Today’s read is a bit different from the latest ones. Following my research stay in Barcelona, I’ve being compiling some previous papers related to Patents and SEO. While searching, I came across a paper by Burhan and Jain that goes to the basics of how to obtain information related to patents. I find this essential, as navigating the enormous (and fragmented) world of patent information is not straightforward. The paper compiles the main tools and strategies available in 2012 to manage patent search and analysis efficiently.
Burhan, M., & Jain, S. K. (2012). Tools for Search, Analysis and Management of Patent Portfolios. DESIDOC Journal of Library & Information Technology, 32(3).
https://doi.org/10.14429/djlit.32.3.2376 [Cris-Note: DOI was not working so I've attached the PDF on ResearchGate 🙏🏻]
Mapping the landscape of Patent Portfolio Tools:
The authors position patent documents as an exceptionally rich source of technical information. Since they are published shortly after filling, 18 months more or less and always before the corresponding scientific literature, they act as early indicators of technological trends. R&D directions, collaborations, and competitive strategies.
They argue that effective patent portfolio management is a cornerstone of corporate strategy. Patent data is used not only to monitor competitors but also to identify opportunities, reduce investment risk, and build technological foresight.
The paper builds on earlier work emphasising patent information systems as essential for competitive intelligence. What stands out is the emphasis on online search tools, which have transformed what was once a labour-intensive and fragmented process into something more systematic, faster, and potentially more strategic.
The method:
This article adopts a descriptive and comparative approach, reviewing different types of patent studies, search strategies, and portfolio management tools. It does not involve new empirical research but instead provides a structured map of available approaches and databases.
The methodological structure covers:
- Types of patent searches: landscape, validity, novelty, freedom to operate.
- Core search syntax: boolean, proximity, wildcard, nesting.
- Search strategies: quick searches, classification-based, sequence-based, chemical patent searching, text searching.
- Patent information systems and tools for IP portfolio management.
Note: the tables of the paper summarize perfectly the different categories and offer the information in a very well structured way, I think they are worth taking a look.
Key Points:
- Patent search types are purpose-driven:
- Landscape search: gives a broad overview.
- Validity search: test patent strength.
- Novelty search: help draft new patents.
- FTO search: assess potential infringement risks.
- Search syntax matters as it can drastically improve both recall and precision.
- Boolean operators: AND, OR, NOT
- Proximity search: find words as a phrase, within a specified radius, near 10 words, before a word, or after a word.
- Wildcards: the * can be used to truncate or as a multi-caracter in a word (e.g., behavi*r retrieves behaviour or behavior).The ? can be used to find alternative spellings (e.g., wom?n to find woman or women).
- Nesting: to group words os phrases. E.G.: (mouse or mice).
- Classification systems remain powerful as they help navigate language and terminology differences that keyword searches alone might miss. There are several to have in mind: IPC, USPC, ECLA, DEKLA, among others.
- There is a huge diversity on databases, from public (like Patentscope) to commercial (such as Thomson Reuters Innovation), that offer varying levels of depth, coverage, and analytical features.
- The use of macros, clustering, mapping, and citation analysis supports more efficient decision-making.
Limitations & What’s left to explore:
The paper offers a thorough overview, but it does not empirically assess the tools’ effectiveness in practical context. Also, its focus remains on search and analysis, with limited attention to how these insights inform strategic or policy decisions. Moreover, being a descriptive review, it lacks comparative performance metrics beyond basic database coverage.
Conclusions:
This article provides a clear and structured overview of the ecosystem of patent search and portfolio management tools, highlighting the importance of using the right strategy for the right purpose.
Although it was published over a decade ago, many of the principles remain relevant today, particulary the need to balance precision and recall, and integrate different data sources.
See you in the next paper =)