信息资源管理学报 ›› 2025, Vol. 15 ›› Issue (6): 52-66.doi: 10.13365/j.jirm.2025.06.052

• 研究论文 • 上一篇    下一篇

数据要素市场中高质量数据集评价指标体系建设研究

林镇阳1,2,3 　吴江2,4　胡鑫5　王璇6,7　袁一鸣4　杜乐2,3   

  1. 1.清华大学计算机技术与科学系，北京，100084；　
    2.武汉数据智能研究院，武汉，430072；　
    3.南京信息工程大学大数据法治研究院，南京，210044；　
    4.武汉大学信息管理学院，武汉，430072；　
    5.中国社会科学院大学国际政治经济学院，北京，102401；　
    6.国家信息中心大数据发展部，北京，100045；　
    7.中国信息协会，北京，100045
  • 出版日期:2025-11-26 发布日期:2026-01-06
  • 作者简介:林镇阳，博士，高级工程师，研究方向为数字经济与技术创新；吴江，博士，教授，研究方向为数据智能与科技赋能；胡鑫（通讯作者），硕士，研究方向为数字经济与数据要素价值化，Email：hh11690@163.com；王璇，博士，副研究员，研究方向为大数据分析、数据要素基础制度；袁一鸣，博士研究生，研究方向为信息管理、数据要素；杜乐，硕士，高级工程师，研究方向为数据法学、数据要素市场。
  • 基金资助:
    本文系国家自然科学基金专项项目“数据交易场所的功能定位、运营机制与治理机制研究”（72442030），国家社会科学基金“马克思主义政治经济学视阈下数据要素的确权、流通和收益分配研究”(23BKS031)和湖北省数据局2024年研究课题项目“湖北省高质量数据集建设研究”(IM2409E085N1)的研究成果之一。

Construction of an Evaluation Indicator System for High-Quality Datasets in the Data Element Market

Lin Zhenyang1,2,3 　Wu Jiang2,4　Hu Xin5　Wang Jingxuan6,7　Yuan Yiming4　Du Le2,3   

  1. 1.Department of Computer Technology and Science, Tsinghua University, Beijing, 100084；　
    2.Wuhan Institute of Data Intelligence, Wuhan, 430072；　
    3.Institute of Big Data Rule of Law, Nanjing University of Information Science and Technology,Nanjing,210044;　
    4.School of Information Management, Wuhan University, Wuhan,430072;　
    5.School of International Political Economy, University of Chinese Academy of Social Sciences, Beijing, 102401;　
    6.Big Data Development Department, State Information Center, Beijing,100045;　
    7.China Information Association, Beijing,100045
  • Online:2025-11-26 Published:2026-01-06
  • About author:Lin Zhenyang, Ph.D., senior engineer, research interests including digital economy and technological innovation; Wu Jiang, Ph.D., professor, research interests including data intelligence and technology empowerment; Hu Xin (corresponding author), master, research interests including digital economy and value realization of data elements, Email: hh11690@163.com; Wang Jingxuan, Ph.D., associate researcher, research interests including big data analysis and fundamental institutions of data elements; Yuan Yiming, Ph.D. candidate, research interests including information management and data elements; Du Le, master, senior engineer, research interests including data law and data elements market.
  • Supported by:
    This work is supported by the Special Project of the National Natural Science Foundation of China "Functional Orientation, Operational Mechanism, and Governance Mechanism of Data Trading Venues" (72442030), the National Social Science Foundation of China Project "Research on the Ownership Confirmation, Circulation, and Income Distribution of Data Elements from the Perspective of Marxist Political Economy" (23BKS031), and the 2024 Research Project of the Hubei Provincial Data Bureau "Construction of High-Quality Datasets in Hubei Province" (IM2409E085N1).

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摘要： 构建科学的数据质量评价指标体系是推动数据要素市场化配置的关键基础，为数据资源向资产化、资本化转型提供量化评价基准，进而促进数据要素市场价值循环机制的建立。本研究基于扎根理论，系统分析政策文本、技术标准以及行业专家访谈资料，构建包含合规属性、规模属性、内容属性、价值属性4个主维度、12项一级指标及32项二级指标的多层次评价指标体系，并结合层次分析法和专家咨询法确定指标权重，形成具有可操作性的综合评价模型；通过湖北省高质量数据集遴选工作的实证检验，验证了模型的有效性和实践适用性。研究结果可为数据资产定价、流通效能提升与价值转化路径优化提供理论依据和实践参考。

关键词: 高质量数据集, 扎根理论, 评价指标体系, 数据要素, 数据流通交易

Abstract: This study aims to construct a scientific data quality evaluation indicator system as a fundamental basis for promoting the market-oriented allocation of data elements. It provides a quantitative benchmark for the transformation of data resources into assets and capital, thereby supporting the development of a value circulation mechanism in the data element market. Based on grounded theory, this study systematically analyzes policy documents, technical standards, and expert interview materials to build a multi-level evaluation indicator system comprising four main dimensions—compliance characteristics, scale-related attributes, content-specific properties, and value-oriented features—with 12 first-level indicators and 32 second-level indicators. This study further adopts the Analytic Hierarchy Process (AHP) and expert consultation methods to determine indicator weights and develop a practical, operable comprehensive evaluation model. Empirical validation through the selection of high-quality datasets in Hubei Province demonstrates the model’s effectiveness and practical applicability. The findings provide theoretical support and practical references for data asset valuation, improving data circulation efficiency, and optimizing value transformation pathways.

Key words: High-quality datasets, Grounded theory, Evaluation indicator system, Data elements, Data circulation and transaction

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