Abstract
The development of trustworthy Health Data Spaces (HDS) is currently in the spotlight of digital health policy. Diverse stakeholders agree on the importance of trust for the adoption and legitimacy of HDS. This emphasis on trust has led to the development of conceptual work describing what trust in HDS entails, along with initial suggestions on how trust principles can be operationalized in HDS governance and architecture. In contrast, little research has been conducted on methods to evaluate the performance of trust-building principles and the overall trustworthiness of HDS. In response, we propose two distinct methodologies that share a common focus on assessing trustworthiness: A) Trust Performance Indicators collect routine data related to trust-building principles. B) Trust Stress Tests support the design of resilient HDS architectures by identifying potential future scenarios that could undermine their trustworthiness. Through these methodologies, we aim to contribute to the ongoing development of trustworthy HDS.