农业图书情报学报 ›› 2024, Vol. 36 ›› Issue (5): 43-51.doi: 10.13998/j.cnki.issn1002-1248.24-0381

• 研究论文 • 上一篇    下一篇

以数据要素增值为导向的数字乡村建运一体模式

周志安, 王杰伟*   

  1. 北京国信钧元科技有限公司,北京 100007
  • 收稿日期:2024-04-05 发布日期:2024-09-24
  • 通讯作者: *王杰伟(1987- ),男,工程师,研究方向为人工智能、数据要素。Email:wangjiewei@gxjydata.com
  • 作者简介:周志安(1989- ),男,工程师,研究方向为数字乡村、数据要素

Integrated Model of Digital Construction and Operation of Rural Areas Guided by Value-added Data Elements

ZHOU Zhian, WANG Jiewei*   

  1. Beijing Guoxin Junyuan Technology Co., LTD, Beijing 100007
  • Received:2024-04-05 Published:2024-09-24

摘要: [目的/意义]为贯彻国家数据要素、数字乡村、现代农业发展战略,研究探讨“数据要素×”现代农业创新发展路径,总结提炼数据要素赋能农业产业高质量发展的新经验、新模式,以新质生产力助力传统产业突破发展瓶颈。[方法/过程]在梳理近年来数据要素、数字乡村、涉农数据资源政策体系及融合发展趋势基础上,采用政策研究、对比分析、模型分析、案例探讨等方法,首次创新提出以数据要素增值为导向的数字乡村建运一体模式(DOD)。[结果/结论]通过分析DOD模式内涵与意义、运营与收益模型,并以阜南数字乡村项目、广西生猪数据授权运营项目为例,深度剖析DOD模式在数字乡村数据资产专项债、农业产业数据授权运营方面的实践应用,最后基于案例实践与面临问题,针对性提出工作建议,为各地政府灵活运用DOD模式,探索实践以数据要素价值助力数字乡村建设、开展涉农公共数据授权运营提供参考,以数据要素赋能农业产业创新发展。

关键词: 数据要素, 数字乡村, 现代农业, 数据资产专项债, 建运一体

Abstract: [Purpose/Significance] At present, we are in a strategic development period of integrated development of digital rural areas and data elements. The government has introduced a series of policies to promote the deep integration and development of digital technology and rural areas, and promote the release of data value. The continuous improvement of rural digital capabilities and data resource systems, as well as the continuous improvement of data element policy system and the value transformation paths, provide unlimited opportunities for unlocking the value of agricultural data. The purpose of this study is to further study and explore the model of enabling "data elements X" in modern agricultural innovation, summarize and extract the model of empowering high-quality development of the agricultural industry with data elements, and explore the vertical application of data elements in the agricultural field, which is of great significance for breaking through the bottleneck of agricultural industry development with the help of data elements. [Method/Process] The research method of this article is based on the review of data elements, digital rural areas, agricultural data resource policy system, and integrated development trends released by the country in recent years. It has used policy analysis, comparative analysis, model analysis, case study and other research methods. The theoretical basis mainly comes from government official policy documents, and the comparative analysis and model analysis mainly rely on industry experience in practical work. The case study mainly takes the Funan Digital Rural Project and Guangxi Pig Data Authorization Operation Project as examples to deeply analyze the practical application of the DOD mode in the special debt of digital rural data assets and agricultural industry data authorization operation, and conducts in-depth analysis and discussion based on the current situation of the industry. This study combines theory and practice. [Results/Conclusions] First, an innovative digital rural construction and operation integration model (DOD) guided by value-added elements is proposed. The connotation and significance of this model are analyzed, and a model for the operation and benefits of this model is further proposed. Two representative cases are used to deeply analyze the practical application of the DOD model. Finally, based on the case practice and the problems faced, targeted work suggestions are proposed to provide reference for local governments to flexibly use the DOD model, explore the use of value-added data elements to support digital rural construction, and empower agricultural industry development.

Key words: data element, digital village, modern agriculture, special bond for data assets, integrated construction and operation

中图分类号:  F49;F323

引用本文

周志安, 王杰伟. 以数据要素增值为导向的数字乡村建运一体模式[J]. 农业图书情报学报, 2024, 36(5): 43-51.

ZHOU Zhian, WANG Jiewei. Integrated Model of Digital Construction and Operation of Rural Areas Guided by Value-added Data Elements[J]. Journal of Library and Information Science in Agriculture, 2024, 36(5): 43-51.