Data market platforms

激励 资产(计算机安全) 数据共享 计算机科学 市场数据 数据集成 价值(数学) 数据科学 货币 业务 计算机安全 数据挖掘 财务 经济 病理 货币经济学 替代医学 微观经济学 机器学习 医学
作者
Raul Castro Fernandez,Pranav Subramaniam,Michael J. Franklin
出处
期刊:Proceedings of the VLDB Endowment [Association for Computing Machinery]
卷期号:13 (12): 1933-1947 被引量:95
标识
DOI:10.14778/3407790.3407800
摘要

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 desired outcomes, 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.
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