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首页 > 过刊浏览>2023年第34卷第3期 >1396-1424. DOI:10.13328/j.cnki.jos.006751
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数据定价与交易研究综述
作者:
作者简介:

江东(1996-),男,博士生,主要研究领域为大图数据分析,数据定价;袁野(1981-),男,博士,教授,博士生导师,CCF高级会员,主要研究领域为大数据管理,数据库理论与系统;张小伟(1996-),男,硕士生,主要研究领域为数据定价;王国仁(1966-),男,博士,教授,博士生导师,CCF杰出会员,主要研究领域为不确定数据管理,数据密集型计算,可视媒体数据管理与分析,非结构化数据管理,分布式查询处理与优化技术,生物信息学.

通讯作者:

袁野，yuanye@mail.neu.edu.cn

基金项目:

国家自然科学基金（61932004，61732003，62072087，U2001211）；中央高校基本科研基金（N181605012）


Survey on Data Pricing and Trading Research
Author:
  • 摘要
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    摘要:

    在大数据时代，随着信息技术的发展，各行各业都在收集海量数据.数据是数字经济的基础，蕴含有巨大价值.但是由于缺乏高效可行的共享机制，数据拥有方彼此之间缺乏沟通，形成了一个个数据孤岛.这不利于大数据产业的健康发展.因此，给数据分配一个合适的价格，设计高效的数据交易市场平台成为消除数据孤岛、使数据充分流动的重要途径.系统梳理进行数据定价与交易时涉及的技术性问题.具体来说，介绍数据定价与交易的难点和相关准则；将大数据在市场中的生命周期分为数据收集与集成、数据管理与分析、数据定价和数据交易4个环节；在大数据管理研究的基础上介绍适用于前两个环节的相关方法；然后对数据定价思路和方法进行分类，分析各类方法的适用场景以及优势和短板；介绍数据市场的分类，以博弈论和拍卖为例研究了数据交易中市场类型和参与人行为对交易过程及价格的影响.最后，对数据定价与交易的未来研究方向进行展望.

    Abstract:

    In the big data era, an enormous amount of data is collected in every industry with the development of information technology. Data is the foundation of the digital economy, containing great value. However, for the lack of efficient and feasible data-sharing mechanisms, data owners seldom communicate with each other, which leads to the formation of data islands and is unfavorable to the healthy development of the big data industry. Hence, allocating a proper price to data and designing an efficient data market platform have become important ways to eliminate data islands and secure sufficient data flow. This study systematically sorts out the technical issues regarding data pricing and trading. Specifically, the difficulties and related principles of data pricing and trading are introduced. The life cycle of data in the data market is divided into four stages: data collection and integration, data management and analysis, data pricing, and data trading. Upon the research on big data management, related methods applicable to the first two stages are elaborated. After that, data pricing methods are categorized, and usage scenarios, advantages, and shortcomings of these methods are analyzed. Moreover, the classification of data markets is introduced, and the impact of market types and participants’ behavior in data trading on the trading process and prices is studied with game theory and auctions as examples. Finally, future research directions of data pricing and trading are discussed.

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江东,袁野,张小伟,王国仁.数据定价与交易研究综述.软件学报,2023,34(3):1396-1424

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