摘要 科研大数据共生作为科研大数据共享的重要过程,在科研数据生成过程中发挥着至关重要的作用,探究其内在机理具有重要的理论价值和实践价值。文章在共生理论的基础上,给出"科研大数据共生"的概念,构建了科研大数据共生模型(SM-SRBD),然后从维度分析、共生方程分析与寄生机制的关联分析等几个方面,深入阐释了科研大数据共生的内在运行机理,分析了科研大数据共生和寄生之间的趋利型和趋害型两类演化路径。研究表明:科研大数据共生是一个以利益维、自由度维、空间维、时间维、强度维等不同维度的共生活动为核心活动体系,以"共生数据源"为基,以"数据共生方程"为过程逻辑,以实现优势互补、共同成长(或偏利成长)并生成共生化新数据、构建科研大数据命运共同体、提升科研大数据质量为目标,不断趋于优化的泛在化、协同化的动态进化过程。 As an important process of scientific research big data sharing,Symbiosis for Scientific Research Big Data(SSRBD)plays an important role in the generation process of scientific research data.Exploring its internal mechanism has important theoretical and practical value.based on the symbiosis theory,this paper gives the concept of"scientific research big data symbiosis"and constructs the Symbiosis Model for Scientific Research Big Data(SM-SRBD),and deeply explains the internal operation mechanism of SSRBD from the dimension analysis,symbiosis equation analysis,and correlation analysis with parasitic mechanism,and then analyzes the two kinds of evolution paths of profit oriented and harm oriented between symbiosis and parasitism of SRBD.Research shows that:SSRBD is a ubiquitous and collaborative dynamic evolution process which is with different dimensions of symbiotic activities such as interest dimension,freedom dimension,space dimension,time dimension,intensity dimension and form dimension as the core activity system,with"symbiotic data source"as the basis,and"data symbiosis equation"as process logic,with the goal of complementing mutual advantages,growing together(or favorably growing),generating"new symbiosis data",building a"community of common destiny"for scientific research big data and improving the quality of scientific research big data.
机构地区 山东理工大学信息管理研究院 山东理工大学管理学院
出处 《情报理论与实践》 北大核心 2021年第3期19-26,52,共9页 Information Studies:Theory & Application
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”的成果之一,项目编号:19BTQ077。
关键词 科研大数据 科研大数据共生 泛在性 维度分析 共生方程 演化路径 scientific research big data scientific research big data symbiosis ubiquity dimension analysis symbiosis equation evolution path
分类号 G64 [文化科学—高等教育学]
