文章摘要
陈氢,李承濠.面向数智赋能的开放科学数据平台研究[J].数字图书馆论坛,2024,20(5):13~21
面向数智赋能的开放科学数据平台研究
Open Science Data Platform for Digital Intelligence Empowerment
投稿时间:2024-02-20  
DOI:10.3772/j.issn.1673-2286.2024.05.002
中文关键词: 开放科学数据平台;数智赋能;数智环境;科学数据;数据治理
英文关键词: Open Science Data Platform; Digital Intelligence Empowerment; Digital Intelligence Environment; Scientific Data; Data Governance
基金项目:本研究得到湖北省教育厅哲学社会科学研究重点项目“数字政府建设视域下智慧政务服务聚合模式研究”(编号:22D048)资助。
作者单位
陈氢 湖北工业大学经济与管理学院;湖北循环经济发展研究中心 
李承濠 湖北循环经济发展研究中心 
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中文摘要:
      构建面向数智赋能的开放科学数据平台,以应对现有平台存在的科学主体需求识别分析欠缺、科学资源价值实现困难、数智技术应用落后、标准规范指引模糊等问题,从而动态满足科学主体的智能化需求、充分释放科学资源的潜在价值、深度融合数智技术体系、创新科学资源管理标准规范。首先分析开放科学数据平台现有问题,其次明晰面向数智赋能的开放科学数据平台构建价值,再次构建由智慧服务层、智能业务层、资源存储层、标准规范层、基础设施层构成的平台体系结构,最后从管理服务、科学服务双维度论述平台运行流程。以期实现数智赋能与开放科学数据平台的有机结合,弥补开放科学数据平台现有理论的不足,为开放科学背景下的行业实践提供参考。
英文摘要:
      This paper aims to build an open science data platform for digital intelligence empowerment, in order to address the existing problems of insufficient identification and analysis of scientific subject needs, difficulties in realizing the value of scientific resources, outdated application of digital intelligence technology, and vague guidance of standard specifications. This will dynamically meet the intelligent needs of scientific subjects, fully unleash the potential value of scientific resources, deeply integrate digital intelligence technology systems, and innovate scientific resource management standard specifications. This paper analyzes the existing problems of open science data platforms, clarifies the value of building open science data platforms for digital intelligence empowerment, and constructs a platform architecture consisting of intelligent service layer, intelligent business layer, resource storage layer, standard specification layer, and infrastructure layer. Finally, the platform operation process is discussed from the dimensions of management service and scientific service. This paper aims to achieve an organic combination of digital intelligence empowerment and open science data platforms, filling the gaps in existing theories of open science data platforms and providing references for industry practice in the context of open science.
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