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Smart Agriculture ›› 2026, Vol. 8 ›› Issue (3): 270-283.doi: 10.12133/j.smartag.SA202603023

• 专刊--数字技术赋能与农业经济范式转型 • 上一篇    

智慧农业背景下农业经营者数据权益保护困境与制度因应

万志前1(), 刘玉珍2   

  1. 1. 华中农业大学文法学院,湖北 武汉 430070,中国
    2. 华中农业大学农业农村法治创新研究中心,湖北 武汉 430070,中国
  • 收稿日期:2026-03-21 出版日期:2026-05-30
  • 基金项目:
    国家社会科学基金项目(23BFX078)
  • 通信作者:
    万志前,博士,教授,研究方向为农业法。E-mail:

The Protection Dilemma and Institutional Responses of Agricultural Operators' Data Rights and Interests in the Context of Smart Agriculture

WAN Zhiqian1(), LIU Yuzhen2   

  1. 1. College of Humanities Social Sciences, Huazhong Agricultural University, Wuhan 430070, China
    2. Innovation Research Center for Agricultural and Rural Rule of Law, Huazhong Agricultural University, Wuhan 430070, China
  • Received:2026-03-21 Online:2026-05-30
  • Foundation items:The National Social Science Fund of China(23BFX078)
  • Corresponding author:
    WAN Zhiqian, E-mail:

摘要:

【目的/意义】 智慧农业是现代农业发展的重要着力点和农业强国建设的战略制高点,数据为其发展基础,农业经营者作为数据来源者之一,其数据权益保护亟待解决,以促进智慧农业高质量发展。 【方法】 采用规范、案例、比较等分析方法,从理论上揭示农业经营者数据权益的性质与内涵,剖析权益保护的现实困境,并基于理论与现实的差距,提出农业经营者数据权益保护制度因应。 【结果和讨论】 农业经营者数据权益是一种基于数据来源贡献而形成的,受民法保护但未上升为权利的财产性权益,权益的客体为非个人农业数据;请求权基础缺失、意思自治失衡、技术控制或局限、权益救济困难等导致农业经营者数据权益难以实现。 【结论】 应以权利束理论构建包括知情、访问与控制、可携带、收益在内的农业经营者非排他性数据权益;由相关部门制定农业数据标准合同示范文本,防止格式条款单方拟定所导致的不公;从农业数据互操作性、分级分类、合规认证等方面完善农业数据治理规范;结合农业经营者数据特殊性,探索数据信托集体治理模式。

关键词: 智慧农业, 农业数据, 数据权益, 数据来源者, 数据治理, 数据资产

Abstract:

[Objective] Agricultural operators are the initial origin and key contributors to smart agriculture data, and the protection of their data rights and interests urgently needs to be addressed. China's smart agriculture is currently developing rapidly, and the digitalization level of agricultural production continues to rise. However, agricultural operators' data rights and interests have not received sufficient attention. What rights and interests they should enjoy and how these can be realized have become pressing practical issues. The aim of this research is to reveal the nature and connotation of agricultural operators' data rights and interests, analyze the dilemmas in rights protection, and propose institutional responses, and form a virtuous cycle of "data generation-value creation-rights feedback", thereby promoting the healthy and sustainable development of smart agriculture. [Methods] Literature review, normative analysis, case analysis and comparative analysis were adopted. The literature review was conducted to examine existing research progress and to identify the research questions. Through normative analysis and systematic interpretation of the data rights rules in China's existing legal norms and relevant policy documents, the nature of rights and interests of agricultural operators' non-personal agricultural data was defined. Representative institutional norms of foreign agricultural data governance were compared to distill referable experience for the protection of agricultural data rights and interests. Typical cases were used to concretely illustrate the practical dilemmas in protecting agricultural operators' data rights and interests in the development of smart agriculture. [Results and Discussions] The results demonstrated that agricultural operators' data rights and interests constituted a legal interest arising from their contribution as a data source, protected by civil law but not elevated to a right. The subjects of rights and interests included rural contract-management households, family farms, specialized farmer cooperatives, agricultural enterprises, etc. The object was non-personal agricultural data within agricultural data. Based on the theories of fruits of rights and "digital labor", agricultural operators held property-type rights and interests in their non-personal data. It further revealed that in practice, the protection of agricultural operators' data rights and interests faced fourfold dilemmas. First, the lack of a basis for claims: Existing laws do not provide protection for non-personal agricultural data. Second, the imbalanced autonomy of will: Contract terms were unilaterally drafted by data processors, leaving agricultural operators with limited bargaining power and substantive choice. Third, the technological control or constraints: Data processors locked in data through technical means, while the absence of technical standards for agricultural data interoperability made data portability unattainable. Fourth, the difficulties in rights and interests relief: The highly concealed technical nature of data processing made it hard for agricultural operators to trace data flows and to prove damages and causation, coupled with the generally low digital literacy of agricultural operators and their fragmented strength, which made it challenging for them to enforce their rights. [Conclusions] A multi-layered institutional framework encompassing "rights confirmation - contractual checks and balances - data governance - mechanism innovation" should be established to safeguard agricultural operators' data rights and interests. At the legal level, the content of agricultural operators' data property interests should be clearly defined, and non-exclusive data interests including the right to know, to access and control, to portability, and to benefit should be constructed based on the bundle-of-rights theory. At the contractual level, relevant authorities should formulate model texts for standard agricultural data contracts to rectify the substantive inequality between agricultural operators and data controllers. In terms of data governance, technical rules and legal norms should be integrated by unifying data technical standards, refining data classification and grading, and establishing compliance certification systems. In the dimension of mechanism innovation, considering the particularities of agricultural operators' data, the introduction of a collective governance model through data trusts should be explored, relying on specialized operation and collective management to ensure the effective realization of data rights and interests.

Key words: smart agriculture, agricultural data, data rights and interests, data providers, data governance, data asset

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