摘要
技术路线图是一种有效支撑国家科技战略规划的方法,但是在现实的科技创新政策制定与执行过程中,由于单纯依赖专家先验知识,缺乏客观数据中的后验知识,易造成主观偏误性,导致技术预见、国家战略规划和行动计划的脱节。因此,需要提出一种基于技术知识图谱引导的专家交互技术路线图制定流程。通过绘制技术知识图谱与扫描技术领域态势、制定技术预见清单、专家访谈与问卷调查、技术路线图制定等步骤,支持专家知识与客观数据分析进行多轮交互,帮助专家意见快速收敛,从而更准确的把握未来技术发展方向。以中国工程院和国家自然科学基金委联合开展的"面向未来20年的中国工程科技发展战略研究"中的智能机床领域实证研究,通过专家研讨验证了流程的有效性。提出的流程与方法对国家层面工程科技领域的技术路线图制定有重要支撑作用,通过技术知识图谱引导专家与数据进行多次交互迭代,在降低技术预见过程中主观偏误性的同时,产出可提供基础知识支撑的中间成果,避免长期迭代过程中的信息流失。流程以交互为手段有效连接专家知识和技术客观发展规律形成技术预见,通过预见路线图支持国家战略规划,最终以政策建议辅助落实行动计划。
Technology roadmapping is an effective method to support national science and technology strategic planning. However, in making and implementing science and technology innovation policies in reality, there is a problem of relying solely on prior knowledge of experts and lacking posterior knowledge in objective data. The problem may cause subjective bias, which leads to the disconnect between technology foresight, national strategic planning and action plan.Researchers try to analyze and visualize technical information to support expert discussions, so as to realize the combination of data analysis and expert knowledge. There is still a problem that data analysis and experts are independent of each other and it is difficult to effectively support experts. The knowledge graph provides a way to manage and utilize massive amounts of information efficiently. It displays structured technical information in a graphical manner, helping experts locate and acquire knowledge accurately. Therefore, it is necessary to propose a development process of expert interaction technology roadmapping guided by the technical knowledge graph. The process guides the effective interaction between experts and data through the technical knowledge graph, which can improve the quality of data analysis and enhance the foresight ability of experts. The process of multiple interactions helps to better connect expert knowledge and the objective development laws of technology, and enhances the scientificity and accuracy of the technology roadmapping.The process is mainly divided into four steps. First, with the help of expert knowledge, data analysts develop the domain technical knowledge graph and analyzes the development trend of the technical field. The technical information contained in these two intermediate outputs can enhance the ability of experts to judge the future direction of technological development. Second, experts formulate technical foresight lists through seminars to reach a consensus on key technologies, providing clear discussion items for technology roadmapping. Third, through expert questionnaires and interviews,opinions on the revision of the technical foresight list were widely consulted, so as to supplement and revise the list of technologies with the collective wisdom of experts. Fourth, formulating a technology roadmapping. In this stage, the results of the previous three steps were used as discussion materials to carry out multiple rounds of seminars. Experts exchange opinions and finally reach a consensus on the technology development path.This research takes the 2035-oriented intelligent machine tool technology roadmapping as a case study. The case has also verified that the proposed process and methods have an important supporting role in the formulation of technology roadmapping in the field of engineering science and technology at the national level, which are mainly reflected in: the technical knowledge graph is used to guide multiple interactive iterations of expert knowledge and data analysis, realizing the combination of experts, data and computer technology, and enhancing the overall ability to grasp the decision-making scheme of complex systems. The technical field situation analysis report and technical foresight list provide basic knowledge support for expert decision-making. Such intermediate results avoid the loss of information during the long-term iteration of the technical roadmap, thereby alleviating to a certain extent the problem that the iteration of the roadmap is limited by the time cost of experts. This research initially explores how to effectively combine data and expert knowledge from a technical perspective, and considers the impact of technology promotion in the development of technology on the formulation of the technology roadmapping. However, the social and economic demand pulling is less involved, which is the future research direction.
作者
刘宇飞
周源
褚恒
唐杰
LIU Yufei;ZHOU Yuan;CHU Heng;TANG Jie(Center for Strategic Studies,Chinese Academy of Engineering,Beijing 100088,China;School of Public Policy and,Management,Tsinghua University,Beijing 100084,China;School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,China;Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China)
出处
《科学学与科学技术管理》
CSSCI
CSCD
北大核心
2021年第3期29-47,共19页
Science of Science and Management of S.& T.
基金
国家自然科学基金项目(71974107,91646102,L1924058,L1824039,L1724034)
中国工程科技知识中心建设项目(CKCEST-2021-2-7)
清华大学—剑桥大学自主科研国际合作专项(2019Z02CAU)
清华大学绿色经济与可持续发展研究中心研究项目(20183910020)
中国工程科技发展战略江苏研究院咨询研究项目(JS2019ZT15,JS2020ZT08,JS2019ZT14)
教育部人文社会科学研究专项任务项目(16JDGC011)。
关键词
技术路线图
工程科技
知识图谱
专家交互
智能机床
technology roadmapping
engineering science and technology
knowledge graph
expert interaction
intelligent machine tools
