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

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

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

A Globe

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?

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?

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)

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?

An Example Applied to Patent Text

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)

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?

An Example Applied to Patent Structures

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.