情报科学 ›› 2025, Vol. 43 ›› Issue (8): 78-90.

• 理论研究 • 上一篇    下一篇

基于生成式人工智能的政府开放数据共享模型研究

  

  • 出版日期:2025-08-05 发布日期:2025-12-12

  • Online:2025-08-05 Published:2025-12-12

摘要: 【目的/意义】政府开放数据共享能够加快数据流动和知识扩散,深化政府治理体系与治理能力现代化。【方 法/过程】本研究基于问卷调查、专家打分法与系统架构设计理论,面向广东、内蒙古、北京等31个省、自治区、直辖 市,识别了1009位受访者针对政府开放数据共享的需求、痛点与期望,构建了政府开放数据共享模型。【结果/结论】 基于生成式人工智能的政府开放数据模型可以集数据访问、集成、筛选、下载、更新、易用、权限与安全模块于一体, 通过自然语言处理、多轮对话等能力更加高效、灵活地推动数据的标准化与协同性,解决数据分散、获取门槛较高、 访问效率偏低等现实难题。【创新/局限】融合模型与 OpenAPI规范所搭建的政府开放数据共享问答服务具备自主 管理和定期优化能力,在系统维护、更新以及成本控制方面相较ChatGPT-4.0更加灵活、可控。该服务能够直接与 政府原始数据集对接,提供精确、实时的政府数据查询,确保数据的可维护性和可追溯性。

Abstract: 【Purpose/significance】Government open data sharing can accelerate data flow and knowledge diffusion, and deepen the modernization of government governance system and governance capacity.【Method/process】Based on the questionnaire survey, ex⁃ pert scoring method and system architecture design theory, this study identifies the needs, pain points and expectations of 1009 respon⁃ dents for government open data sharing for 31 provinces, autonomous regions and municipalities directly under the central govern⁃ ment, such as Guangdong, Inner Mongolia, Beijing, etc., and constructs a government open data sharing model.【Result/conclusion】 The government open data model based on generative artificial intelligence can integrate data access, integration, screening, download⁃ ing, updating, ease of use, permission and security modules, and promote data standardization and synergy more efficiently and flexibly through the capabilities of natural language processing and multi-round dialogues, solving the realistic problems of data dispersion, high threshold of access, low access efficiency, and so on.【Innovation/limitation】The government open data sharing Q&A service built by integrating the model and OpenAPI specification has the ability of independent management and regular optimization, and is more flexible and controllable than ChatGPT-4.0 in terms of system maintenance, update and cost control. The service can directly in⁃ terface with the original government dataset to provide accurate and real-time government data query, ensuring the maintainability and traceability of the data.