Patent Data, Analysis & Visualisation

by Juan C. Dürsteler

Patents are extremely important when configuring the business strategy of technological companies. There are more and more tools that allow you to download and analyse patents in one way or another. Visualisation is a key tool for the analysis and detection of opportunities that is still used shyly.

One of the less usual applications of information visualisation is patent visualisation. In fact visualising patent information is just a part of text or document visualisation. In the end, a patent is just text with a certain structure and with a specific objective.

Patents encompass several aspects that have, nonetheless, great importance.:

* they are a way to protect intellectual property rights

o our own rights, allowing us to produce without being copied with inpunity

o the other’s rights, preventing us of using alien developments.

For these reasons patents constitute a very important source of information about the competitors. This makes them the main tool for technological and business intelligence. On the other hand, knowing which patents are enforced in the market is vital before deciding to make a new development or product, with the important investment it means, that could be finally blocked by an existing patent.

Many patent offices already allow to freely download abstracts and complete text of their patents. Among them the USPTO from United States or the EPO from Europe, and many others you can find, for example, in the PatentLawLinks.com list. In particular Esp@cenet, the download service of the European Patent Office has become a very popular source of information in this field.

Based on the many possibilities of search that all this offers, there have been appearing in the market different systems allowing you to search, download and analyse patents automatically. Many of them are present in the Patent Information Users Group (PIUG) vendors list. Although downloading, classificating, clustering and finding the relationship between patents of similar contents has become quite widespread, even making use of text mining tools, the visualisation of those resuts is not so usual.

Anacubis, patent division of the i2 inc group, has some visualisation demos that use i2 inc Analyst’s Notebook visualisation tool. Unfortunately some problem with the demo has prevented me from executing it properly, so I can’t report on it.

Spore.inc provides two main types of visualisations:

Patent matrix diagram. Diagrams that represent the substance and hierachical relationships of the claims of a patent. This way, reading and understanding of a patent’s claims is much easier.
Source: Diagram as can be seen at Spore Inc website. Spore diagram. It produces graphs of patent groups that allow you to see how are they related, identifying trends and detecting development opportunities related to “gaps” in some areas of the patent scope of a product portfolio.
Source: Diagram as can be seen at Spore Inc website.

But maybe Mathéo Software represents one of the easiest to use systems (you can download a free demo) that incorporates four main types of visualisation that can be produced with many combinations of the different variables that identify a patent. We’ll focus on MatheoPatent 6.1. This program allows you to launch a search on different sources according to keywords, inventors, etc. With the downloaded results you can get the following types of visualisation.

MatheoPatent 6.1
MatheoPatLista2.gif (182879 bytes) MatheoPatPDate.gif (68024 bytes)
Table: Presentation in form of a table where you can see the results of the search. To the left, a list of inventors with their nationalities and number of patents granted. To the right, the list of patents. Below lies the summary of particular patent of the list.
Source: Screenshot by the author of the program in execution.
Click on the image to enlarge it. Bar chart: Here you can see a bar chart of the number of patents present per year. MatheoPatent allows you to select different variables (inventor, family, date, etc) building bar charts accordingly.
Source: Screenshot by the author of the program in execution.
Click on the image to enlarge it.
MatheoMatrix1.gif (146436 bytes) MatheoGrafo1.gif (82098 bytes)
Matrix: By crossing the different variables MatheoPatent allows you to select (inventor, family, date, etc), you can obtain this matrix chart. In this particular case we cross inventors against inventors. The coloured squares in the diagonal indicate the patents of a particular inventor. Big squares indicate groups of inventors acting together. If they are out of the diagonal it means that some inventors or groups participate in patents with other groups. It’s possible to cross other variables to detect different patterns
Source: Screenshot by the author of the program in execution.
Click on the image to enlarge it. Networks: In this case we represent the relationships between inventors and companies by means of a force directed graph where dragging a company you can drag also the inventors related to it as if they were linked by rubber bands. Again we can select different variables to see the networking between them.
Source: Screenshot by the author of the program in execution.
Click on the image to enlarge it.

¿Do you remember ThemeScape and newsmaps? (see number 93). Finally this technology, renamed as Aureka!, has become the patent visualisation of MicroPatent. This way, this extraordinary form of visualisation has seen its incorporation to the world of patents. Let’s recall that ThemeScape allows you to represent a document corpus as a topographic map where the “mountains” are associated with frequent terms (predominant “themes”) that are as close as their concepts are similar.

Aureka! The patent version of ThemeScape represents as a topographic map the explored document space. Dots depict particular documents (patents) . The closer they are, the most related the patent topics. You can access the documents by clicking on them.
Fuente: Image of Aureka! as can be seen at MicroPatent’s website in Internet.

Patent visualisation is just one more within the possibilities of text mining. Nevertheless, as anyone working in R+D knows, detecting the patents that can prevent us to follow a research line or finding a “hole” where there’s nothing patented can be fundamental for the business strategy of a company. Visualisation is vital to open a way through the web of legal text, [sometimes obscure] claims, and the large amount of data that represent the world of patents. We are still an a very preliminar stage in this field.

Links of this issue:
http://www.uspto.gov/ United States Patent Office (USPTO)
http://www.european-patent-office.org/ European Patent Office (EPO)
http://www.patentlawlinks.com/patoff.htm PatentLawLinks website
http://ep.espacenet.com/ Espacenet EPO download center
http://www.piug.org/ Patent Information Users Group web site.
http://www.piug.org/vendor.html Patent Information Users Group vendors list.
http://www.anacubis.com/ Anacubis website
http://www.i2inc.com/Products/Analysts_Notebook/default.asp i2 inc. Analyst’s Notebook
http://www.sporeusa.com/home/ Spore website
http://www.matheo-software.com/ Mathéo Software website
http://www.infovis.net/printMag.php?num=93〈=2 Num 93 Two years later
http://www.micropatent.com/ Micro Patent website

Patent Analysis: Data Analysis & Result Visualisation

Patent Analysis
by Juan C. Dürsteler

One of the less usual applications of information visualisation is patent visualisation. In fact visualising patent information is just a part of text or document visualisation. In the end, a patent is just text with a certain structure and with a specific objective.
Patents encompass several aspects that have, nonetheless, great importance.:

• they are a way to protect intellectual property rights
• our own rights, allowing us to produce without being copied with inpunity
• the other’s rights, preventing us of using alien developments.

For these reasons patents constitute a very important source of information about the competitors. This makes them the main tool for technological and business intelligence. On the other hand, knowing which patents are enforced in the market is vital before deciding to make a new development or product, with the important investment it means, that could be finally blocked by an existing patent.
Many patent offices already allow to freely download abstracts and complete text of their patents. Among them the USPTO from United States or the EPO from Europe, and many others you can find, for example, in the PatentLawLinks.com list. In particular Esp@cenet, the download service of the European Patent Office has become a very popular source of information in this field.
Based on the many possibilities of search that all this offers, there have been appearing in the market different systems allowing you to search, download and analyse patents automatically. Many of them are present in the Patent Information Users Group (PIUG) vendors list. Although downloading, classificating, clustering and finding the relationship between patents of similar contents has become quite widespread, even making use of text mining tools, the visualisation of those resuts is not so usual.
Anacubis, patent division of the i2 inc group, has some visualisation demos that use i2 inc Analyst’s Notebook visualisation tool. Unfortunately some problem with the demo has prevented me from executing it properly, so I can’t report on it.
Spore.inc provides two main types of visualisations:
(image placeholder)
(image placeholder)

Spore Inc
Spore Inc

But maybe Mathéo Software represents one of the easiest to use systems (you can download a free demo) that incorporates four main types of visualisation that can be produced with many combinations of the different variables that identify a patent. We’ll focus on MatheoPatent 6.1. This program allows you to launch a search on different sources according to keywords, inventors, etc. With the downloaded results you can get the following types of visualisation.

¿Do you remember ThemeScape and newsmaps? (see number 93). Finally this technology, renamed as Aureka!, has become the patent visualisation of MicroPatent. This way, this extraordinary form of visualisation has seen its incorporation to the world of patents. Let’s recall that ThemeScape allows you to represent a document corpus as a topographic map where the “mountains” are associated with frequent terms (predominant “themes”) that are as close as their concepts are similar.
(image placeholder)
(image placeholder)

MicroPatent

Patent visualisation is just one more within the possibilities of text mining. Nevertheless, as anyone working in R+D knows, detecting the patents that can prevent us to follow a research line or finding a “hole” where there’s nothing patented can be fundamental for the business strategy of a company. Visualisation is vital to open a way through the web of legal text, [sometimes obscure] claims, and the large amount of data that represent the world of patents. We are still an a very preliminar stage in this field.
Links of this issue:
http://www.uspto.gov/

http://www.european-patent-office.org/

http://www.patentlawlinks.com/patoff.htm

http://ep.espacenet.com/

http://www.piug.org/

http://www.piug.org/vendor.html

http://www.anacubis.com/

http://www.i2inc.com/Products/Analysts_Notebook/default.asp

http://www.sporeusa.com/home/

http://www.matheo-software.com/

http://www.infovis.net/printMag.php?num=93〈=2

http://www.micropatent.com/

Patent Searching an Effective Tool for Competitive Intelligence

Patent Searching an Effective Tool for Competitive Intelligence
Article by Vinod Singh

A lot of valuable information is now available of the industries in different databases in the web. Among all those patents the most important and easily available. Patent searching can give insights into the state of the art across any technical field. It can provide a platform to monitor the competitors activities by revealing which companies are involved in a field of technology of your interest. Patent searching data can also reveal the technological road map to a particular invention, the science or logic behind the invention, and its intended application.

However the legal nature of patents makes them an uncompromisingly formal style. They are written in a language sometimes so abstruse that it does more to obscure the nature of the invention than to elucidate it. Also the millions of patents exited are distributed across different databases and in each case coded and grouped according to one of several classification systems. The family patent information is also varied from various databases.

The skilled patent search requires in-depth knowledge of an array of software tools, search commands, searching techniques and classification systems. That’s why patent searching is an expert’s job. In the recent few years the demand for a professional patent searcher has increased.

Main benefits of free-access Web databases are that they provide a low-cost means of doing initial background searches. The problem is that they suffer serious drawbacks for more crucial searches. For example: free databases generally come from the patent issuing authorities (usually national patent offices) so their content is restricted to those patents granted by that particular authority. There is no universal structure, so the same fields may not necessarily be searchable across different databases. There is no ‘added value’ - such as readable abstracts in plain English, which has given patent information-provider Thomson Derwent its enviable reputation. There are rarely any patent analysis technologies. And they do not provide the option of sophisticated, command driven, Boolean searches as offered by powerful tools from host companies such as Dialog, Delphion, Questel-Orbit, MicoPat and STN - which also allow parallel searches across several (commercial and free) databases at once.

More importantly, a quick and easy search on a free site is extremely unlikely to uncover ’stealth patents’ or “hidden patents”- one of the latest IP protection tricks. The authors of these patents deliberately choose obfuscating keywords and try to have their patents inappropriately classified in order that others’ searches do not throw them up. Whereas commercial patent database providers provide access to patent collections throughout the world, along with value-added patent information, various analytical tools and other technologies. A number of these commercial providers have recently released innovative new functionalities alongside the search function

Why Conduct a Patent Search?

1. Patent searches are conducted for many purposes. Among them are to:

1. Determine if a particular invention is unique

2. Identify potential features for new product

3. Identify other possible uses for a new product

4. Determine independent inventors or companies currently or historically obtaining patents in a particular area

5. Find the patent(s) for a particular invention

6. Determine the state of the art in a particular area

7. Identify patents in a specific field for generating citation maps (a tool in determining the relative importance/value of a specific invention

8. Study the rate of innovation in a particular area

9. Determine the patent portfolio of a specific company

10. Determine if an invention infringes upon the intellectual property rights of others

11. Learn about an industry or a specific company

12. Search for potential solutions to design or safety problems

13. Identify potential licensees

14. To identify additional reference materials (journal articles, books, product literature) of use to those working in this area. Patents often list printed reference materials.

15. Identify inventors working in a certain field.

Patent search Procedure:

1. The Steps

1. Search the web to get the up to date information about the area of work and select the specific keywords describing the area of interest and identify the control patents. To start with by searching for any specific patents be aware of in this area, patents of companies work in this field, patents invented by inventors in this field, etc. This step is called “shoot from the tip”.

2. Try a few relevant words in the word search engine and see what turns up. If turned up any patents in the “shoot from the hip” step above, examine them for possible search words. Record the search words on a page in a project notebook and add other words as they come to mind or encounter them in other patents. Usually the word list becomes separated into groups of words covering different aspects of the invention.

3. Access the Classification Index. In paper it is about the size of a small town phone book. Look up your topic and you will find a class number. The area you are interested in may have several class numbers (for example marine propulsion and propellers (impellers) are in two different classes).

4. Access the Manual of Classification (in paper it is a large 3 volume set of ring binders). Turn to or click to the class you are interested in and identify the specific subclass’s best relating to your topic. You may need some assistance in understanding the hierarchial listing of subclasses. Many are subclasses of subclasses.

5. Access the Classification Definitions. It used to be on microfiche, but now you can access it online. Look up the specific class and subclass under study. Make sure you are really hunting for items resembling the definition of this class/subclass. Often additional hints are given for other places to look, including classes no longer existing.

6. Keep cycling through the three tools (Classification Index, Manual of Classification and Classification Definitions) until you identify the appropriate classes and subclasses.

7. Search the database to identify patents in the classes/subclasses identified.

8. Examine the ABSTRACT & IMAGE of these patents to identify those resembling your device. Make copies of the drawings, abstract and description of patents closely resembling your invention and of inventions serving the same purpose.

After completing Steps 1 to 7, examine the patents for:

1. Companies frequently appearing as assignees (patents assigned to them). Search for other patents assigned to these companies in an attempt to identify more patents in the area of interest.

2. Inventors frequently appearing on the patents (both independents and those working for companies). Search for other patents listing these individuals as inventors in an attempt to identify more patents in the area of interest.

3. Look for words and combinations of words in the patents of interest. Sort the words into groups. Some will describe one aspect of the invention and some will describe another. Record the search words on the list started earlier. Search for other patents containing these words in an attempt to identify more patents in the area of interest. Be aware of what portion of the patent you are searching (some search abstract only, front page only, full texts).

4. Examine the patents cited as reference by the patents of interest to see if some of them are of interest as well.

5. Examine the class and subclass info of the patents of interest in an attempt to identify other classes and subclasses that may contain patents of interest. Search these new classes/subclasses for additional patents of interest.

9. Keep cycling through steps 1 to 8 over and over until no more patents of interest are identified.

Conclusion

The patent search has become an effective tool for the mining of the patent data, which help in the competitive analysis. A throughout knowledge of the different patent database, their classification system is required for a in depth patent search. Patent search is crucial for the patentability, validity, infringement analysis etc. Thus a skilled patent search professional must know the various search procedures, databases limitations and technical tools and software to reveal a good search result.

Best resources in intellectual property and asset management

http://www.ipambestpractices.com/Info/BPLibraryIndex.html
Intellectual Property Best Practices Library:  Summaries

http://www.ipmenu.com/
IP Menu – Global Intellectual Property

http://www.providersedge.com/docs/km_articles/Managing_Knowledge_for_Advantage_-_Technologies.pdf
Managing Knowledge for Advantage: Content & Collaboration Technologies

http://www.kmmag.com/articles/default.asp?ArticleID=655
Making Knowledge Pay
Companies find that their intellectual processes and assets, if
properly packaged and sold, can yield surprising top-line revenues

http://www.internetcapital.com/news/partners/061702b.html
Delphion to Deliver Enterprise Software for Generating Corporate Value
from Intellectual Assets

Patently Obvious: MBHB Patent Law Blog: Patent Explosion

Patently Obvious: MBHB Patent Law Blog: Patent Explosion: “Aug 02, 2004
Patent Explosion
The past twenty years has seen increadible increases in the number of patents both applied for and issued. In her most recent paper (PDF), Berkeley professor and empirical whiz, Bronwyn Hall, examines patenting data and arrives at some interesting conclusions.
1) Although patenting has increased in most technological fields, the explosive growth is largely accounted for by electrical and computing fields.
2) The explosion is drivin, for the most part, by U.S. firms, with some contribution from Asia and Europe.
3) Patenting has become a critical signal of viability for new entrants in many industries.
Professor Hall’s data shows that in most industries, increases in patenting were drivin by new entrants. However, patenting increases in electrical and computing industries were accomplished by a shift in patenting by industry stalwarts.
The figures reveal the following interesting fact: although the jump in patent applications within the U.S. occurred in all technology classes, when we look by broad industry class, we find that it occurred only in firms that are in the electrical, computing and instruments industries. That is, the increase in chemicals, mechanical and other technologies appears to have been driven by increasing patenting activity by firms that were not traditionally in these industries. This result is consistent with the view that there has been a major strategic shift in patenting in the electrical/computing industries, but not in other industries.
UPDATE: Professor Hall provided a correction to my original interpretation of her results. She interprets her results as showing ‘that patents held by new entrants in the electrical and computing industries became more valuable post-1985 than those”