中国高校专利统计数据

在教育部、国家知识产权局、科技部等部门的政策措施促进下，我国高校科技成果转化机制更加完善、科研人员转化积极性不断增强、转化效益逐年提升。  作为衡量高校科技创新成效的重要指标，专利统计数据和专利引用数据分别在数量和质量双方面给予数据支持。CnOpenData高校专利数据包含专利统计、专利引用被引用两个部分，其中，专利统计数据分为数量统计表和质量统计表，这两类表分别以专利申请和专利授权为依据再进行划分，更进一步地，专利质量统计表还按专利类型细分为发明、实用新型、外观设计三模块。专利引用及被引信息在此数据中体现于专利详情表部分，与上市公司、工业企业等专利引用被引用数据相同，分发明申请、发明授权、实用新型、外观设计四模块，各模块包含基础信息表、引用表、被引用表、事务表四张表格（外观设计无引用表、被引表、事务表）。

Fueled by policy measures from multiple departments including the Ministry of Education, the National Intellectual Property Administration, and the Ministry of Science and Technology, the mechanism for translating scientific and technological achievements in China's universities has been continuously improved, the enthusiasm of researchers for commercializing research outcomes has been growing, and the benefits of such commercialization have been increasing year by year.

As important indicators for evaluating the effectiveness of scientific and technological innovation in universities, patent statistics data and patent citation data provide data support in terms of quantity and quality respectively. The CnOpenData University Patent Dataset includes two parts: patent statistics and patent citation & cited data. The patent statistics data is divided into quantity statistics tables and quality statistics tables, which are further categorized based on patent applications and patent authorizations respectively. Furthermore, the patent quality statistics tables are subdivided into three modules according to patent types: invention patent, utility model patent, and design patent.

Patent citation and cited information are included in the patent detail tables section of this dataset. Similar to patent citation & cited data of listed companies, industrial enterprises and other relevant entities, this part is divided into four modules: invention application, invention authorization, utility model patent, and design patent. Each module contains four tables: basic information table, citation table, cited table, and transaction table. (Design patents do not have citation tables, cited tables, or transaction tables.)

搜集汇总

背景与挑战

背景概述

该数据集系统收录了中国2000多所高校的专利信息，涵盖专利数量统计、质量统计和专利详情三大模块，时间跨度为1985年至2025年。其核心特点是率先引入了专利质量量化体系，通过区分独立与合作专利、统计技术复杂度（IPC分类号）和年度被引用次数，提供了超越传统数量统计的多维度评价指标。数据采用结构化设计，支持高校创新能力、技术转化与专利质量的深度分析，适用于学术研究、政策制定和商业决策。