Intelligent Innovation Dataset on Scientific Research Outcomes and Patents
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 advanc...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2025-03-01
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| Series: | Journal of Social Computing |
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| Online Access: | https://www.sciopen.com/article/10.23919/JSC.2024.0033 |
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| author | Xinran Wu Hui Zou Yidan Xing Jingjing Qu Weiwei Guo Xiaoming Fu |
| author_facet | Xinran Wu Hui Zou Yidan Xing Jingjing Qu Weiwei Guo Xiaoming Fu |
| author_sort | Xinran Wu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c0c7d58d2b174be68f8f4ad27e127d79 |
| institution | OA Journals |
| issn | 2688-5255 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Journal of Social Computing |
| spelling | doaj-art-c0c7d58d2b174be68f8f4ad27e127d792025-08-20T01:47:54ZengTsinghua University PressJournal of Social Computing2688-52552025-03-0161637310.23919/JSC.2024.0033Intelligent Innovation Dataset on Scientific Research Outcomes and PatentsXinran Wu0Hui Zou1Yidan Xing2Jingjing Qu3Weiwei Guo4Xiaoming Fu5Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai 200433, ChinaDepartment of Library and Information Science, Shanghai University, Shanghai 200444, ChinaBoguan Innovation (Shanghai) Big Data Technology Co., Ltd., Shanghai 200082, ChinaShanghai Artificial Intelligence Laboratory, Shanghai 200082, ChinaDepartment of Management, Fudan University, Shanghai 200433, ChinaShanghai Key Laboratory of Intelligent Information Processing, Fudan University, Shanghai 200433, China, and also with the Institute of Computer Science, University of Göttingen, Göttingen 37073, GermanyVarious 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.https://www.sciopen.com/article/10.23919/JSC.2024.0033open datasetdata analysispaper informationpatent detailsfunding informationdata completenessdata reliabilitytemporal coverage |
| spellingShingle | Xinran Wu Hui Zou Yidan Xing Jingjing Qu Weiwei Guo Xiaoming Fu Intelligent Innovation Dataset on Scientific Research Outcomes and Patents Journal of Social Computing open dataset data analysis paper information patent details funding information data completeness data reliability temporal coverage |
| title | Intelligent Innovation Dataset on Scientific Research Outcomes and Patents |
| title_full | Intelligent Innovation Dataset on Scientific Research Outcomes and Patents |
| title_fullStr | Intelligent Innovation Dataset on Scientific Research Outcomes and Patents |
| title_full_unstemmed | Intelligent Innovation Dataset on Scientific Research Outcomes and Patents |
| title_short | Intelligent Innovation Dataset on Scientific Research Outcomes and Patents |
| title_sort | intelligent innovation dataset on scientific research outcomes and patents |
| topic | open dataset data analysis paper information patent details funding information data completeness data reliability temporal coverage |
| url | https://www.sciopen.com/article/10.23919/JSC.2024.0033 |
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