关于科研成果和专利的智能创新数据集

Xinran Wu, Hui Zou, Yidan Xing, Jingjing Qu, Qiongxiu Li, Renxia Xue, Xiaoming Fu
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引用次数: 0

摘要

研究人员、政府机构、企业和实验室等各利益相关方都需要可靠的科研成果和专利数据来支持他们的工作。这些数据对于推进科学研究、开展商业评估和政策分析至关重要。因此,许多用户转而使用可公开访问的数据进行研究。然而,这些开放数据的发布可能存在不同数据源之间缺乏关联或时间覆盖范围有限的问题。在这种情况下,我们提出了一个新的智能创新数据集(IDS数据集),它由六个相互关联的数据集组成,时间跨度近120年,涵盖论文信息、论文引用关系、专利详情、专利法律状态、资助信息和资助关系。IIDS 数据集广泛的上下文和时间覆盖将为研究人员提供全面的数据支持,使他们能够深入开展科学研究并进行全面的数据分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Innovation Dataset on Scientific Research Outcomes and Patents
Various stakeholders, such as researchers, government agencies, businesses, and laboratories require reliable scientific research outcomes and patent data to support their work. These data are crucial for advancing scientific research, conducting business evaluations, and policy analysis. However, collecting such data is often a time-consuming and laborious task. Consequently, many users turn to using openly accessible data for their research. However, these open data releases may suffer from lack of relationship between different data sources or limited temporal coverage. In this context, we present a new Intelligent Innovation Dataset (IIDS dataset), which comprises six inter-related datasets spanning nearly 120 years, encompassing paper information, paper citation relationships, patent details, patent legal statuses, funding information and funding relationship. The extensive contextual and extensive temporal coverage of the IIDS dataset will provide researchers with comprehensive data support, enabling them to delve into in-depth scientific research and conduct thorough data analysis.
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