科研大数据质量管控模型仿真研究被引量：8

Simulation Research on Scientific Research Big Data Control Model

导出

摘要 [目的/意义]大数据时代科研数据激增,与此同时劣质科研数据的传播给中国与世界的科研工作带来巨大的挑战,如何合理有效地管控劣质科研数据是科研工作所面临的难题。[方法/过程]面向科研大数据质量管控的紧迫需求,结合博弈论模型、改进病毒传播SIR模型构建科研大数据质量管控模型(CM-SRBD),并对科研大数据各阶段管控措施效果进行仿真模拟。[结果/结论]研究表明,科研大数据质量管控是一个以控制劣质科研大数据在数据生态链中传播、提升科研大数据质量为目标,以“源头博弈阶段(G)—传播阻隔阶段(D)—修复淘汰阶段(E)”(GDE)为一体化管控阶段,以建立产出质量控制机制、设立数据隔离空间单元、引入劣质状态优选机制为管控策略体系,进而对具有“致命性、隐藏性、专业性、潜伏性”的劣质科研大数据实现有效管控,以减少易劣质科研大数据、快速发掘暗劣质科研大数据、有效优化数据修复流程,从而维护科研大数据生态平衡的动态过程。 [Purpose/significance]In the era of big data,scientific research data are proliferating,and at the same time,the dissemination of inferior scientific research data brings great challenges to the scientific research work in China and the world.How to reasonably and effectively control inferior scientific research data is a difficult problem for scientific research work.[Method/process]To meet the urgent needs of big data quality control for scientific research,the CM-SRBD was constructed by combining game theory model and SIR model of improved virus transmission,and the effect of control measures at all stages of big data for scientific research was simulated.[Result/conclusion]Research shows that the scientific research and large data quality control is a big data to control the inferior scientific research in data chain transmission,improve the scientific research data quality as the goal,to“source game stages(G)-spread block(D)-repair the knockout stage(E)”(GDE)for the integration of control stage,to establish production quality control mechanism,set up data isolation space unit,into the inferior state optimization mechanisms for the control strategy of system,and then to“fatal,hidden,professionalism,latent”big inferior scientific data to realize the effective control,In order to reduce the bad scientific research big data,quickly explore the bad scientific research big data,effectively optimize the data repair process,so as to maintain the dynamic process of ecological balance of scientific research big data.

作者丰佰恒佟泽华韩春花薛晓娜冯晓孙晓彬 Feng Baiheng

机构地区山东理工大学信息管理研究院

出处《情报理论与实践》 CSSCI 北大核心 2021年第9期33-42,共10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。

关键词大数据科研数据科研数据管理科研大数据质量管控大数据治理博弈论仿真 big data scientific research data scientific research data management scientific research big data quality control big data governance game theory simulation

分类号 TP311.13 [自动化与计算机技术—计算机软件与理论]