1. Patent Mapping and Visualization
What is the State-of-the-Art?
Anthony Trippe, Sr. Innovation Manager
Chemical Abstracts Service

2. From the Way Back Machine
Linear Law of Patent Analysis (1998)
Create a tool kit of Patinformtics tools
Understand the Need Behind the Need
The Need Drives the Question
The Question Drives the Data
The Data Drives the Tool
Why is this important?
To a man with a hammer, everything looks like a nail - avoid this at all costs

3. A Riddle
What is round, represents millions of different pieces of data, yet is completely understood regardless of language or culture?

4. A Globe

5. Mapping Principles What sort of data are you mapping?
What relationships are you trying to represent or bring out in a large collection of data?
What is the principle object on the map?
What is the item you want the user to focus on?
What other dimensions or variables are you trying to represent?

6. Mapping Principles
What types of symbols, colors, shapes, etc… will you use to represent the dimensions and variables?
How will you determine the relevance between the dimensions
Particularly with the primary object
How do you measure this?
How do you “lay-out” the map so the relevance is represented and then present the map to the user?
What sort of interface do you apply so the user can interact with the data?

7. An Example Applied to Patent Text
Need behind the need
View from 20,000 feet of whole documents for large answer sets (macro-level analysis)
Examine fine details within a small collection (micro-level analysis)
Patent Family relationships
Claim construction
The need drives the question
How many documents in a particular sub-category and who are they assigned to? (macro-level)
How many independent claims are there and which dependant claims are associated with them? (micro-level)

8. An Example Applied to Patent Text
The question drives the data
What is my object?
What are the important pieces of meta-data associated with this object?
The data drives the tool
How do I measure the relationship?
How do I represent this to the user?
What will the user interaction be like?

9. An Example Applied to Patent Text

10. An Example Applied to Patent Structures
Need behind the need
View from 20,000 feet of large substance collections (macro-level analysis)
Examine fine details within a small collection (micro-level analysis)
Identify related properties amongst substances
Identify structural diversity within collection
The need drives the question
How many substances in a particular disease category and who are they assigned to? (macro-level)
Is there any space remaining to develop new and novel substances in this area? (micro-level)

11. An Example Applied to Patent Structures
The question drives the data
What is my object?
What are the important pieces of meta-data associated with this object?
The data drives the tool
How do I measure the relationship?
How do I represent this to the user?
What will the user interaction be like?

12. An Example Applied to Patent Structures

13. Conclusions
Apply the tried and true methodology to approaching these issues and problems
Don’t create a solution looking for a problem
Break the problem down into its component pieces and tackle each individually.