Various stakeholders, such as researchers, government agencies, businesses, and research laboratories require a large volume of reliable scientific research outcomes including research articles and patent data to support their work. These data are crucial for a variety of application, such as advancing scientific research, conducting business evaluations, and undertaking 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 existing open dataset releases typically suffer from lack of relationship between different data sources and a limited temporal coverage. To address this issue, we present a new open dataset, the Intelligent Innovation Dataset (IIDS), which comprises six interrelated datasets spanning nearly 120 years, encompassing paper information, paper citation relationships, patent details, patent legal statuses, and funding information. The extensive contextual and extensive temporal coverage of the IIDS dataset will provide researchers and practitioners and policy maker with comprehensive data support, enabling them to conduct in-depth scientific research and comprehensive data analyses.

翻译：研究人员、政府机构、企业及研究实验室等各类利益相关方，需要大量可靠的科学研究成果（包括研究论文和专利数据）以支持其工作。这些数据对于推进科学研究、开展商业评估及进行政策分析等多种应用至关重要。然而，收集此类数据通常是一项耗时费力的任务。因此，许多用户转而使用公开可获取的数据进行研究。然而，现有的开放数据集发布通常存在不同数据源之间缺乏关联以及时间覆盖范围有限的问题。为解决这一问题，我们提出了一个新的开放数据集——智能创新数据集（IIDS），该数据集包含六个相互关联的子数据集，时间跨度近120年，涵盖论文信息、论文引用关系、专利详情、专利法律状态以及资助信息。IIDS数据集广泛的上下文信息和长时间跨度的覆盖，将为研究人员、从业者和政策制定者提供全面的数据支持，使其能够开展深入的科学研究与综合的数据分析。