A Survey on Data Pricing: Methods, Challenges, and Prospects

Abstract

As organizations increasingly rely on data-driven decision-making, understanding the true value and potential of data becomes crucial. Data pricing, which aims to determine the financial value of information, plays a pivotal role in data circulation and transactions. However, the existing surveys on data pricing have limitations that need to be addressed. This paper presents a comprehensive survey of big data pricing methods from a data science perspective. It begins by providing an overview of the fundamental concepts underlying data pricing and the data market. Subsequently, it delves into the general principles and challenges associated with data pricing. The survey categorizes and summarizes various approaches and methods employed in data pricing, assessing their respective advantages and disadvantages. In conclusion, this paper identifies potential research directions to enhance our understanding of data pricing. By rectifying the deficiencies in existing surveys, this comprehensive study aims to contribute to the development of effective data pricing strategies and foster advancements in the field of data science.