Analyzing Distributed Medical Data in FAIR Data Spaces

The exponential growth in data production has led to increasing demand for high-quality data-driven services. Additionally, the benefits of data-driven analysis are vast and have significantly propelled research in many fields. Data sharing benefits scientific advancement, as it promotes transparency, and collaboration, accelerates research and aids in making informed decisions. The European strategy for data aims to create a single data market that ensures Europe's global competitiveness and data sovereignty. Common European Data Spaces ensure that data from different sources are available in the economy and society, while data providers (e.g., hospitals and scientists) control data access. The National Research Data Infrastructure for Personal Health Data (NFDI4Health) initiative is a prime example of an effort focused on data from clinical trials and public health studies. Collecting and analyzing this data is essential to developing novel therapies, comprehensive care approaches, and preventive measures in modern healthcare systems. This work describes distributed data analysis services and components that adhere to the FAIR data principles (Findable, Accessible, Interoperable, and Reusable) within the data space environment. We focus on distributed analytics functionality in Gaia-X-based data spaces. Gaia-X offers a trustworthy federation of data infrastructure and service providers for European countries.