A Survey on Data Pricing: from Economics to Data Science
This is an incremental work that synthesizes existing knowledge on data pricing for researchers and practitioners, offering a comprehensive overview without novel findings.
The paper provides a unified, interdisciplinary survey on data pricing, examining motivations, economic principles, and pricing models across fields like economics and machine learning, without presenting new experimental results.
Data are invaluable. How can we assess the value of data objectively, systematically and quantitatively? Pricing data, or information goods in general, has been studied and practiced in dispersed areas and principles, such as economics, marketing, electronic commerce, data management, data mining and machine learning. In this article, we present a unified, interdisciplinary and comprehensive overview of this important direction. We examine various motivations behind data pricing, understand the economics of data pricing and review the development and evolution of pricing models according to a series of fundamental principles. We discuss both digital products and data products. We also consider a series of challenges and directions for future work.