| 基于双源数据的云计算创新合作网络多维分析 |
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| 引用本文： | 武兰芬,姜军.基于双源数据的云计算创新合作网络多维分析[J].科研管理,2006,41(2):142-151. |
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| 作者姓名： | 武兰芬 姜军 |
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| 作者单位： | 1.南京理工大学知识产权学院, 江苏 南京210094;
2.南京理工大学江苏人才发展战略研究院, 江苏 南京210094 |
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| 摘 要： | 本文以2002-2016年间的学术文献和专利两种数据源为基础，利用社会网络分析法从论文作者所属机构与专利权人、作者与发明人、学科与技术领域等多维视角，对全球云计算基础研究与应用研究的创新合作网络进行数据挖掘和对比分析。研究发现：云计算论文作者及所属机构间的合作更普遍；专利权人合作网络呈现分散的小网络特点，专利发明人合作关系更密切且群体性更强；云计算的基础学科是计算机理论与方法、电气与电子工程和计算机信息系统，而核心技术是数字计算机和电话与数据传输系统。基于研究结果，提出建立基础创新与应用创新的对接和融合，利用合作网络分析发掘重要的创新竞合对象，精准定位领军人才和创新群体，构建学科知识体系等促进中国云计算协同创新与产教融合的启示和建议。
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| 收稿时间： | 2018-02-28 |
A multidimensional analysis of innovative collaboration networks in cloud computing based on dual-source data |
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| Wu Lanfen,Jiang Jun.A multidimensional analysis of innovative collaboration networks in cloud computing based on dual-source data[J].Science Research Management,2006,41(2):142-151. |
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| Authors: | Wu Lanfen Jiang Jun |
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| Abstract: | Innovative collaboration has become an accelerator to drive scientific and technological innovation and economic development. And the characteristics of innovative collaboration network can reflect the characteristics and scope of knowledge flow. Academic publications and patent applications are two of the most important forms of scientific innovation and technological invention. Academic literature represents advances in basic scientific knowledge while patents can demonstrate technological knowledge with significant commercial potential. Past researches primarily have used social network analysis to study innovative collaboration network from different perspectives based on paper or patent data.
These studies basically utilize one single data source, i.e. paper data or patent data to analyze the structural characteristics of innovative collaboration network, knowledge flow, and impact on innovation. In the context of increasingly diversified innovation, it is necessary to analyze the structure and characteristics of the innovative collaboration network from the perspective of multi-data sources, so as to reflect the collaboration relationships between the innovative subjects in scientific and technological innovation more comprehensively, and to find out a richer network connotation.
In order to study the collaboration development status of innovative network in basic scientific research and industrial technology applications of cloud computing, this paper uses social network analysis to comparatively analyze paper and patent data during the interval 2002-2016 from multi-dimensional perspectives such as institutions, individuals, disciplines or technological fields. It aims to demonstrate the innovative collaboration network in cloud computing to provide more complete and accurate analysis for the collaboration of scientific and technological innovation in cloud computing.
Scientific paper data is collected in Science Citation Index Expanded (SCI-E) and Conference Proceedings Citation Index- Science (CPCI-S) from Web of Science database, including journal papers and conference papers. Patent data is collected from the Derwent Innovations Index (DII) database. Searches are made through paper or patent name fields in August 2017. Paper and patent data are collected up to 2016. After data cleaning, the results of the SCI-E and CPCI-S databases are 10,781 papers, of which 2335 are journal papers and 8511 are conference papers. The DII database has a search result of 13,658 patent families. A patent family represents a technological invention, a collection of patent applications in multiple countries for the same invention.
Comparing the annual trends of paper publications and patent applications, we can find that their total number is equal between 2002 and 2006. The annual number of paper publications is higher than the annual number of patent applications during the interval 2007-2012. It is the reverse in 2013-2016, and the gap between patent and paper data is widening. In the top ten institutions for paper publications in cloud computing, the influential ones are all universities or institutes. Except for one Korean university, all the others are from China, with eight universities and one research institutes. The influential institutions in patent applications of cloud computing are all companies, with five from the US, four from China and one from the UK in the top ten institutions.
Institutional collaboration can be reflected in the network interrelated by literature, which is used to study the emergence and dissemination of new ideas or the academic development in certain fields. The integrity of institutional collaboration network affects the strength of knowledge sharing and information diffusion.In institutional collaboration network of cloud computing, the nodes denote the author′s institutions or patent assignees, while edges denote the collaboration relationship between the institutions or assignees.
The structure and characteristics of collaboration network of scientists or inventors can be visualized using social network analysis, based on the co-occurrence data of authors or inventors. In collaboration network of authors and inventors, nodes denote authors or inventors, while edges denote the collaboration relationship between authors or inventors.
By using network analysis method to study the collaboration network of disciplines and technology fields, we can find out basic disciplines, interdisciplinary disciplines, core technology areas, and their co-occurrence relationship. In collaboration network of disciplines and technologies, nodes denote disciplines or technology areas, while edges denote the co-occurrence relationship between disciplines or technology areas.
We present the research results as follows. First, the development of global cloud computing technology has shifted from basic research innovation to commercial application innovation since 2013. Second, the basic research of cloud computing is centralized in universities and institutes, while application technology research is centralized in the company. The collaboration between the paper authors is more common. However, the collaboration network of patentees is more decentralized. The patentee network structure shows the characteristics of more small networks. And certain patentees have very close collaboration relationship. Third, the number of influential patent inventors in cloud computing is greater than that of influential authors. And the collaboration network between authors is more common. But the collaboration relationship between patent inventors is closer and more grouped. Fourth, the three basic disciplines of cloud computing are computer theory and method, electrical and electronic engineering, and computer information system. Cloud computing mainly relates to the disciplines such as telecommunications, computer hardware and architecture, software engineering, artificial intelligence and computer cross-disciplinary applications, which spread around the three basic disciplines. The core technology of cloud computing is digital computer, telephone and data transmission system. The main technological fields involve computer peripherals, process and mechanical control, alarm, signal, telemetry and remote control.
Based on the above analysis, the following enlightenments and suggestions are put forward from the perspectives of research and development collaboration, talent recruitment and discipline construction. First, the connection and fusion can be established between basic scientific innovation and industrial technological innovation to accelerate the innovation-driven development of China′s cloud computing industry. Second,influential competitors and collaborators and their networks can be found out by visualizing institutional collaboration network to build collaborative ecosystem in industry innovation of cloud computing. Third, leading innovative talents and innovative groups can be identified accurately in cloud computing by use of the collaboration networks of paper authors and patent inventors. Finally, knowledge of basic disciplines, interdisciplinary disciplines, core technologies and major technology fields can be obtained by use of the collaboration network analysis of disciplines and technology fields. This can provide the construction of discipline knowledge system for the cultivation of innovative talents in cloud computing. |
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