数据与计算发展前沿 ›› 2026, Vol. 8 ›› Issue (4): 1-18.

CSTR: 32002.14.jfdc.CN10-1649/TP.2026.04.001

doi: 10.11871/jfdc.issn.2096-742X.2026.04.001

• • 上一篇    下一篇

面向AI4S的天文数智化服务体系构建与实践——以国家天文科学数据中心为例

崔辰州1,2,*(),许允飞1,2,樊东卫1,2,李长华1,2,李珊珊1,2,米琳莹1,2,甘庆波1,2,赵公博1,2,China-VO团队   

  1. 1 中国科学院国家天文台北京 100101
    2 国家天文科学数据中心北京 100101
  • 收稿日期:2026-02-05 出版日期:2026-08-20 发布日期:2026-08-21
  • 通讯作者: 崔辰州(E-mail:ccz@nao.cas.cn
  • 作者简介:崔辰州,中国科学院国家天文台,研究员,国家天文科学数据中心,常务副主任,主要研究领域为天文信息学、虚拟天文台、人工智能驱动的科学研究。
    本文承担的工作为整体研究框架及论文撰写。
    CUI Chenzhou is a professor at the National Astronomical Observatories, Chinese Academy of Sciences, and executive deputy director of the National Astronomical Data Center. His main research areas include astroinformatics, virtual observatory, and AI for Science.
    In this paper, he is mainly responsible for overall research framework and manuscript writing.
    E-mail: ccz@nao.cas.cn
  • 基金资助:
    国家重点研发计划(2022YFF0711500);国家自然科学基金(12573111);国家自然科学基金(12403102);国家自然科学基金(12373110);国家自然科学基金(12273077);国家自然科学基金(12103070);中国科学院战略性先导科技专项(XDB0550101)

Building an AI4S-Oriented Intelligent Data Service System for Astronomy: Practices from the National Astronomical Data Center

CUI Chenzhou1,2,*(),XU Yunfei1,2,FAN Dongwei1,2,LI Changhua1,2,LI Shanshan1,2,MI Linying1,2,GAN Qingbo1,2,ZHAO Gongbo1,2,China-VO Collaboration   

  1. 1 National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China
    2 National Astronomical Data Center, Beijing 100101, China
  • Received:2026-02-05 Online:2026-08-20 Published:2026-08-21

摘要:

【目的】 天文学已全面步入数据密集型科学发现时代,而人工智能驱动的科学研究(AI4S)范式的兴起,对作为国家战略科技力量组成部分的科学数据中心提出了前所未有的能力提升需求。国家天文科学数据中心(NADC)面对海量异构数据的治理压力、传统数据服务模式的效率瓶颈以及支撑前沿AI4S创新的使命,系统性地规划构建了以“数智化”为核心特征的下一代天文数据服务体系。【方法】 首先完整阐述该体系“三位一体”的总体设计:以应用程序接口(API)和模型上下文协议(MCP)为双核构建标准化与智能化兼备的“数据服务层”;以深度集成数据、软件、算力、模型资源的云端科研平台为承载,打造一站式“科研支撑层”;通过深度嵌入重大科学工程、革新科教融合模式、开展学科和人才建设、拓展公众科学及深化国际合作,培育开放协同的“应用生态层”。【结果】 剖析该体系在LAMOST天体光谱数据库、AI智能体驱动的天关卫星时域天文发现及公众科学项目中的成功实践,展示其在提升数据智能化供给、降低前沿技术使用门槛、赋能天文学发现等方面的显著成效。【结论】 NADC的探索为大数据与人工智能时代国家科学数据中心的功能重塑、能力建设与服务模式创新提供了具有示范意义的系统性解决方案。

关键词: 国家天文科学数据中心(NADC), 数据密集型科学, 人工智能驱动的科学研究(AI4S), 虚拟天文台(VO), 数智化服务, 开放科学, 模型上下文协议(MCP), 智能体

Abstract:

[Objective] Astronomy has fully entered the era of data-intensive scientific discovery. Meanwhile, the rapid emergence of the artificial intelligence-driven scientific research paradigm, namely AI for Science (AI4S), has imposed unprecedented requirements for enhancing the capability of scientific data centers as integral components of national strategic scientific and technological forces. Confronted with the challenges of governing massive and heterogeneous datasets, the efficiency bottlenecks of traditional data service models, and the mission of supporting cutting-edge AI4S innovation, the National Astronomical Data Center (NADC) has systematically planned and implemented a next-generation astronomical data service system characterized by “Digital-Intelligent Integration”. [Methods] This paper first presents a comprehensive description of the system's “trinity” overall architecture. A standardized and intelligent data service layer is established with application programming interfaces (APIs) and the Model Context Protocol (MCP) as dual cores. A one-stop research support layer is built upon the cloud-based scientific research platform, the China-VO Science Platform, which deeply integrates data, software, computing resources, and models. An open and collaborative application ecosystem layer is cultivated through deep engagement with major scientific projects, innovation in science-education integration models, disciplinary and talent development, expansion of citizen science initiatives, and strengthened international collaboration. [Results] The paper focuses on in-depth analyses of successful practices within this system, including standardized and intelligent services for the LAMOST astronomical spectral database, AI agent-driven time-domain astronomical discovery with EP satellites, and citizen science programs. These cases demonstrate the system's significant effectiveness in enhancing intelligent data provision, lowering the barriers to adopting advanced AI technologies, and empowering discoveries in time-domain astronomy. [Conclusions] The explorations of NADC provide a systematic and demonstrative solution for functional transformation, capacity building, and service model innovation of national scientific data centers in the era of big data and artificial intelligence.

Key words: National Astronomical Data Center (NADC), data-intensive scientific discovery, AI for Science (AI4S), Virtual Observatory (VO), intelligent data service, open science, Model Context Protocol (MCP), agent