摘要
作为科研大数据共享的核心过程,科研大数据再生在科研创新活动中发挥着重要的作用。文章基于再生理论,在对科研大数据再生概念进行界定和特性分析的基础上,构建了科研大数据再生模型(RM-SRBD),然后从阶段分析、核心活动维度分析、转化分析、状态演化分析、循环反馈路径分析等几个方面对模型的运行机理进行了解析。研究表明,科研大数据再生的过程可以看成是一个以"科研大数据再生需求""科研大数据再生核心活动""科研大数据再生应用"为阶段,以修复性、重用性、继承性、可溯源性、增值性等为特性,以结构、空间、时间、过程、关联程度、有益性等不同维度的再生活动为核心活动体系,以单阶反馈、双阶反馈与有利性反馈(同时也存在着有害性反馈)为循环反馈路径,以"旧数据"为基,实现数据再生优化并生成"新数据"为目标,进而使之焕发生命活力,阶跃式、非线性、迭代式的周期性动态演化过程。
As the core process of scientific research big data sharing,the regeneration of scientific research big data plays an important role in scientific research innovation activities.Based on the definition and characteristic analysis of the concept of research big data regeneration,this paper constructs the Regeneration Model for Scientific Research Big Data(RM-SRBD),and then,the operation mechanism of the model is analyzed from several aspects,such as stage analysis,core activity analysis,transformation analysis,state evolution analysis and loop feedback analysis.The research shows that:the process of scientific research big data regeneration can be seen as a stage of"scientific research big data regeneration demand""scientific research big data regeneration core activity""scientific research big data regeneration application";it is characterized by repairability,reusability,inheritance,provenance,value-added,etc.;it is with different dimensions such as structure,space,time,process,relevance,and usefulness;its circular feedback path includes the one-step feedback,two-step feedback and favorable feedback(there is harmful feedback at the same time);it is based on"old data",with the goal of achieving data regeneration and optimization,generating"new data"and making it full of vitality;it is a steped,non-linear and iterative periodic dynamic evolution process.
出处
《情报理论与实践》
CSSCI
北大核心
2020年第9期39-46,78,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
再生
内涵
核心活动
循环反馈路径
scientific research big data
regeneration
connotation
core activities
loop feedback path
