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作 者:佟泽华[1] 丰佰恒 石江瀚 孙晓彬 Tong Zehua;Feng Baiheng;Shi Jianghan;Sun Xiaobin(Institute of Information Management,Shandong University of Technology,Zibo 255000)
机构地区:[1]山东理工大学信息管理研究院,淄博255000
出 处:《情报杂志》2022年第9期121-128,98,共9页Journal of Intelligence
基 金:国家社会科学基金项目“数据生态视角下科研大数据协同治理研究”(编号:19BTQ077)的究成果之一。
摘 要:[研究目的]为响应国家大数据发展战略,完善科研大数据治理理论,提升科研人员数据治理能力,继而维护科研大数据生态系统稳定。[研究方法]针对科研大数据治理现存问题,在现有的双螺旋、三螺旋、四螺旋模型研究基础上,构建了科研大数据治理多螺旋联动模型并以中国科学院数据云为例对其应用场景进行了分析。[研究结论]研究表明,多螺旋联动模型是在数据维度混乱、数据不对称引用、生态关系薄弱、国际数据壁垒等问题下催生的,以控制科研数据质量、保护科研数据安全、维护科研大数据生态系统稳定为目标,以降维旋、定位旋、转化旋为核心,以人员旋、服务旋、管理旋、数据旋、技术旋、X旋、Y旋、Z旋为辅助,以数据降维、快速定位、线性转化为策略的多螺旋联动的具有较强适用性的科研大数据治理模型。[Research purpose]Respond to the national big data development strategy,improve the theory of scientific research big data governance,enhance the data governance ability of researchers and maintain the stability of the scientific research big data ecosystem.[Research method]Aiming at the solving existing problems of big data governance for scientific research,a multi-helix linkage model for big data governance for scientific research was constructed based on the existing double helix,triple helix and quadruhelix models,and its application scenarios were analyzed by taking the data cloud of Chinese Academy of Sciences as an example.[Research conclusion]Research shows that spiral linkage model was developed because of the more chaotic,asymmetric data in data dimension reference,weak ecological relationship and the problem such as barriers to international data,its goals involve controlling the quality of scientific research data,protecting the safety of the scientific research data and sustaining the stability of the scientific research big data maintenance ecosystem.Dimension reduction,positioning screw,transformation act as the core of the model.With the assistance of personnel rotation,service rotation,management rotation,data rotation,technology rotation,X rotation,Y rotation and Z rotation,it is a multi-spiral linkage governance model of scientific research big data with strong applicability and adopts data dimension reduction,fast positioning and linear transformation as strategy.
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