Innovation serves as the fundamental driver of economic development. As the basic unit of economic society, the innovation investment of individual enterprises not only forms the foundation for their long-term development but also plays 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 citation frequency, grant ratios, technological coverage, and number of claims all constitute evaluation criteria for patent quality.
Patent citations occur when a patent is referenced by subsequent patent applicants or examiners, indicating technical correlations between patents. Originating from the Science Citation Index (SCI), patent citations form a knowledge network analogous to academic literature references. Around February 1947, the USPTO (United States Patent and Trademark Office) pioneered listing prior art references in granted patents for technical evaluation. Currently, patent citation information primarily derives from two sources:
- First, references provided by inventors during application, typically disclosed in sections like "Background Technology" within patent specifications to articulate distinctions from existing technologies and demonstrate novelty. For instance, the U.S. patent system mandates applicants to submit all relevant technical materials through an Information Disclosure Statement (IDS); non-compliance may result in patent invalidation.
- Second, references added by patent examiners during review. To assess novelty and inventiveness, examiners conduct prior art searches to identify technologies closest to the claimed invention.
Patent citation data serves at least two critical purposes:
- Tracking technological evolution and knowledge flows. Since Narin (1994) introduced bibliometrics into patent analysis, patent citations have been recognized as objective indicators of knowledge linkages. Citation networks reveal dynamic innovation processes and inter-sectoral/inter-industry knowledge transfer patterns.
- Measuring innovation quality and value. Innovation assessment requires moving beyond quantity metrics, as patent significance varies substantially. Citation analysis provides insights into patent quality and technological value that raw counts cannot capture.
The seminal work Patents, Citations, and Innovations by Adam Jaffe and Manuel Trajtenberg establishes methodologies for analyzing technological trends and patent value through citation networks.
CnOpenData has systematically organized South Korean Patent Data into a specialized database, offering comprehensive support for relevant research.
Data Features
- Contains both citation references made by patents and citations received by patents
- Records current legal status information（法律状态信息） for each patent
Time Coverage
1985 - December 31, 2024
Field Display
Sample Data
Basic Information of South Korean Patents
South Korean Patent Citation Information
South Korean Patent Cited-by Information
South Korean Patent Transaction Records
South Korean Patent Literature Citation Information
South Korean Patent Classification Codes
Data Update Frequency
Annual updates