Architecture building blocks for data governance in data spaces

Abstract

The growing importance of data as a driver of the digital economy is promoting the creation of data spaces for the secure and controlled exchange of data between organizations. Data governance is emerging as an essential pillar to ensure efficient, ethical and transparent access and use of data in these ecosystems. The article reviews the state of the art to identify the specific requirements that data governance must address in data spaces and proposes a reference enterprise architecture to facilitate the design, development and implementation of a data governance system for a data space scenario. The proposed framework has already been formally defined and validated in the context of Industry 4.0, and is now adapted to the particular characteristics and needs of data spaces. This architecture focuses on key aspects of data governance in data spaces, such as new requirements, principles, organization, roles and responsibilities, and data quality, security and metadata management, as well as the data lifecycle in the data space. This research contributes to guiding data space government bodies to formalize data strategies and high-level governance principles in concrete architectural components that establish the capacities to be implemented within the data ecosystem. To support practical adoption, this work also provides clarifying examples of different blocks of architecture.