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A dataset of scientific citations in U.S. patent Office Actions

Author

Listed:
  • Kyle Higham

    (Motu Economic and Public Policy Research)

  • Hannah Kotula

    (Motu Economic and Public Policy Research)

  • Emma Scharfmann

    (University of California, Berkeley)

  • Steve Gong

    (Google)

  • Gaétan de Rassenfosse

    (Ecole polytechnique fédérale de Lausanne)

Abstract

We present a curated dataset of about 850,000 citations extracted from Office Actions issued by examiners at the United States Patent and Trademark Office. These references, historically underused due to accessibility challenges, provide a granular view into the patent examination process and complement traditional front-page citation data. We classify each citation into one of 14 categories and focus on the 265,000 references to scientific literature, which we parse, clean, and disambiguate using machine learning and external bibliographic services. To enhance reusability, disambiguated records are linked to OpenAlex, a comprehensive research metadata platform. The dataset enables new research on examiner behavior, science–technology linkages, and the construction of citation-based metrics. All data and code are openly available to facilitate reuse across disciplines.

Suggested Citation

  • Kyle Higham & Hannah Kotula & Emma Scharfmann & Steve Gong & Gaétan de Rassenfosse, 2026. "A dataset of scientific citations in U.S. patent Office Actions," Working Papers 31, Chair of Science, Technology, and Innovation Policy.
    • Handle: RePEc:iip:wpaper:31
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    References listed on IDEAS

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    More about this item

    Keywords

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    JEL classification:

    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital
    • K29 - Law and Economics - - Regulation and Business Law - - - Other
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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