# Data Market Platforms: Trading Data Assets to Solve Data Problems

arXiv: https://arxiv.org/abs/2002.01047 · HTML: https://mlsanity.com/paper/2002.01047/

## Key facts

- Cited by 7 papers in the map (data through 7 Oct 2026).
- First posted on arXiv 3 Feb 2020.

## Built on by (most cited first, 7 of 7)

- [Pneuma: Leveraging LLMs for Tabular Data Representation and Retrieval in an End-to-End System](https://mlsanity.com/paper/2504.09207/) (2025)
- [Data Pricing in Machine Learning Pipelines](https://mlsanity.com/paper/2108.07915/) (2021)
- [METAM: Goal-Oriented Data Discovery](https://mlsanity.com/paper/2304.09068/) (2023)
- [ML-Asset Management: Curation, Discovery, and Utilization](https://mlsanity.com/paper/2509.23577/) (2025)
- [LLM-based Multi-Agent System for Simulating Strategic and Goal-Oriented Data Marketplaces](https://mlsanity.com/paper/2511.13233/) (2025)
- [Local Shapley: Model-Induced Locality and Optimal Reuse in Data Valuation](https://mlsanity.com/paper/2603.03672/) (2026)
- [Designing Reputation Systems for Manufacturing Data Trading Markets: A Multi-Agent Evaluation with Q-Learning and IRL-Estimated Utilities](https://mlsanity.com/paper/2511.19930/) (2025)

## Abstract (arXiv)

Data only generates value for a few organizations with expertise and resources to make data shareable, discoverable, and easy to integrate. Sharing data that is easy to discover and integrate is hard because data owners lack information (who needs what data) and they do not have incentives to prepare the data in a way that is easy to consume by others. In this paper, we propose data market platforms to address the lack of information and incentives and tackle the problems of data sharing, discovery, and integration. In a data market platform, data owners want to share data because they will be rewarded if they do so. Consumers are encouraged to share their data needs because the market will solve the discovery and integration problem for them in exchange for some form of currency. We consider internal markets that operate within organizations to bring down data silos, as well as external markets that operate across organizations to increase the value of data for everybody. We outline a research agenda that revolves around two problems. The problem of market design, or how to design rules that lead to the outcomes we want, and the systems problem, how to implement the market and enforce the rules. Treating data as a first-class asset is sorely needed to extend the value of data to more organizations, and we propose data market platforms as one mechanism to achieve this goal.