Patent analysis

Patent law
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Procedural concepts
Patentability requirements and related concepts
Other legal requirements
By region / country
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See also

Patent analysis is the process of analyzing the texts of patent disclosures and other information (such as priority dates, filing and issuance countries, patent maintenance payments, patent citations, patent infringement actions etc.) from the patent lifecycle. Patent analysis is used to obtain deeper insights into different technologies and innovation. Other terms are sometimes used as synonyms for patent analytics: patent landscape, patent mapping, or cartography.[citation needed] However, there is no harmonized terminology in different languages, including in French and Spanish. Patent analytics encompasses the analysis of patent data, analysis of the scientific literature, data cleaning, text mining, machine learning, geographic mapping, and data visualisation.[1]

Patent analytics is used in industry and increasingly[as of?] explored by the public sector to take informed decisions related to prioritization and investments in R&D, IP portfolio management, commercialization of technology, and research collaborations among others.[2][3]

Patent analysis tools and methods have traditionally[when?] been done using spreadsheet-based data analysis methods, such as SQL. However, since ca. 2020 the field of patent analysis has witnessed a convergence of traditional patent analytics with data science, machine learning, semantic technologies, and artificial intelligence[4] along with a surge in available tools that are being applied to patent visualization.[5] There has also been an increase in open-source software, tools[6] and datasets[7] being used for patent analytics, as well as the use of techniques, such as machine learning, for different tasks.[8] Some tools[9] propose semi-automated production of visualizations, dashboards or reports. Terabytes of patent information from many patent offices is available on-line for free from INPADOC or espacenet or Patentscope. Many developers of big data software, such as Google Patents, The Lens, Clarivate Analytics, ip.com, Derwent World Patents Index, and Questel-Orbit, use these free and other patent databases to test the capabilities of their own data analysis software.[citation needed]

  1. ^ Oldham, Paul. Chapter 1 Introduction | The WIPO Patent Analytics Handbook.
  2. ^ Ernst, Holger (2003-09-01). "Patent information for strategic technology management". World Patent Information. 25 (3): 233–242. Bibcode:2003WPatI..25..233E. doi:10.1016/S0172-2190(03)00077-2. ISSN 0172-2190.
  3. ^ Analytics, WIPO Patent (2020-07-14), wipo-analytics/presentations, retrieved 2021-12-30
  4. ^ University, Carnegie Mellon. "About - Center for AI and Patent Analysis - Carnegie Mellon University". www.cmu.edu. Retrieved 2021-12-30.
  5. ^ Kitsara, Irene (29 January 2018). "Stages, Tasks, Workflow and Tools in the preparation of Patent Landscape Reports". WIPO Github. Retrieved 30 December 2021.
  6. ^ "An Overview of Patent Analytics Tools - Paul Oldham's Analytics Blog". www.pauloldham.net. Retrieved 2021-12-30.
  7. ^ de Rassenfosse, Gaétan; Kozak, Jan; Seliger, Florian (6 November 2019). "Geocoding of worldwide patent data". Scientific Data. 6 (1): 260. Bibcode:2019NatSD...6..260D. doi:10.1038/s41597-019-0264-6. PMC 6834584. PMID 31695047.
  8. ^ WIPO (2016). "WIPO Manual on Open Source Tools for Patent Analytics". www.wipo.int. Patent Landscape Reports. doi:10.34667/tind.28980. Retrieved 2021-12-30.
  9. ^ "The Lens - Free & Open Patent and Scholarly Search". The Lens - Free & Open Patent and Scholarly Search. Retrieved 2022-11-30.