  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.
