Commercializing data and data-related services has gained in importance in recent years. Driven by digitalization and the Internet-of-Things (IoT), companies and individuals continuously generate vast amounts of data. Data marketplaces have emerged to support these data providers in selling their data to different data consumers. However, data marketplaces face challenges in different data governance decision domains that inhibit their adoption. To get a better understanding of how data marketplaces counteract these challenges, this paper develops a taxonomy of data governance decision domains in data marketplaces. We used a taxonomy development method to inspect 13 data marketplaces from eight countries. The resulting taxonomy shows an overview of mechanisms concerning data quality, data security, data architecture, metadata, data lifecycle, data storage, and data pricing. We discuss common instantiation patterns, highlight gaps, and propose possible solutions. The taxonomy sets a foundation for further research and theory-building on data marketplaces. Practitioners can use the taxonomy to develop customized data governance strategies for data marketplaces.

近年来，数据和数据相关服务的商业化变得越来越重要。在数字化和物联网 (IoT) 的推动下，公司和个人不断产生大量数据。数据市场已经出现，以支持这些数据提供者将他们的数据出售给不同的数据消费者。然而，数据市场在不同的数据治理决策领域面临着阻碍其采用的挑战。为了更好地了解数据市场如何应对这些挑战，本文开发了数据市场中数据治理决策域的分类法。我们使用分类法开发方法检查了来自八个国家的 13 个数据市场。由此产生的分类法概述了有关数据质量、数据安全、数据架构、元数据、数据生命周期的机制，数据存储和数据定价。我们讨论常见的实例化模式，突出差距，并提出可能的解决方案。该分类法为数据市场的进一步研究和理论构建奠定了基础。从业者可以使用分类法为数据市场开发定制的数据治理策略。