Art and Science of patent Searching
Patent searching is both an art and a science. Consequently, search capability improves with practice. But optimum practice requires a solid foundation for those who seek to conduct searches accurately and efficiently. Identification of factors for determining when a search is needed and what types and sources of information should be searched in the process is the crucial part.
For a patent searcher knowledge of various patent databases is extremely important. He should know the various pros and cons of these databases, along with database behavior in term of searching with the use of operators. For example, the USPTO patent search website allows to search full text and drawings of the entire patent issued since 1975. The full page images of patents since 1790 are also available. Also we can search patent application published since March 15th 2001. Similarly, other database such as EPO, JPO, Depatisnet, SIP, etc. is providing the free search facility. Paid databases such as MicroPat, STN, QPAT provides various handy search techniques and even have more operators. These databases also provide extraction of search results in excel format for further analysis, along with some level of data clustering or mapping.
The following points are very important to keep in mind during patent search:
# How to properly scope the search.
# How to search by classification, text query progression and citations.
# The differences in approaching a patentability, validity or infringement patent search.
# Issues unique to searching within specific technical disciplines.
# Approaches to searching foreign patents and published applications.
# Considerations in searching non-patent literature.
# Approaches to reporting search results.
# How to select an appropriate search tool.
# Awareness of new developments in patent searching techniques and tools.
A searcher should know all the points made above to generate a good search strategy and ultimately a good report. Visual thinking is an important parameter of a good patent search report. That’s the reason patent intelligence profession in a combination of science and art. Especially the patent mapping is purely an art, and thus mapping and representation of dataset information varies from person to person.
For a patent searcher knowledge of various patent databases is extremely important. He should know the various pros and cons of these databases, along with database behavior in term of searching with the use of operators. For example, the USPTO patent search website allows to search full text and drawings of the entire patent issued since 1975. The full page images of patents since 1790 are also available. Also we can search patent application published since March 15th 2001. Similarly, other database such as EPO, JPO, Depatisnet, SIP, etc. is providing the free search facility. Paid databases such as MicroPat, STN, QPAT provides various handy search techniques and even have more operators. These databases also provide extraction of search results in excel format for further analysis, along with some level of data clustering or mapping.
The following points are very important to keep in mind during patent search:
# How to properly scope the search.
# How to search by classification, text query progression and citations.
# The differences in approaching a patentability, validity or infringement patent search.
# Issues unique to searching within specific technical disciplines.
# Approaches to searching foreign patents and published applications.
# Considerations in searching non-patent literature.
# Approaches to reporting search results.
# How to select an appropriate search tool.
# Awareness of new developments in patent searching techniques and tools.
A searcher should know all the points made above to generate a good search strategy and ultimately a good report. Visual thinking is an important parameter of a good patent search report. That’s the reason patent intelligence profession in a combination of science and art. Especially the patent mapping is purely an art, and thus mapping and representation of dataset information varies from person to person.
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