| 冯娇1 刘勇2.甘肃省科学数据中心建设发展路径研究——基于国家经验的省域适配性探索[J].中国科技资源导刊,2026,(3):82~90,110 |
| 甘肃省科学数据中心建设发展路径研究——基于国家经验的省域适配性探索 |
| Research on the Construction and Development Path of Scientific Data Centers in Gansu Province— A Provincial Adaptation Based on National Experiences |
| 投稿时间：2026-04-15 |
| DOI： |
| 中文关键词: 科学数据中心;建设模式;数据价值链;省域实践 |
| 英文关键词: scientific data center, construction model, data value chain, provincial-level practice |
| 基金项目:甘肃省自然基金重点项目“基于大模型深度学习的科技评价科学数据人工智能生成与分析研究”(25JRRA764);甘肃 省软科学一般项目“基于情报视角的甘肃省科技安全风险监测预警指标体系研究”(26JRZA044)。 |
| 作者 | 单位 | | 冯娇1 刘勇2 | (1. 甘肃省科学技术情报研究所，甘肃 兰州 730000
2. 甘肃省科学技术厅，甘肃 兰州 730000) |
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| 摘要点击次数: 20 |
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| 中文摘要: |
| 针对省级科学数据中心建设普遍存在的定位模糊与效能不足问题，系统转化国家层面建设经验，为甘肃省及其他同类省域探索适配性的建设路径。综合运用案例比较与政策文本分析法，解构20个国家科学数据中心的建设逻辑，提炼共性特征;采用“经验适配”思路，紧密结合甘肃省的资源禀赋与战略需求，设计并论证本地化的路径。研究归纳出国家科学数据中心建设过程中“战略部署—资源建设—平台支撑—服务输出—保障体系”5个关键维度的协同关系，并据此为甘肃省提出聚焦生态安全与特色产业、健全汇交与标准体系、升级服务平台、完善评估机制的系统实施路径。研究结果为省域科学数据中心建设提供了可操作的转化框架与实践参考。 |
| 英文摘要: |
| Addressing the common problems of ambiguous positioning and insufficient effectiveness in the construction of provincial scientific data centers, this paper aims to systematically translate national-level construction experiences to explore an adaptive development path for Gansu Province and other similar provinces. By comprehensively employing case comparison and policy text analysis methods, the construction logic of 20 national scientific data centers is deconstructed to extract common characteristics. On this basis, an “experience adaptation” approach is adopted, closely integrating Gansu Province’s resource endowments and strategic needs, to conduct localized path design and demonstration. This paper summarizes the synergistic relationships among five key dimensions in the construction of national scientific data centers, namely “strategic deployment – resource construction – platform support – service output – guarantee system.” Accordingly, a systematic implementation path for Gansu Province is proposed, focusing on ecological security and characteristic industries, improving data submission and standard systems, upgrading service platforms, and perfecting evaluation mechanisms. This study provides an operational transformation framework and practical reference for the construction of provincial scientific data centers. |
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