数据与计算发展前沿 ›› 2025, Vol. 7 ›› Issue (1): 86-98.

CSTR: 32002.14.jfdc.CN10-1649/TP.2025.01.006

doi: 10.11871/jfdc.issn.2096-742X.2025.01.006

• 技术与应用 • 上一篇    下一篇

临近空间科学数据管理与共享服务机制研究与实现

米琳(),李晓辉,朱家佳,窦帅   

  1. 中国科学院空天信息创新研究院，北京 100094
  • 收稿日期:2024-08-28 出版日期:2025-02-20 发布日期:2025-02-21
  • 通讯作者: *米琳（E-mail: milin@aircas.ac.cn）
  • 作者简介:米琳，中国科学院空天信息创新研究院，助理研究员，长期从事空间科学数据管理与共享方面的研究，作为技术负责人设计了国内首个临近空间科学数据管理与共享服务平台
    本文中负责论文撰写、临近空间科学数据元模型设计以及临近空间科学数据管理与共享服务平台设计。
    MI Lin, as an assistant researcher at the Aerospace Information Innovation Research Institute of the Chinese Academy of Sciences, has long been engaged in the research of space science data management and sharing. As the technical director, she designed the first domestic near-space scientific data management and sharing service platform.
    In this paper, she is responsible for writing papers, designing meta models for near-space scientific data, and designing the platform for near-space scientific data management and sharing services.
    E-mail: milin@aircas.ac.cn
  • 基金资助:
    国家重点研发计划(2022YFB3903000);国家重点研发计划(2022YFB3903002)

Research and Implementation on the Mechanism of Near-Space Scientific Data Management and Sharing Service

MI Lin(),LI Xiaohui,ZHU Jiajia,DOU Shuai   

  1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
  • Received:2024-08-28 Online:2025-02-20 Published:2025-02-21

RichHTML

4

PDF

61

摘要：

【背景】伴随临近空间探测的持续实施，临近空间科学数据增长迅速，覆盖多专业学科领域，涉及多维度参量要素。【目的】临近空间科学数据结构的异质性、来源的多样性、类型的丰富性，给数据汇交存储、管理和共享的技术、机制、流程和方法带来了新的挑战。【方法】结合临近空间科学数据类型繁杂、来源多样、涉及学科领域和载荷参量要素多样化等特点，分析数据汇交管理与共享服务需求，设计面向临近空间科学数据的核心元数据总体结构和详细内容，探索涵盖数据汇交与接收流程、数据分级与用户分类、数据质量控制与知识产权保护等内容的数据管理与共享服务机制。【结果】以此为基础，研制国内首个面向临近空间科学数据的管理与共享服务平台，搭建了集访问控制、查询检索、共享分发、统计分析为一体的高性能时空数据共享服务框架。【结论】通过实践应用，数据管理与共享服务平台已汇交数据集567个，数据总量超过136TB，有效支撑了临近空间环境探测的持续实施。

关键词: 临近空间科学数据, 核心元数据, 数据汇交, 访问控制, 数据共享

Abstract:

[Context] With the continuous implementation of near-space exploration, near-space scientific data is growing rapidly, covering multiple disciplines and involving various multidimensional parameters. [Objective] The heterogeneity of data structures, diversity of data sources, and richness of data types pose new challenges to the technologies, mechanisms, processes, and methods used in data integration, storage, management, and sharing. [Methods] Given the characteristics of near-space scientific data, such as complicated types, diverse sources, multiple disciplines, and multiple parameters, a core metadata model of near-space scientific data is designed to meet the needs of data collection, data management, and data sharing services. The mechanism of near-space scientific data management and sharing service is explored, including data collection and receiving, data classification, and data quality control. [Results] The first domestic platform of near-space scientific data management and sharing service is developed based on the mechanism of near-space scientific data management and sharing service, and a high-performance spatio-temporal data sharing service framework integrating access control, query and retrieval, sharing and distribution, and statistical analyses is designed. [Conclusions] The platform, which has collected 567 datasets with a total data volume of over 136 TB through practical application, provides effective support for the follow-up exploration of near-space.

Key words: near-space scientific data, core metadata, data collection, access control, data sharing