数据交易模式对比与交易难点分析

doi:10.11896/jsjkx.250900002

摘要/Abstract

摘要： 在数字化加速的趋势下,数据要素成为各行业的核心资源,推动了市场的不断发展。然而,目前的数据交易市场发展并不完善,其原因主要有两点:一是个人用户的行为数据交易门槛过高;二是企业间数据交易的合规审查机制不健全,数据交易规则尚未完善,市场活力受到制约。数据交易困难的根本原因在于数据本身区别于传统意义上“一手交钱一手交货”的商品,存在定价难、确权难、质量保证难、交易非否认难和保障数据主权难的问题。对此,搜集整理了现有较为完善的数据交易框架,从交易模式的视角对现有框架进行分类对比;针对上述5个难点,详细介绍了现有文献的解决方案;针对现有数据交易市场的发展情况,提出了对未来发展的建议。

关键词: 数据交易难点, 数据确权, 数据定价, 数据主权, 数据质量保证, 数据交易非否认

Abstract: With the acceleration of digitalization,data have become a core resource across industries,driving continuous market growth.However,the current data trading market remains underdeveloped,mainly due to two reasons.Firstly,the high barriers for individuals to trade behavioral data.Secondly,the lack of sound compliance review mechanisms for inter-enterprise data tran-sactions,with incomplete trading rules that restrict market vitality.The fundamental difficulties in data trading lie in the unique characteristics of data,which differ from traditional “cash-and-carry” goods,leading to challenges in pricing,data rights confirmation,data quality assurance,non-repudiation of transactions,and the safeguarding of data sovereignty.This paper collects and organizes relatively mature data trading frameworks,classifies and compares them from the perspective of trading models,and provides a detailed introduction to the solutions proposed in the literature for the five major challenges mentioned above.Finally,in light of the current development of the data trading market,this study puts forward suggestions for future development.

Key words: Challenges in data trading, Data rights confirmation, Data pricing, Data sovereignty, Data quality assurance, Non-repudiation in data trading

中图分类号:

TP399

崔金甲, 曾琛, 王璐, 彭晓晖. 数据交易模式对比与交易难点分析[J]. 计算机科学, 2026, 53(4): 121-133. https://doi.org/10.11896/jsjkx.250900002

CUI Jinjia, ZENG Chen, WANG Lu, PENG Xiaohui. Analysis of Data Trading Models and Transaction Challenges[J]. Computer Science, 2026, 53(4): 121-133. https://doi.org/10.11896/jsjkx.250900002

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