Innovation serves as the primary driver of economic development. As fundamental units of economic society, the innovation investments of individual enterprises not only form the foundation for long-term corporate growth but also play a crucial role in shaping the global innovation landscape. A direct manifestation of corporate R&D capabilities lies in both the quantity and quality of patents. However, patent quality cannot be assessed unidimensionally—metrics such as patent citations, grant ratios, technological coverage, and number of patent claims (专利权利要求数) all serve as evaluative criteria for patent quality.
Patent citations refer to the referencing of prior patents by subsequent patent applicants or examiners, indicating technical correlations between patents. Originating from the Science Citation Index (SCI), patent citations construct a knowledge network analogous to academic literature references. Around February 1947, the USPTO (United States Patent and Trademark Office) pioneered the inclusion of prior art references in granted patent documents for evaluating patent claims. Currently, patent citation information primarily derives from two sources:
- First, references provided by inventors during application preparation, typically cited in sections like "Background Art" within patent specifications to delineate technical distinctions from existing knowledge and demonstrate novelty. For instance, the U.S. patent system mandates applicants to disclose all relevant prior art through Information Disclosure Statements (IDS); non-compliance may result in patent invalidation.
- Second, references added by patent examiners during prosecution. Examiners conduct prior art searches to assess the novelty and inventive step of patent applications within relevant technical domains.
Patent citation data serves at least two critical functions:
- Tracking technological trajectories and knowledge flows. Since Narin (1994) introduced bibliometric methods into patent analysis, patent citations have been recognized as objective indicators of knowledge linkages. Citation relationships between patents imply knowledge utilization from cited inventions. Citation networks reveal dynamic innovation processes and inter-sectoral/inter-industrial knowledge diffusion patterns.
- Measuring innovation quality and value. Innovation assessment requires qualitative differentiation beyond quantitative counts, as patent values exhibit significant heterogeneity. Citation frequency provides critical insights into patent quality and technological impact.
The seminal work Patents, Citations, and Innovations by Adam Jaffe and Manuel Trajtenberg establishes foundational methodologies for analyzing technological evolution and patent value through citation networks.
CnOpenData has systematically organized Japanese Patent Information Data into a dedicated database, providing comprehensive and granular data support for related research.
Data Features
- Contains detailed information on both citing patents (forward citations) and cited patents (backward citations).
- Includes current legal status (法律状态) tracking for each patent.
Temporal Coverage
1985-2024.12.31
Field Specifications
Sample Data
Japanese Patent Basic Information Table
Japanese Patent Citation Information Table
Japanese Patent Cited Information Table
Japanese Patent Reference Literature Table
Japanese Patent Transaction Records Table
Japanese Patent Classification Codes Table
Data Update Frequency
Annual updates