In order to implement the business value described in the previous chapter, data spaces need to ensure trust for their participants to share and mutualise data in a decentralised way. Moreover, the governance model needs to ensure each participant can maintain control over its data and services in order to ensure the data space delivers its value: enabling more data sharing thanks to a trusted infrastructure.
There are different levels on which these decisions are implemented: at data space level, at data space use case level and at participant level. To enable such trust decisions need to be made on standards, rules to access data, rules to enter and exit the data space, roles and responsibilities of participants, business models and use cases. These decisions need to be commonly accepted, necessitating a governance model that encompasses this complexity.
This multi-layered and multi-dimensional governance is complex and needs to involve a set of very different stakeholders (public and private, big and small). Without this holistic and systemic model, the governance will not be able to ensure the trust and adoption needed for the data space to function.
In this section, DS4Skills outlines its recommendations on:
- The governance framework to be adopted: the different layers of governance needed in the data space, the decisions made at each level and the key documents needed to set up a data space governance model,
- The roles and responsibilities: the main type of roles in a skills data space, their obligations with a special focus on the Data Space Governance Authority and the Personal Data Intermediary,
- The governance building blocks: the main tools and processes needed to standardise and automate the governance model for a quick and efficient data space set up.
