Modern Data Pricing Models: Taxonomy and Comprehensive Survey

TL;DR

This comprehensive survey classifies and analyzes modern data pricing models across three main strategies, providing insights and future directions to improve data trade and sharing.

Contribution

First to systematically classify and analyze thirteen data pricing models within three major strategies, offering new insights and research directions.

Findings

Classified data pricing models into three strategies and thirteen models.

Provided in-depth analysis and comparison among models.

Suggested future research directions and novel topics in data pricing.

Abstract

Data play an increasingly important role in smart data analytics, which facilitate many data-driven applications. The goal of various data markets aims to alleviate the issue of isolated data islands, so as to benefit data circulation. The problem of data pricing is indispensable yet challenging in data trade. In this paper, we conduct a comprehensive survey on the modern data pricing solutions. We divide the data pricing solutions into three major strategies and thirteen models, including query pricing strategy, feature-based data pricing strategy, and pricing strategy in machine learning. It is so far the first attempt to classify so many existing data pricing models. Moreover, we not only elaborate the thirteen specific pricing models within each pricing strategy, but also make in-depth analyses among these models. We also conclude five research directions for the data pricing field, and put forward some novel and interesting data pricing topics. This paper aims at gaining better insights, and directing the future research towards practical and sophisticated pricing mechanisms for better data trade and share.