A data marketplace is an online venue that brings data owners, data brokers, and data consumers together and facilitates commoditisation of data amongst them. Data pricing, as a key function of a data marketplace, demands quantifying the monetary value of data. A considerable number of studies on data pricing can be found in literature. This paper attempts to comprehensively review the state-of-the-art on existing data pricing studies to provide a general understanding of this emerging research area. Our key contribution lies in a new taxonomy of data pricing studies that unifies different attributes determining data prices. The basis of our framework categorises these studies by the kind of market structure, be it sell-side, buy-side, or two-sided. Then in a sell-side market, the studies are further divided by query type, which defines the way a data consumer accesses data, while in a buy-side market, the studies are divided according to privacy notion, which defines the way to quantify privacy of data owners. In a two-sided market, both privacy notion and query type are used as criteria. We systematically examine the studies falling into each category in our taxonomy. Lastly, we discuss gaps within the existing research and define future research directions.
翻译:数据市场是一个在线场所,将数据拥有者、数据经纪人和数据消费者汇集在一起,并促进数据相互交流。数据定价作为数据市场的一个关键功能,要求量化数据的货币价值。关于数据定价的大量研究可以在文献中找到。本文件试图全面审查现有数据定价研究的最新工艺,以提供对这一新兴研究领域的普遍理解。我们的主要贡献在于数据定价研究的新分类,这种分类将数据价格的不同属性统一起来,从而决定数据价格。我们框架的基础按市场结构分类这些研究,是销售、购买或双向的。然后在销售市场中,这些研究进一步分为查询类型,其中界定数据消费者获取数据的方式,而在购买市场中,这些研究按照隐私概念进行划分,其中界定了数据所有人隐私的量化方式。在双面市场中,隐私概念和查询类型都被用作标准。我们系统地研究进入我们分类中每个类别的研究,我们界定了现有研究方向。最后,我们讨论了现有研究方向。</s>