| 王翠萍 宋雯琪 姜鑫妍.我国科学数据共享平台建设及服务内容研究[J].中国科技资源导刊,2023,(3):9~18,67 |
| 我国科学数据共享平台建设及服务内容研究 |
| Research on the Construction and Service Content of Scientific Data Sharing Platform in China |
| 投稿时间：2022-10-25 |
| DOI： |
| 中文关键词: 科学数据;科学数据共享平台;科学数据中心;数据服务;平台建设 |
| 英文关键词: scientific data, scientific data sharing platform, scientific data center, data service,platform construction |
| 基金项目: |
| 作者 | 单位 | | 王翠萍 宋雯琪 姜鑫妍 | (东北师范大学信息科学与技术学院，吉林长春 130117) |
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| 摘要点击次数: 319 |
| 全文下载次数: 721 |
| 中文摘要: |
| 为了解我国科学数据共享平台建设现状及服务内容，探索各科学数据共享平台间服务方式的差异，对比各 平台建设中存在的问题。利用科学数据共享平台官方网站，从建设背景、组织规范、服务内容和服务能力调查分析我 国 14 个典型的科学数据共享平台的总体情况。研究发现，我国科学数据共享平台重视数据汇交服务，数据汇交流程较 为完善，平台数据影响力不断提升，数据共享服务内容较为丰富，但仍存在平台组织规范缺少绩效评价内容、数据与 科技成果间关联性不足以及数据利用和共建共享程度不足的问题。因此，建议科学数据共享平台需进一步完善元数据 标准、数据分类标准，形成统一的引用标准，提供统一的集成检索服务，并注重与其他平台间的关联建设，提高科学 数据的共享利用水平。 |
| 英文摘要: |
| In order to understand the current situation and service content of scientific data sharing platform construction in China, explore the differences of service modes among various scientific data sharing platforms, and compare the problems in the construction of various platforms. This paper analyzes the overall situation of 14 typical scientific data sharing platforms in China through visiting the official website of the scientific data sharing platforms and investigating the construction background, organizational standards, service content and service capacity. It is found that the scientific data sharing platform attaches importance to data collection and exchange services, the data collection and exchange process is relatively complete, the platform's data influence continues to increase, and the content of data sharing services is relatively rich. However, there are problems such as the lack of performance evaluation content in the platform organization specification, the insufficient correlation between data and scientific and technological achievements and lack of data utilization, co-construction and sharing. Therefore, the scientific data sharing platform needs to further improve metadata standards and data classification standards, form a unified reference standard, provide a unified integrated search service and pay attention to the association construction with other platforms to improve the sharing and utilization level of scientific data. |
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