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Updated: Nov 24, 2025

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
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Imputation of missing information in worldwide patent data.

Gaétan de Rassenfosse1, Florian Seliger2

  • 1Chair of Innovation and Intellectual Property Policy, College Management of Technology, Ecole polytechnique fédérale de Lausanne Switzerland.

Data in Brief
|December 23, 2020
PubMed
Summary

We developed a method to fill in missing patent data in the Worldwide Patent Statistical Database (PATSTAT). This improves the accuracy of global technology activity analysis using patent information.

Keywords:
ImputationMissing dataPATSTATPatentsPostgreSQL

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Area of Science:

  • Bibliometrics
  • Data Science
  • Intellectual Property

Background:

  • The Worldwide Patent Statistical Database (PATSTAT) is crucial for academic patent research.
  • Incomplete data in PATSTAT hinders accurate analysis of technological activities.
  • Missing country codes and technology classifications are significant data gaps.

Purpose of the Study:

  • To present a general method for imputing missing information in the PATSTAT database.
  • To release publicly available datasets and algorithms for data imputation.
  • To enhance the completeness and accuracy of patent data for research.

Main Methods:

  • Developed a SQL algorithm leveraging institutional knowledge of the international patent system.
  • Applied the algorithm to impute missing country codes.
  • Applied the algorithm to impute missing technology classifications.

Main Results:

  • Created and released two datasets with imputed country codes and technology classifications.
  • The imputation method is generalizable to other missing information in PATSTAT.
  • Publicly available imputed datasets and the imputation algorithm.

Conclusions:

  • The developed imputation method significantly improves the completeness of PATSTAT.
  • The publicly released datasets and algorithm facilitate more accurate patent data analysis.
  • This work supports robust research on global technological trends.