potential users as much as possible, it is necessary to implement and design a web application (especially web based graphical representations) in multiple manners:

===Java Applets===

* + rich interaction capabilities
* - Java Plugin
* - download time

===Raster Graphics with HTML Image Maps===

* + no additional client software
* + suitable for old browsers
* - less interactiv capabilities

===Rich Internet Applications with AJAX and SVG===

* + no additional client software
* + fast
* + lots of libraries and animation frameworks
* + rich interaction capabilities
* - [http://alexbosworth.backpackit.com/pub/67688 several drawbacks in using AJAX]

==Former Efforts==

In the last few years, analyzing specific areas of patent knowledge spaces by exploiting author co-citations and semantic similarities between patent documents have been important activities for data reduction and visualization. The activities are using methods like multidimensional scaling, factor analysis, or organizing maps which are related to the field of scientometrics. Moreover, there have been serveral approaches in visualizing patent e.g. representations of patent related social networks showing the relationships between inventors, applicants and companies and representations of classificatory information using treemaps.

===Commercial Products===

* Aureka
* Citation Link
* Matheo Analyzer

==Authors & Reference==

* [http://www.infovis-wiki.net/index.php?title=Giereth%2C_Mark Mark Giereth]
* Steffen Koch
* [http://www.infovis-wiki.net/index.php?title=Rotard%2C_Martin Martin Rotard]
* Thomas Ertl

This article ist based on the paper:

Giereth, M. et. al.: ''Web Based Visual Exploration of Patent Information'', 11th International Conference Information Visualization (IV'07)

Univertity of Stuttgart, Visualization and Interactive Systems Institute, Germany, 2007

[http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Flpdocs%2Fepic03%2Fwrapper.htm%3Farnumber%3D4271975&authDecision=-203 Download on IEEE]

===PatExpert===

For further information on patent information work visit [http://www.patexpert.org www.patexpert.org]. Unfortunately it is impossible to bookmark specific links of this website. A link to a demonstration video of the visualization techniques described above can be found on the bottom of the website.
[[Category:Techniques]]

Web Based Visual Exploration of Patent Information

2009-05-27T16:40:38Z

UE-InfoVis09-18:

==Motivation==

On the one hand, patents are a well known instrument to protect intellectual properties. On the other hand, there are several aspects which are often neglected by the scientific community: analyzing patent information can lead to e.g. identification of the direction of technical change, forecasts of market values and getting insights into your competitors work and inventions. At present there are about 60 million patent documents existing worldwide mostly comprising natural language supplemented by figures, diagrams, formulas, etc. As a consequence of this, it is needless to allude that computer support is heavily required. Besides this, patent evaluation still takes a lot of human effort. Therefore, it is very important to explore new approaches in software supported retrieval and visualization of patent information. The main goal in this connection is to improve the users cognition processes; e.g. to faster identify potential search results/constraints etc.

==Characteristics of Patent Information==

Because of national patent laws, patent documents are following a well-defined structure arranged on a title page:

* bibliographic data and an abstract
* classificatory data
* description of the state of the art
* claims section
* images, diagrammes, formulae, etc. (optional)

As seen above, patent documents comprise some metadata such as bibliographic data and classificatory data. Nevertheless, for evaluation there often is some further information needed: The legal status and patent family information, which both have to be fetched from external data sources like the [http://www.european-patent-office.org/inpadoc/stats/ Europaean Patent Office]

===Legal Status===
The legal status specifies significant events in the lifetime of a patent like changes of the owner etc.

===Patent Family===
Patents which describe the same invention belong to the same patent family. A common definition says that a patent document belongs to a respective patent family if the claims section and priorities of this document are matching the other patents claims and priorities of this family (e.g. protecting an invention in different countries).

===Classificatory Data===
The [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] (IPC) is the number one classification scheme of patent documents for ordering them in terms of technical fields. Therefore the IPC comprises 68.000 (advanced) or 17.000 (core) categories and is hierarchically organized in 13 levels.

==Visualization Techniques==

===Mass-Spring Graphs===

[[{{ns:6}}:Massspringgraph.gif |thumb|right|300px|'''Figure 1''': A Mass-Spring Graph]]

During search, it is often a matter of concern to identify clusters or groups e.g. patents that are related to each other by different criteria (same category, same inventor, etc.) and visualize them in an appropriate manner. A common way to do this are (interactive) mass-spring graphs. They are an adequate and intuitive form of visualizing clusters and interrelations between paticular nodes. To simulate the physics of this kind of force-directed graphs, you can use the [http://en.wikipedia.org/wiki/Barnes-Hut_simulation Barnes-Hut Algorithm] that allows efficient n-body force calculations in O(n log n) time.

'''Figure 1''' shows the relationship between patents (yellow) and their corresponding priority document (brown). In the special case of patent documents it is thus possible to i.e. easily identify the priority applications that have been the groundwork for other patents. In gereral, mass-spring graphs are suitable for search through all kinds of [http://www.infovis-wiki.net/index.php?title=Category:Hierarchical_Data hierarchically data] to show their interrelationships.

====Demonstrations of Related Work and Mass-Spring Graphs====

* [http://christopherbaker.net/2007/03/22/patent-database-visualization/ Patent Database Visualization of Christopher Baker]
* [http://www.youtube.com/watch?v=m-lLPvXeCfY Demo of another Mass-Spring Graph Application]

===Patent Family Layout===

[[{{ns:6}}:patent family layout.jpg |thumb|right|300px|'''Figure 2''': Patent Family Layout]]

Next to the mass-spring graph, the patent family layout is also part of visually clustering patent sets. It is based on filling date and country in an interactive 2D matrix that are represented as red and blue nodes. The filing date of the patents and priorities are shown on the horizontal position (x-axis). On vertical position, every line describes a country or organization where the patents or priorities have been filed. Arcs will point from a patent to it's priority document and the priority relations are visualized if a node is selected. To get a quick overview of often referenced documents, the node size displays the number of ingoing arcs of the node.

===Visualization of Classificatory Information using Treemaps===

[[{{ns:6}}:Class.gif |thumb|right|300px|'''Figure 3''': Treemap of Classificatory Data of Patent Information]]

With a treemap it is possible to show the hierarchical structure of the [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] IPC. The IPC categories are rendered as nested rectangular areas, which help to keep a clear view of the used categories in large patent sets. To get more information and further details it is possible to zoom into specific parts for an enlargment of the specific labels. An alleviation in these technique is to search for keywords in the titles of IPC categories. The search results are shown as a list and in the treemap as rectangles with red and green filling. The red items are not part of the patent set, the green items are part of the patent set.

====Related Topics====

* [http://www.infovis-wiki.net/index.php?title=Treemap More Info on Treemaps]
* [http://www.infovis-wiki.net/index.php?title=Extreme_visualization:_squeezing_a_billion_records_into_a_million_pixels Squeezing a Billion Records Into a Million Pixels]

==Constraints of Web Application Development==

There exists serveral problems or constraints in developing interactive visualizations that are accessible via a web browser:

* heterogenity of client software (different browsers, plugins)
* infrastructure (low bandwidth, firewalls)
* inactive javascript

To fit this constraints and the needs of potential users as much as possible, it is necessary to implement and design a web application (especially web based graphical representations) in multiple manners:

===Java Applets===

* + rich interaction capabilities
* - Java Plugin
* - download time

===Raster Graphics with HTML Image Maps===

* + no additional client software
* + suitable for old browsers
* - less interactiv capabilities

===Rich Internet Applications with AJAX and SVG===

* + no additional client software
* + fast
* + lots of libraries and animation frameworks
* + rich interaction capabilities
* - [http://alexbosworth.backpackit.com/pub/67688 several drawbacks in using AJAX]

==Former Efforts==

In the last few years, analyzing specific areas of patent knowledge spaces by exploiting author co-citations and semantic similarities between patent documents have been important activities for data reduction and visualization. The activities are using methods like multidimensional scaling, factor analysis, or organizing maps which are related to the field of scientometrics. Moreover, there have been serveral approaches in visualizing patent e.g. representations of patent related social networks showing the relationships between inventors, applicants and companies and representations of classificatory information using treemaps.

===Commercial Products===

* Aureka
* Citation Link
* Matheo Analyzer

==Authors & Reference==

* [http://www.infovis-wiki.net/index.php?title=Giereth%2C_Mark Mark Giereth]
* Steffen Koch
* [http://www.infovis-wiki.net/index.php?title=Rotard%2C_Martin Martin Rotard]
* Thomas Ertl

This article ist based on the paper:

Giereth, M. et. al.: ''Web Based Visual Exploration of Patent Information'', 11th International Conference Information Visualization (IV'07)

Univertity of Stuttgart, Visualization and Interactive Systems Institute, Germany, 2007

[http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Flpdocs%2Fepic03%2Fwrapper.htm%3Farnumber%3D4271975&authDecision=-203 Download on IEEE]

===PatExpert===

For further information on patent information visit [http://www.patexpert.org]. Unfortunately it is impossible to bookmark specific links of this website. A link to a demonstration video of the visualization techniques described above can be found on the bottom of the website.
[[Category:Techniques]]

Web Based Visual Exploration of Patent Information

2009-05-27T16:27:50Z

UE-InfoVis09-18:

==Motivation==

On the one hand, patents are a well known instrument to protect intellectual properties. On the other hand, there are several aspects which are often neglected by the scientific community: analyzing patent information can lead to e.g. identification of the direction of technical change, forecasts of market values and getting insights into your competitors work and inventions. At present there are about 60 million patent documents existing worldwide mostly comprising natural language supplemented by figures, diagrams, formulas, etc. As a consequence of this, it is needless to allude that computer support is heavily required. Besides this, patent evaluation still takes a lot of human effort. Therefore, it is very important to explore new approaches in software supported retrieval and visualization of patent information. The main goal in this connection is to improve the users cognition processes; e.g. to faster identify potential search results/constraints etc.

==Characteristics of Patent Information==

Because of national patent laws, patent documents are following a well-defined structure arranged on a title page:

* bibliographic data and an abstract
* classificatory data
* description of the state of the art
* claims section
* images, diagrammes, formulae, etc. (optional)

As seen above, patent documents comprise some metadata such as bibliographic data and classificatory data. Nevertheless, for evaluation there often is some further information needed: The legal status and patent family information, which both have to be fetched from external data sources like the [http://www.european-patent-office.org/inpadoc/stats/ Europaean Patent Office]

===Legal Status===
The legal status specifies significant events in the lifetime of a patent like changes of the owner etc.

===Patent Family===
Patents which describe the same invention belong to the same patent family. A common definition says that a patent document belongs to a respective patent family if the claims section and priorities of this document are matching the other patents claims and priorities of this family (e.g. protecting an invention in different countries).

===Classificatory Data===
The [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] (IPC) is the number one classification scheme of patent documents for ordering them in terms of technical fields. Therefore the IPC comprises 68.000 (advanced) or 17.000 (core) categories and is hierarchically organized in 13 levels.

==Visualization Techniques==

===Mass-Spring Graphs===

[[{{ns:6}}:Massspringgraph.gif |thumb|right|300px|'''Figure 1''': A Mass-Spring Graph]]

During search, it is often a matter of concern to identify clusters or groups e.g. patents that are related to each other by different criteria (same category, same inventor, etc.) and visualize them in an appropriate manner. A common way to do this are (interactive) mass-spring graphs. They are an adequate and intuitive form of visualizing clusters and interrelations between paticular nodes. To simulate the physics of this kind of force-directed graphs, you can use the [http://en.wikipedia.org/wiki/Barnes-Hut_simulation Barnes-Hut Algorithm] that allows efficient n-body force calculations in O(n log n) time.

'''Figure 1''' shows the relationship between patents (yellow) and their corresponding priority document (brown). In the special case of patent documents it is thus possible to i.e. easily identify the priority applications that have been the groundwork for other patents. In gereral, mass-spring graphs are suitable for search through all kinds of [http://www.infovis-wiki.net/index.php?title=Category:Hierarchical_Data hierarchically data] to show their interrelationships.

====Demonstrations of Related Work and Mass-Spring Graphs====

* [http://christopherbaker.net/2007/03/22/patent-database-visualization/ Patent Database Visualization of Christopher Baker]
* [http://www.youtube.com/watch?v=m-lLPvXeCfY Demo of another Mass-Spring Graph Application]

===Patent Family Layout===

[[{{ns:6}}:patent family layout.jpg |thumb|right|300px|'''Figure 2''': Patent Family Layout]]

Next to the mass-spring graph, the patent family layout is also part of visually clustering patent sets. It is based on filling date and country in an interactive 2D matrix that are represented as red and blue nodes. The filing date of the patents and priorities are shown on the horizontal position (x-axis). On vertical position, every line describes a country or organization where the patents or priorities have been filed. Arcs will point from a patent to it's priority document and the priority relations are visualized if a node is selected. To get a quick overview of often referenced documents, the node size displays the number of ingoing arcs of the node.

===Visualization of Classificatory Information using Treemaps===

[[{{ns:6}}:Class.gif |thumb|right|300px|'''Figure 3''': Treemap of Classificatory Data of Patent Information]]

With a treemap it is possible to show the hierarchical structure of the [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] IPC. The IPC categories are rendered as nested rectangular areas, which help to keep a clear view of the used categories in large patent sets. To get more information and further details it is possible to zoom into specific parts for an enlargment of the specific labels. An alleviation in these technique is to search for keywords in the titles of IPC categories. The search results are shown as a list and in the treemap as rectangles with red and green filling. The red items are not part of the patent set, the green items are part of the patent set.

====Related Topics====

* [http://www.infovis-wiki.net/index.php?title=Treemap More Info on Treemaps]
* [http://www.infovis-wiki.net/index.php?title=Extreme_visualization:_squeezing_a_billion_records_into_a_million_pixels Squeezing a Billion Records Into a Million Pixels]

==Constraints of Web Application Development==

There exists serveral problems or constraints in developing interactive visualizations that are accessible via a web browser:

* heterogenity of client software (different browsers, plugins)
* infrastructure (low bandwidth, firewalls)
* inactive javascript

To fit this constraints and the needs of potential users as much as possible, it is necessary to implement and design a web application (especially web based graphical representations) in multiple manners:

===Java Applets===

* + rich interaction capabilities
* - Java Plugin
* - download time

===Raster Graphics with HTML Image Maps===

* + no additional client software
* + suitable for old browsers
* - less interactiv capabilities

===Rich Internet Applications with AJAX and SVG===

* + no additional client software
* + fast
* + lots of libraries and animation frameworks
* + rich interaction capabilities
* - [http://alexbosworth.backpackit.com/pub/67688 several drawbacks in using AJAX]

==Former Efforts==

In the last few years, analyzing specific areas of patent knowledge spaces by exploiting author co-citations and semantic similarities between patent documents have been important activities for data reduction and visualization. The activities are using methods like multidimensional scaling, factor analysis, or organizing maps which are related to the field of scientometrics. Moreover, there have been serveral approaches in visualizing patent e.g. representations of patent related social networks showing the relationships between inventors, applicants and companies and representations of classificatory information using treemaps.

===Commercial Products===

* Aureka
* Citation Link
* Matheo Analyzer

==Authors==

* [http://www.infovis-wiki.net/index.php?title=Giereth%2C_Mark Mark Giereth]
* Steffen Koch
* [http://www.infovis-wiki.net/index.php?title=Rotard%2C_Martin Martin Rotard]
* Thomas Ertl

This article ist based on the paper:

Giereth, M. et. al.: Web Based Visual Exploration of Patent Information, 11th International Conference Information Visualization (IV'07)

Univertity of Stuttgart, Visualization and Interactive Systems Institute, Germany, 2007

[http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Flpdocs%2Fepic03%2Fwrapper.htm%3Farnumber%3D4271975&authDecision=-203 Download on IEEE]

[[Category:Techniques]]

Web Based Visual Exploration of Patent Information

2009-05-27T16:26:34Z

UE-InfoVis09-18:

==Motivation==

On the one hand, patents are a well known instrument to protect intellectual properties. On the other hand, there are several aspects which are often neglected by the scientific community: analyzing patent information can lead to e.g. identification of the direction of technical change, forecasts of market values and getting insights into your competitors work and inventions. At present there are about 60 million patent documents existing worldwide mostly comprising natural language supplemented by figures, diagrams, formulas, etc. As a consequence of this, it is needless to allude that computer support is heavily required. Besides this, patent evaluation still takes a lot of human effort. Therefore, it is very important to explore new approaches in software supported retrieval and visualization of patent information. The main goal in this connection is to improve the users cognition processes; e.g. to faster identify potential search results/constraints etc.

==Characteristics of Patent Information==

Because of national patent laws, patent documents are following a well-defined structure arranged on a title page:

* bibliographic data and an abstract
* classificatory data
* description of the state of the art
* claims section
* images, diagrammes, formulae, etc. (optional)

As seen above, patent documents comprise some metadata such as bibliographic data and classificatory data. Nevertheless, for evaluation there often is some further information needed: The legal status and patent family information, which both have to be fetched from external data sources like the [http://www.european-patent-office.org/inpadoc/stats/ Europaean Patent Office]

===Legal Status===
The legal status specifies significant events in the lifetime of a patent like changes of the owner etc.

===Patent Family===
Patents which describe the same invention belong to the same patent family. A common definition says that a patent document belongs to a respective patent family if the claims section and priorities of this document are matching the other patents claims and priorities of this family (e.g. protecting an invention in different countries).

===Classificatory Data===
The [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] (IPC) is the number one classification scheme of patent documents for ordering them in terms of technical fields. Therefore the IPC comprises 68.000 (advanced) or 17.000 (core) categories and is hierarchically organized in 13 levels.

==Visualization Techniques==

===Mass-Spring Graphs===

[[{{ns:6}}:Massspringgraph.gif |thumb|right|300px|'''Figure 1''': A Mass-Spring Graph]]

During search, it is often a matter of concern to identify clusters or groups e.g. patents that are related to each other by different criteria (same category, same inventor, etc.) and visualize them in an appropriate manner. A common way to do this are (interactive) mass-spring graphs. They are an adequate and intuitive form of visualizing clusters and interrelations between paticular nodes. To simulate the physics of this kind of force-directed graphs, you can use the [http://en.wikipedia.org/wiki/Barnes-Hut_simulation Barnes-Hut Algorithm] that allows efficient n-body force calculations in O(n log n) time.

'''Figure 1''' shows the relationship between patents (yellow) and their corresponding priority document (brown). In the special case of patent documents it is thus possible to i.e. easily identify the priority applications that have been the groundwork for other patents. In gereral, mass-spring graphs are suitable for search through all kinds of [http://www.infovis-wiki.net/index.php?title=Category:Hierarchical_Data hierarchically data] to show their interrelationships.

====Demonstrations of Related Work and Mass-Spring Graphs====

* [http://christopherbaker.net/2007/03/22/patent-database-visualization/ Patent Database Visualization of Christopher Baker]
* [http://www.youtube.com/watch?v=m-lLPvXeCfY Demo of another Mass-Spring Graph Application]

===Patent Family Layout===

[[{{ns:6}}:patent family layout.jpg |thumb|right|300px|'''Figure 2''': Patent Family Layout]]

Next to the mass-spring graph, the patent family layout is also part of visually clustering patent sets. It is based on filling date and country in an interactive 2D matrix that are represented as red and blue nodes. The filing date of the patents and priorities are shown on the horizontal position (x-axis). On vertical position, every line describes a country or organization where the patents or priorities have been filed. Arcs will point from a patent to it's priority document and the priority relations are visualized if a node is selected. To get a quick overview of often referenced documents, the node size displays the number of ingoing arcs of the node.

===Visualization of Classificatory Information using Treemaps===

[[{{ns:6}}:Class.gif |thumb|right|300px|'''Figure 3''': Treemap of Classificatory Data of Patent Information]]

With a treemap it is possible to show the hierarchical structure of the [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] IPC. The IPC categories are rendered as nested rectangular areas, which help to keep a clear view of the used categories in large patent sets. To get more information and further details it is possible to zoom into specific parts for an enlargment of the specific labels. An alleviation in these technique is to search for keywords in the titles of IPC categories. The search results are shown as a list and in the treemap as rectangles with red and green filling. The red items are not part of the patent set, the green items are part of the patent set.

====Related Topics====

* [http://www.infovis-wiki.net/index.php?title=Treemap More Info on Treemaps]
* [http://www.infovis-wiki.net/index.php?title=Extreme_visualization:_squeezing_a_billion_records_into_a_million_pixels Squeezing a Billion Records Into a Million Pixels]

==Constraints of Web Application Development==

There exists serveral problems or constraints in developing interactive visualizations that are accessible via a web browser:

* heterogenity of client software (different browsers, plugins)
* infrastructure (low bandwidth, firewalls)
* inactive javascript

To fit this constraints and the needs of potential users as much as possible, it is necessary to implement and design a web application (especially web based graphical representations) in multiple manners:

===Java Applets===

* + rich interaction capabilities
* - Java Plugin
* - download time

===Raster Graphics with HTML Image Maps===

* + no additional client software
* + suitable for old browsers
* - less interactiv capabilities

===Rich Internet Applications with AJAX and SVG===

* + no additional client software
* + fast
* + lots of libraries and animation frameworks
* + rich interaction capabilities
* - [http://alexbosworth.backpackit.com/pub/67688 several drawbacks in using AJAX]

==Former Efforts==

In the last few years, analyzing specific areas of patent knowledge spaces by exploiting author co-citations and semantic similarities between patent documents have been important activities for data reduction and visualization. The activities are using methods like multidimensional scaling, factor analysis, or organizing maps which are related to the field of scientometrics. Moreover, there have been serveral approaches in visualizing patent e.g. representations of patent related social networks showing the relationships between inventors, applicants and companies and representations of classificatory information using treemaps.

===former commercial products===

* Aureka
* Citation Link
* Matheo Analyzer

==Authors==
* [http://www.infovis-wiki.net/index.php?title=Giereth%2C_Mark Mark Giereth]
* Steffen Koch
* [http://www.infovis-wiki.net/index.php?title=Rotard%2C_Martin Martin Rotard]
* Thomas Ertl

This article ist based on the paper:

Giereth, M. et. al.: Web Based Visual Exploration of Patent Information, 11th International Conference Information Visualization (IV'07)

Univertity of Stuttgart, Visualization and Interactive Systems Institute, Germany, 2007

[http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Flpdocs%2Fepic03%2Fwrapper.htm%3Farnumber%3D4271975&authDecision=-203 Download on IEEE]

[[Category:Techniques]]

Web Based Visual Exploration of Patent Information

2009-05-27T16:25:24Z

UE-InfoVis09-18:

==Motivation==

On the one hand, patents are a well known instrument to protect intellectual properties. On the other hand, there are several aspects which are often neglected by the scientific community: analyzing patent information can lead to e.g. identification of the direction of technical change, forecasts of market values and getting insights into your competitors work and inventions. At present there are about 60 million patent documents existing worldwide mostly comprising natural language supplemented by figures, diagrams, formulas, etc. As a consequence of this, it is needless to allude that computer support is heavily required. Besides this, patent evaluation still takes a lot of human effort. Therefore, it is very important to explore new approaches in software supported retrieval and visualization of patent information. The main goal in this connection is to improve the users cognition processes; e.g. to faster identify potential search results/constraints etc.

==Characteristics of Patent Information==

Because of national patent laws, patent documents are following a well-defined structure arranged on a title page:

* bibliographic data and an abstract
* classificatory data
* description of the state of the art
* claims section
* images, diagrammes, formulae, etc. (optional)

As seen above, patent documents comprise some metadata such as bibliographic data and classificatory data. Nevertheless, for evaluation there often is some further information needed: The legal status and patent family information, which both have to be fetched from external data sources like the [http://www.european-patent-office.org/inpadoc/stats/ Europaean Patent Office]

===Legal Status===
The legal status specifies significant events in the lifetime of a patent like changes of the owner etc.

===Patent Family===
Patents which describe the same invention belong to the same patent family. A common definition says that a patent document belongs to a respective patent family if the claims section and priorities of this document are matching the other patents claims and priorities of this family (e.g. protecting an invention in different countries).

===Classificatory Data===
The [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] (IPC) is the number one classification scheme of patent documents for ordering them in terms of technical fields. Therefore the IPC comprises 68.000 (advanced) or 17.000 (core) categories and is hierarchically organized in 13 levels.

==Visualization Techniques==

===Mass-Spring Graphs===

[[{{ns:6}}:Massspringgraph.gif |thumb|right|300px|'''Figure 1''': A Mass-Spring Graph]]

During search, it is often a matter of concern to identify clusters or groups e.g. patents that are related to each other by different criteria (same category, same inventor, etc.) and visualize them in an appropriate manner. A common way to do this are (interactive) mass-spring graphs. They are an adequate and intuitive form of visualizing clusters and interrelations between paticular nodes. To simulate the physics of this kind of force-directed graphs, you can use the [http://en.wikipedia.org/wiki/Barnes-Hut_simulation Barnes-Hut Algorithm] that allows efficient n-body force calculations in O(n log n) time.

'''Figure 1''' shows the relationship between patents (yellow) and their corresponding priority document (brown). In the special case of patent documents it is thus possible to i.e. easily identify the priority applications that have been the groundwork for other patents. In gereral, mass-spring graphs are suitable for search through all kinds of [http://www.infovis-wiki.net/index.php?title=Category:Hierarchical_Data hierarchically data] to show their interrelationships.

====Demonstrations of Related Work and Mass-Spring Graphs====

* [http://christopherbaker.net/2007/03/22/patent-database-visualization/ Patent Database Visualization of Christopher Baker]
* [http://www.youtube.com/watch?v=m-lLPvXeCfY Demo of another Mass-Spring Graph Application]

===Patent Family Layout===

[[{{ns:6}}:patent family layout.jpg |thumb|right|300px|'''Figure 2''': Patent Family Layout]]

Next to the mass-spring graph, the patent family layout is also part of visually clustering patent sets. It is based on filling date and country in an interactive 2D matrix that are represented as red and blue nodes. The filing date of the patents and priorities are shown on the horizontal position (x-axis). On vertical position, every line describes a country or organization where the patents or priorities have been filed. Arcs will point from a patent to it's priority document and the priority relations are visualized if a node is selected. To get a quick overview of often referenced documents, the node size displays the number of ingoing arcs of the node.

===Visualization of Classificatory Information using Treemaps===

[[{{ns:6}}:Class.gif |thumb|right|300px|'''Figure 3''': Treemap of Classificatory Data of Patent Information]]

With a treemap it is possible to show the hierarchical structure of the [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] IPC. The IPC categories are rendered as nested rectangular areas, which help to keep a clear view of the used categories in large patent sets. To get more information and further details it is possible to zoom into specific parts for an enlargment of the specific labels. An alleviation in these technique is to search for keywords in the titles of IPC categories. The search results are shown as a list and in the treemap as rectangles with red and green filling. The red items are not part of the patent set, the green items are part of the patent set.

====Related Topics====

* [http://www.infovis-wiki.net/index.php?title=Treemap More Info on Treemaps]
* [http://www.infovis-wiki.net/index.php?title=Extreme_visualization:_squeezing_a_billion_records_into_a_million_pixels Squeezing a Billion Records Into a Million Pixels]

==Constraints of Web Application Development==

There exists serveral problems or constraints in developing interactive visualizations that are accessible via a web browser:

* heterogenity of client software (different browsers, plugins)
* infrastructure (low bandwidth, firewalls)
* inactive javascript

To fit this constraints and the needs of potential users as much as possible, it is necessary to implement and design a web application (especially web based graphical representations) in multiple manners:

===Java Applets===

* + rich interaction capabilities
* - Java Plugin
* - download time

===Raster Graphics with HTML Image Maps===

* + no additional client software
* + suitable for old browsers
* - less interactiv capabilities

===Rich Internet Applications with AJAX and SVG===

* + no additional client software
* + fast
* + lots of libraries and animation frameworks
* + rich interaction capabilities
* - [http://alexbosworth.backpackit.com/pub/67688 several drawbacks in using AJAX]

==Former Efforts==

In the last few years, analyzing specific areas of patent knowledge spaces by exploiting author co-citations and semantic similarities between patent documents have been important activities for data reduction and visualization. The activities are using methods like multidimensional scaling, factor analysis, or organizing maps which are related to the field of scientometrics. Moreover, there have been serveral approaches in visualizing patent e.g. representations of patent related social networks showing the relationships between inventors, applicants and companies and representations of classificatory information using treemaps.

===former commercial products===

* Aureka
* Citation Link
* Matheo Analyzer

==Authors==
* [http://www.infovis-wiki.net/index.php?title=Giereth%2C_Mark Mark Giereth]
* Steffen Koch
* [http://www.infovis-wiki.net/index.php?title=Rotard%2C_Martin Martin Rotard]
* Thomas Ertl

This article ist based on the paper

Giereth, M. et. al.: Web Based Visual Exploration of Patent Information, 11th International Conference Information Visualization (IV'07)
Univertity of Stuttgart, Visualization and Interactive Systems Institute, Germany, 2007
[http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Flpdocs%2Fepic03%2Fwrapper.htm%3Farnumber%3D4271975&authDecision=-203 Download on IEEE]

[[Category:Techniques]]

Web Based Visual Exploration of Patent Information

2009-05-27T15:54:00Z

UE-InfoVis09-18:

==Motivation==

On the one hand, patents are a well known instrument to protect intellectual properties. On the other hand, there are several aspects which are often neglected by the scientific community: analyzing patent information can lead to e.g. identification of the direction of technical change, forecasts of market values and getting insights into your competitors work and inventions. At present there are about 60 million patent documents existing worldwide mostly comprising natural language supplemented by figures, diagrams, formulas, etc. As a consequence of this, it is needless to allude that computer support is heavily required. Besides this, patent evaluation still takes a lot of human effort. Therefore, it is very important to explore new approaches in software supported retrieval and visualization of patent information. The main goal in this connection is to improve the users cognition processes; e.g. to faster identify potential search results/constraints etc.

==Characteristics of Patent Information==

Because of national patent laws, patent documents are following a well-defined structure arranged on a title page:

* bibliographic data and an abstract
* classificatory data
* description of the state of the art
* claims section
* images, diagrammes, formulae, etc. (optional)

As seen above, patent documents comprise some metadata such as bibliographic data and classificatory data. Nevertheless, for evaluation there often is some further information needed: The legal status and patent family information, which both have to be fetched from external data sources like the [http://www.european-patent-office.org/inpadoc/stats/ Europaean Patent Office]

===Legal Status===
The legal status specifies significant events in the lifetime of a patent like changes of the owner etc.

===Patent Family===
Patents which describe the same invention belong to the same patent family. A common definition says that a patent document belongs to a respective patent family if the claims section and priorities of this document are matching the other patents claims and priorities of this family (e.g. protecting an invention in different countries).

===Classificatory Data===
The [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] (IPC) is the number one classification scheme of patent documents for ordering them in terms of technical fields. Therefore the IPC comprises 68.000 (advanced) or 17.000 (core) categories and is hierarchically organized in 13 levels.

==Visualization Techniques==

===Mass-Spring Graphs===

[[{{ns:6}}:Massspringgraph.gif |thumb|right|300px|'''Figure 1''': A Mass-Spring Graph]]

During search, it is often a matter of concern to identify clusters or groups e.g. patents that are related to each other by different criteria (same category, same inventor, etc.) and visualize them in an appropriate manner. A common way to do this are (interactive) mass-spring graphs. They are an adequate and intuitive form of visualizing clusters and interrelations between paticular nodes. To simulate the physics of this kind of force-directed graphs, you can use the [http://en.wikipedia.org/wiki/Barnes-Hut_simulation Barnes-Hut Algorithm] that allows efficient n-body force calculations in O(n log n) time.

'''Figure 1''' shows the relationship between patents (yellow) and their corresponding priority document (brown). In the special case of patent documents it is thus possible to i.e. easily identify the priority applications that have been the groundwork for other patents. In gereral, mass-spring graphs are suitable for search through all kinds of [http://www.infovis-wiki.net/index.php?title=Category:Hierarchical_Data hierarchically data] to show their interrelationships.

====Demonstrations of Related Work and Mass-Spring Graphs====

* [http://christopherbaker.net/2007/03/22/patent-database-visualization/ Patent Database Visualization of Christopher Baker]
* [http://www.youtube.com/watch?v=m-lLPvXeCfY Demo of another Mass-Spring Graph Application]

===Patent Family Layout===

[[{{ns:6}}:patent family layout.jpg |thumb|right|300px|'''Figure 2''': Patent Family Layout]]

Next to the mass-spring graph, the patent family layout is also part of visually clustering patent sets. It is based on filling date and country in an interactive 2D matrix that are represented as red and blue nodes. The filing date of the patents and priorities are shown on the horizontal position (x-axis). On vertical position, every line describes a country or organization where the patents or priorities have been filed. Arcs will point from a patent to it's priority document and the priority relations are visualized if a node is selected. To get a quick overview of often referenced documents, the node size displays the number of ingoing arcs of the node.

===Visualization of Classificatory Information===

[[{{ns:6}}:Class.gif |thumb|right|300px|'''Figure 3''': Treemap of Classificatory Data of Patent Information]]

With a treemap it is possible to show the hierarchical structure of the [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] IPC. The IPC categories are rendered as nested rectangular areas, which help to keep a clear view of the used categories in large patent sets. To get more information and further details it is possible to zoom into specific parts for an enlargment of the specific labels. An alleviation in these technique is to search for keywords in the titles of IPC categories. The search results are shown as a list and in the treemap as rectangles with red and green filling. The red items are not part of the patent set, the green items are part of the patent set.

====Related Topics====

* [http://www.infovis-wiki.net/index.php?title=Treemap More Info on Treemaps]
* [http://www.infovis-wiki.net/index.php?title=Extreme_visualization:_squeezing_a_billion_records_into_a_million_pixels Squeezing a Billion Records Into a Million Pixels]

==Constraints of Web Application Development==

There exists serveral problems or constraints in developing interactive visualizations that are accessible via a web browser:

* heterogenity of client software (different browsers, plugins)
* infrastructure (low bandwidth, firewalls)
* inactive javascript

To fit this constraints and the needs of potential users as much as possible, it is necessary to implement and design a web application (especially web based graphical representations) in multiple manners:

===Java Applets===

* + rich interaction capabilities
* - Java Plugin
* - download time

===Raster Graphics with HTML Image Maps===

* + no additional client software
* + suitable for old browsers
* - less interactiv capabilities

===Rich Internet Applications with AJAX and SVG===

* + no additional client software
* + fast
* + lots of libraries and animation frameworks
* + rich interaction capabilities
* - [http://alexbosworth.backpackit.com/pub/67688 several drawbacks in using AJAX]

[[Category:Techniques]]

Web Based Visual Exploration of Patent Information

2009-05-27T15:52:31Z

UE-InfoVis09-18:

==Motivation==

On the one hand, patents are a well known instrument to protect intellectual properties. On the other hand, there are several aspects which are often neglected by the scientific community: analyzing patent information can lead to e.g. identification of the direction of technical change, forecasts of market values and getting insights into your competitors work and inventions. At present there are about 60 million patent documents existing worldwide mostly comprising natural language supplemented by figures, diagrams, formulas, etc. As a consequence of this, it is needless to allude that computer support is heavily required. Besides this, patent evaluation still takes a lot of human effort. Therefore, it is very important to explore new approaches in software supported retrieval and visualization of patent information. The main goal in this connection is to improve the users cognition processes; e.g. to faster identify potential search results/constraints etc.

==Characteristics of Patent Information==

Because of national patent laws, patent documents are following a well-defined structure arranged on a title page:

* bibliographic data and an abstract
* classificatory data
* description of the state of the art
* claims section
* images, diagrammes, formulae, etc. (optional)

As seen above, patent documents comprise some metadata such as bibliographic data and classificatory data. Nevertheless, for evaluation there often is some further information needed: The legal status and patent family information, which both have to be fetched from external data sources like the [http://www.european-patent-office.org/inpadoc/stats/ Europaean Patent Office]

===Legal Status===
The legal status specifies significant events in the lifetime of a patent like changes of the owner etc.

===Patent Family===
Patents which describe the same invention belong to the same patent family. A common definition says that a patent document belongs to a respective patent family if the claims section and priorities of this document are matching the other patents claims and priorities of this family (e.g. protecting an invention in different countries).

===Classificatory Data===
The [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] (IPC) is the number one classification scheme of patent documents for ordering them in terms of technical fields. Therefore the IPC comprises 68.000 (advanced) or 17.000 (core) categories and is hierarchically organized in 13 levels.

==Visualization Techniques==

===Mass-Spring Graphs===

[[{{ns:6}}:Massspringgraph.gif |thumb|right|300px|'''Figure 1''': A Mass-Spring Graph]]

During search, it is often a matter of concern to identify clusters or groups e.g. patents that are related to each other by different criteria (same category, same inventor, etc.) and visualize them in an appropriate manner. A common way to do this are (interactive) mass-spring graphs. They are an adequate and intuitive form of visualizing clusters and interrelations between paticular nodes. To simulate the physics of this kind of force-directed graphs, you can use the [http://en.wikipedia.org/wiki/Barnes-Hut_simulation Barnes-Hut Algorithm] that allows efficient n-body force calculations in O(n log n) time.

'''Figure 1''' shows the relationship between patents (yellow) and their corresponding priority document (brown). In the special case of patent documents it is thus possible to i.e. easily identify the priority applications that have been the groundwork for other patents. In gereral, mass-spring graphs are suitable for search through all kinds of [http://www.infovis-wiki.net/index.php?title=Category:Hierarchical_Data hierarchically data] to show their interrelationships.

====Demonstrations of Related Work and Mass-Spring Graphs====

* [http://christopherbaker.net/2007/03/22/patent-database-visualization/ Patent Database Visualization of Christopher Baker]
* [http://www.youtube.com/watch?v=m-lLPvXeCfY Demo of another Mass-Spring Graph Application]

===Patent Family Layout===

[[{{ns:6}}:patent family layout.jpg |thumb|right|300px|'''Figure 2''': Patent Family Layout]]

Next to the mass-spring graph, the patent family layout is also part of visually clustering patent sets. It is based on filling date and country in an interactive 2D matrix that are represented as red and blue nodes. The filing date of the patents and priorities are shown on the horizontal position (x-axis). On vertical position, every line describes a country or organization where the patents or priorities have been filed. Arcs will point from a patent to it's priority document and the priority relations are visualized if a node is selected. To get a quick overview of often referenced documents, the node size displays the number of ingoing arcs of the node.

===Visualization of Classificatory Information===

[[{{ns:6}}:Class.gif |thumb|right|300px|'''Figure 3''': Treemap of Classificatory Data of Patent Information]]

With a treemap it is possible to show the hierarchical structure of the [http://en.wikipedia.org/wiki/International_Patent_Classification International Patent Classification] IPC. The IPC categories are rendered as nested rectangular areas, which help to keep a clear view of the used categories in large patent sets. To get more information and further details it is possible to zoom into specific parts for an enlargment of the specific labels. An alleviation in these technique is to search for keywords in the titles of IPC categories. The search results are shown as a list and in the treemap as rectangles with red and green filling. The red items are not part of the patent set, the green items are part of the patent set.

====Related Topics====

* [http://www.infovis-wiki.net/index.php?title=Treemap More Info on Treemaps]
* [http://www.infovis-wiki.net/index.php?title=Extreme_visualization:_squeezing_a_billion_records_into_a_million_pixels Squeezing a Billion Records Into a Million Pixels]

==Constraints of Web Application Development==

There exists serveral problems or constraints in developing interactive visualizations that are accessible via a web browser:

* heterogenity of client software (different browsers, plugins)
* infrastructure (low bandwidth, firewalls)
* inactive javascript

To fit this constraints and the needs of potential users as much as possible, it is necessary to implement and design a web application (especially web based graphical representations) in multiple manners:

===Java Applets===

+ rich interaction capabilities
- Java Plugin
- download time

===Raster Graphics with HTML Image Maps===

+ no additional client software
+ suitable for old browsers
- less interactiv capabilities

===Rich Internet Applications with AJAX and SVG===

+ no additional client software
+ fast
+ lots of libraries and animation frameworks
+ rich interaction capabilities
- [http://alexbosworth.backpackit.com/pub/67688 drawbacks of using AJAX]

[[Category:Techniques]]

Web Based Visual Exploration of Patent Information

2009-05-27T15:40:16Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T15:39:50Z

UE-InfoVis09-18:

File:Class.gif

2009-05-27T15:38:52Z

UE-InfoVis09-18: Treemap of classificatory data

== Summary ==
Treemap of classificatory data
== Copyright status ==

== Source ==
Web Based Visual Exploration of Patent Information, Giereth & Koch et. al., 2007

Web Based Visual Exploration of Patent Information

2009-05-27T15:34:07Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T15:22:36Z

UE-InfoVis09-18:

File:Patent family layout.jpg

2009-05-27T15:20:33Z

UE-InfoVis09-18: Patent Family Layout

== Summary ==
Patent Family Layout
== Copyright status ==

== Source ==
Web Based Visual Exploration of Patent Information, Giereth & Koch et. al., 2007

Web Based Visual Exploration of Patent Information

2009-05-27T15:10:56Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T15:06:19Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:55:59Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:53:02Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:47:56Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:47:24Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:46:34Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:44:29Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:44:05Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:43:26Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:42:50Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:38:50Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:37:34Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:31:40Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:30:58Z

UE-InfoVis09-18:

File:Massspringgraph.gif

2009-05-27T14:29:51Z

UE-InfoVis09-18: visualizing the interrelationships between paticualar patents and priority documents

== Summary ==
visualizing the interrelationships between paticualar patents and priority documents
== Copyright status ==

== Source ==
Web Based Visual Exploration of Patent Information, Giereth & Koch et. al., 2007

Web Based Visual Exploration of Patent Information

2009-05-27T14:23:41Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:11:50Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:06:43Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T14:05:21Z

UE-InfoVis09-18:

===Motivation===

On the one hand, patents are a well known instrument to protect intellectual properties. On the other hand, there are several aspects which are often neglected by the scientific community: analyzing patent information can lead to e.g. identification of the direction of technical change, forecasts of market values and getting insights into your competitors work and inventions. At present there are about 60 million patent documents existing worldwide mostly comprising natural language supplemented by figures, diagrams, formulas, etc. As a consequence of this, it is needless to allude that computer support is heavily required. Besides this, patent evaluation still takes a lot of human effort. Therefore, it is very important to explore new approaches in software supported retrieval and visualization of patent information. The main goal in this connection is to improve the users cognition processes; e.g. to faster identify potential search results/constraints etc.

===Characteristics of Patent Information===

Because of national patent laws, patent documents are following a well-defined structure arranged on a title page:

* bibliographic data and an abstract
* classificatory data
* description of the state of the art
* claims section
* images, diagrammes, formulae, etc. (optional)

As seen above, patent documents comprise some metadata such as bibliographic data and classificatory data. Nevertheless, for evaluation there often is some further information needed: The legal status and patent family information, which both have to be fetched from external data sources like the [http://www.european-patent-office.org/inpadoc/stats/ Europaean Patent Office]

==Legal Status==
The legal status specifies significant events in the lifetime of a patent like changes of the owner etc.

==Patent Family==
Patents which describe the same invention belong to the same patent family. A common definition says that a patent document belongs to a respective patent family if the claims section and priorities of this document are matching the other patents claims and priorities of this family (E.g. protecting an invention in different countries)

==Classificatory Data==
The International Patent Classification (IPC) is the number one classification scheme of patent documents for ordering them in terms of technical fields. Therefore the IPC comprises 68.000 (advanced) or 17.000 (core) categories and is hierarchically organized in 13 levels.

[[Category:Techniques]]

Web Based Visual Exploration of Patent Information

2009-05-27T14:00:17Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T13:50:21Z

UE-InfoVis09-18:

Web Based Visual Exploration of Patent Information

2009-05-27T13:48:17Z

UE-InfoVis09-18: New page: Category:Techniques

[[Category:Techniques]]

Koch, Steffen

2009-05-13T14:42:05Z

UE-InfoVis09-18: Removing all content from page

Rotard, Martin

2009-05-13T12:19:34Z

UE-InfoVis09-18:

[[{{ns:6}}:Rotard.jpg |thumb|Martin Rotard]]

===Short Vita===

'''Martin Rotard''' has been researcher and PostDoc of the Visualization and Interactive Systems Institute, University of Stuttgart, since June 2001. His research interests are new graphical standards on the web like Scalable Vector Graphics, MathML, X3D, SMIL, etc., Human Computer Interaction, Usability and Accessibility. His development activities are in the field of XML-based graphics, semantic web technologies, universal access on the web, graphical user interfaces and software usability. 

Martin Rotard's projects:
*BMWi: HyperBraille
*EU: PatExpert
*MWK-BW: Teaching-/Learningmodules for Key Qualifications in the Field of Computer Graphics and Visualization
*BMBF: Information Technology Online (ITO)
*University of Stuttgart: 100-online
*BMBF/WTZ: Modelling of Discrete Event Systems

===Contact Information===

'''Dr. Martin Rotard'''

University of Stuttgart 
Visualization and Interactive Systems Institute 
Universitätsstraße 38 
70569 Stuttgart 
Germany

'''E-Mail:''' [mailto:martin.rotard@informatik.uni-stuttgart.de martin.rotard@informatik.uni-stuttgart.de]

===External Links===

*[http://www.vis.uni-stuttgart.de/~rotard/ Martin Rotard's homepage]
*[http://www.vis.uni-stuttgart.de/ger/ Visualization and Interactive Systems Institute, University of Stuttgart]

[[Category:Persons]]

Rotard, Martin

2009-05-13T12:04:15Z

UE-InfoVis09-18:

[[{{ns:6}}:Rotard.jpg |thumb|Martin Rotard]]

===Short Vita===

'''Martin Rotard''' is a lawyer in private practice since 2003 with his registered office in Bonn. He studied law at the Johann-Wolfgang von Goethe University of Frankfurt am Main and at the University of Konstanz and took a postgraduate study in economics for jurists. His specializations and interests comprises trademark law, copyright, competition law and IT law. 
From 2002 - 2004 he worked at a corporate law firm at Köln/Bonn and completed the theoretical fully-qualified-lawyer seminar "industrial property". 

Martin Rotard's projects:
*BMWi: HyperBraille
*EU: PatExpert
*MWK-BW: Teaching-/Learningmodules for Key Qualifications in the Field of Computer Graphics and Visualization
*BMBF: Information Technology Online (ITO)
*University of Stuttgart: 100-online
*BMBF/WTZ: Modelling of Discrete Event Systems

===Contact Information===

'''Dr. Martin Rotard'''

University of Stuttgart 
Visualization and Interactive Systems Institute 
Universitätsstraße 38 
70569 Stuttgart 
Germany

'''E-Mail:''' [mailto:martin.rotard@informatik.uni-stuttgart.de martin.rotard@informatik.uni-stuttgart.de]

===External Links===

*[http://www.vis.uni-stuttgart.de/~rotard/ Martin Rotard's homepage]
*[http://www.vis.uni-stuttgart.de/ger/ Visualization and Interactive Systems Institute, University of Stuttgart]

[[Category:Persons]]

Rotard, Martin

2009-05-13T12:00:00Z

UE-InfoVis09-18:

[[{{ns:6}}:Rotard.jpg |thumb|Martin Rotard]]

===Short Vita===

'''Steffen Koch''' is a lawyer in private practice since 2003 with his registered office in Bonn. He studied law at the Johann-Wolfgang von Goethe University of Frankfurt am Main and at the University of Konstanz and took a postgraduate study in economics for jurists. His specializations and interests comprises trademark law, copyright, competition law and IT law. 
From 2002 - 2004 he worked at a corporate law firm at Köln/Bonn and completed the theoretical fully-qualified-lawyer seminar "industrial property". 

Steffen Koch's publications/references:
*Eine der wichtigsten IT-Kanzleien Deutschlands, e-commerce Magazin 05/2008
*RTL Interview zur Erschöpfung von Markenrecht, 29.11.2006 RTL2 News
*"Neuer Rechtsrahmen für elektronische Kommunikation", Europäische Zeitung - The Journal of Europe, März 2004
*"Haftung für Umweltschäden in der EU", Europäische Zeitung - The Journal of Europe, März 2004

===Contact Information===

'''Dr. Martin Rotard'''

University of Stuttgart 
Visualization and Interactive Systems Institute 
Universitätsstraße 38 
70569 Stuttgart 
Germany

'''E-Mail:''' [mailto:martin.rotard@informatik.uni-stuttgart.de martin.rotard@informatik.uni-stuttgart.de]

===External Links===

*[http://www.vis.uni-stuttgart.de/~rotard/ Martin Rotard's homepage]
*[http://www.vis.uni-stuttgart.de/ger/ Visualization and Interactive Systems Institute, University of Stuttgart]

[[Category:Persons]]

File:Rotard.jpg

2009-05-13T11:59:01Z

UE-InfoVis09-18:

== Summary ==
Portrait of Martin Rotard
== Copyright status ==

== Source ==
[http://www.vis.uni-stuttgart.de/~rotard/ http://www.vis.uni-stuttgart.de/~rotard/]

File:Rotard.jpg

2009-05-13T11:58:09Z

UE-InfoVis09-18: Portrait of Martin Rotard

== Summary ==
Portrait of Martin Rotard
== Copyright status ==

== Source ==

Rotard, Martin

2009-05-13T11:57:06Z

UE-InfoVis09-18: New page: Steffen Koch ===Short Vita=== '''Steffen Koch''' is a lawyer in private practice since 2003 with his registered office in Bonn. He studied law at the Johann-...

[[{{ns:6}}:Koch.jpg |thumb|Steffen Koch]]

===Short Vita===

'''Steffen Koch''' is a lawyer in private practice since 2003 with his registered office in Bonn. He studied law at the Johann-Wolfgang von Goethe University of Frankfurt am Main and at the University of Konstanz and took a postgraduate study in economics for jurists. His specializations and interests comprises trademark law, copyright, competition law and IT law. 
From 2002 - 2004 he worked at a corporate law firm at Köln/Bonn and completed the theoretical fully-qualified-lawyer seminar "industrial property". 

Steffen Koch's publications/references:
*Eine der wichtigsten IT-Kanzleien Deutschlands, e-commerce Magazin 05/2008
*RTL Interview zur Erschöpfung von Markenrecht, 29.11.2006 RTL2 News
*"Neuer Rechtsrahmen für elektronische Kommunikation", Europäische Zeitung - The Journal of Europe, März 2004
*"Haftung für Umweltschäden in der EU", Europäische Zeitung - The Journal of Europe, März 2004

===Contact Information===

'''Dr. Martin Rotard'''

University of Stuttgart 
Visualization and Interactive Systems Institute 
Universitätsstraße 38 
70569 Stuttgart 
Germany

'''E-Mail:''' [mailto:martin.rotard@informatik.uni-stuttgart.de martin.rotard@informatik.uni-stuttgart.de]

===External Links===

*[http://www.vis.uni-stuttgart.de/~rotard/ Martin Rotard's homepage]
*[http://www.vis.uni-stuttgart.de/ger/ Visualization and Interactive Systems Institute, University of Stuttgart]

[[Category:Persons]]

File:Koch.jpg

2009-05-12T21:49:24Z

UE-InfoVis09-18:

== Summary ==
Portrait of Steffen Koch

== Copyright status ==

== Source ==
[http://www.koch-rechtsanwalt.de/html/anwalt.htm http://www.koch-rechtsanwalt.de/html/anwalt.htm]

Koch, Steffen

2009-05-12T21:36:02Z

UE-InfoVis09-18: New page: Steffen Koch ===Short Vita=== '''Steffen Koch''' is a lawyer in private practice since 2003 with his registered office in Bonn. He studied law at the Johann-...

[[{{ns:6}}:Koch.jpg |thumb|Steffen Koch]]

===Short Vita===

'''Steffen Koch''' is a lawyer in private practice since 2003 with his registered office in Bonn. He studied law at the Johann-Wolfgang von Goethe University of Frankfurt am Main and at the University of Konstanz and took a postgraduate study in economics for jurists. His specializations and interests comprises trademark law, copyright, competition law and IT law. 
From 2002 - 2004 he worked at a corporate law firm at Köln/Bonn and completed the theoretical fully-qualified-lawyer seminar "industrial property". 

Steffen Koch's publications/references:
*Eine der wichtigsten IT-Kanzleien Deutschlands, e-commerce Magazin 05/2008
*RTL Interview zur Erschöpfung von Markenrecht, 29.11.2006 RTL2 News
*"Neuer Rechtsrahmen für elektronische Kommunikation", Europäische Zeitung - The Journal of Europe, März 2004
*"Haftung für Umweltschäden in der EU", Europäische Zeitung - The Journal of Europe, März 2004

Lawyer Steffen Koch is member of german's lawyer society, of consortium information technology (davit), of consortium intellectual property & media and of german's association for industrial property and copyright (GRUR). 

===Contact Information===

'''Lawyer Steffen Koch'''

Holtorfer Straße 35 
Ennert Gewerbe Park 
D - 53229 Bonn 

'''E-Mail:''' [mailto:rechtsanwalt@koch-rechtsanwalt.de rechtsanwalt@koch-rechtsanwalt.de]

===External Links===

*[http://www.koch-rechtsanwalt.de/ Steffen Koch's homepage]
*[http://www.rak-koeln.de/ Bar association Köln]

[[Category:Persons]]

File:Koch.jpg

2009-05-12T21:33:02Z

UE-InfoVis09-18: New page: == Summary == == Copyright status == == Source ==

== Summary ==

== Copyright status ==

== Source ==

Giereth, Mark

2009-05-08T10:31:53Z

UE-InfoVis09-18:

[[{{ns:6}}:Giereth.jpg |thumb|Mark Giereth]]

===Short Vita===

'''Mark Giereth''' was a former member of the Intelligent Systems Institute of the University Stuttgart, Germany. Until 2004, his main research focused on automatic learning procedures to forecast ambient pollutant and classification problems of speech processing. Afterwards, as a research assistent at the Visualization and Interactive Systems Institute, he changed his main exploratory field to semantic representation, visualizing and partial encryption of patent-metadata in the semantic web. In 2009 Mark Giereth quit his academic career. Currently he is employed at Bosch.

===Contact Information===

'''Dipl.-Inf. Mark Giereth'''

Universität Stuttgart 
Institut für Visualisierung und Interaktive Systeme (VIS) 
Universitätstraße 38
70569 Stuttgart

'''E-Mail:''' [mailto:mark@giereth.de mark@giereth.de]

===External Links===

*[http://www.vis.uni-stuttgart.de/~giereth/ Mark Giereth's homepage and list of publications]
*[http://www.vis.uni-stuttgart.de/ger/ Visualization and Interactive Systems Institute, University Stuttgart]

[[Category:Persons]]

Mark Giereth

2009-05-08T10:29:43Z

UE-InfoVis09-18: Mark Giereth moved to Giereth, Mark

#REDIRECT [[Giereth, Mark]]

Giereth, Mark

2009-05-08T10:29:43Z

UE-InfoVis09-18: Mark Giereth moved to Giereth, Mark

[[{{ns:6}}:Giereth.jpg |thumb|Mark Giereth]]

'''Mark Giereth''' was a former member of the Intelligent Systems Institute of the University Stuttgart, Germany. Until 2004, his main research focused on automatic learning procedures to forecast ambient pollutant and classification problems of speech processing. Afterwards, as a research assistent at the Visualization and Interactive Systems Institute, he changed his main exploratory field to semantic representation, visualizing and partial encryption of patent-metadata in the semantic web. In 2009 Mark Giereth quit his academic career. Currently he is employed at Bosch.

===Contact Information===

'''Dipl.-Inf. Mark Giereth'''

Universität Stuttgart 
Institut für Visualisierung und Interaktive Systeme (VIS) 
Universitätstraße 38
70569 Stuttgart

'''E-Mail:''' [mailto:mark@giereth.de mark@giereth.de]

===External Links===

*[http://www.vis.uni-stuttgart.de/~giereth/ Mark Giereth's homepage and list of publications]
*[http://www.vis.uni-stuttgart.de/ger/ Visualization and Interactive Systems Institute, University Stuttgart]

[[Category:Persons]]