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A Survey on Data Markets

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arxiv 2411.07267 v1 pith:Y6JJJX4W submitted 2024-11-09 cs.GT cs.AIcs.DB

classification cs.GTcs.AIcs.DB
keywords datamarketsdifferentimportantincludingmechanismpricingsurvey
verification ladder T0 review T1 audit T2 compute T3 formal
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Data is the new oil of the 21st century. The growing trend of trading data for greater welfare has led to the emergence of data markets. A data market is any mechanism whereby the exchange of data products including datasets and data derivatives takes place as a result of data buyers and data sellers being in contact with one another, either directly or through mediating agents. It serves as a coordinating mechanism by which several functions, including the pricing and the distribution of data as the most important ones, interact to make the value of data fully exploited and enhanced. In this article, we present a comprehensive survey of this important and emerging direction from the aspects of data search, data productization, data transaction, data pricing, revenue allocation as well as privacy, security, and trust issues. We also investigate the government policies and industry status of data markets across different countries and different domains. Finally, we identify the unresolved challenges and discuss possible future directions for the development of data markets.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Pricing Pandora's Boxes: Revenue Maximization in Sequential Information Acquisition

    cs.DS 2026-07 conditional novelty 7.0 of 10

    Uniform-index pricing—setting all Weitzman indices equal—is a 4-approximation to optimal revenue for selling information in Pandora's-box search, and is exactly optimal in several special cases.

  2. Benchmarking Robust Aggregation in Decentralized Gradient Marketplaces

    cs.LG 2025-09 conditional novelty 6.0 of 10

    Adaptive Sybil backdoor attacks can defeat MartFL, FLTrust, and SkyMask in buyer-baseline gradient marketplaces with little visible effect on accuracy or cost.

  3. Semivalue-based data valuation is arbitrary and gameable

    cs.LG 2025-06 conditional novelty 5.0 of 10

    Semivalue-based data valuations are shown to be highly sensitive to plausible utility-function choices and are gameable under the paper's weak definition of gameability.

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