TrustNShare: Development of a Blockchain-Based Data Trust Model for Secure and Controlled Health Data Sharing Grounded on Empirical Research Hamza MAATOUK a,1 , Sebastian USCHMANN b , Sven FESTAG b , Tim SCHNEIDER b , Anna WEBER c , Ngo Manh KHOI c , Sven BOCK c , Stephan M. JONAS a , Cord SPRECKELSEN b and Friederike KLAN c a Institute of Digital Medicine, University Hospital Bonn, Bonn, Germany b Institute of Medical Statistics, Computer and Data Sciences (IMSID), Jena University Hospital c German Aerospace Center (DLR), Institute of Data Science ORCiD ID: Sven Festag https://orcid.org/0000-0002-2507-5901, Stephan M. Jonas https://orcid.org/0000-0002-3687-6165, Cord Spreckelsen https://orcid.org/0000-0002- 7301-1566, Friederike Klan https://orcid.org/0000-0002-1856-7334 Abstract. Ensuring data quality and protecting data are key requirements when working with health-related data. Re-identification risks of feature-rich data sets have led to the dissolution of the hard boundary between data protected by data protection laws (GDPR) and anonymized data sets. To solve this problem, the TrustNShare project is creating a transparent data trust that acts as a trusted intermediary. This allows for secure and controlled data exchange, while offering flexible datasharing options, considering trustworthiness, risk tolerance, and healthcare interoperability. Empirical studies and participatory research will be conducted to develop a trustworthy and effective data trust model. Keywords. Smart contracts, data trust, incentives 1. Introduction Sharing health data is crucial for clinical decision-making, care coordination, and public health initiatives. New techniques like differential privacy and distributed privacy- preserving computing offer more control over the flow of information [1]. But current data trust models lack transparency, making it difficult to fine-tune trustworthiness, risk tolerance, and data release criteria [2]. The TrustNShare project aims to create a transparent and flexible data trust model using blockchain and smart contracts to facilitate secure and controlled data exchange, encouraging data sharing and promoting optimal use scenarios for health data [3]. 1 Corresponding author: Hamza Maatouk,Institute of Digital Medicine, Faculty of Medicine, Venusberg Campus 1,Building 74, 53127Bonn.Email:Hamza.Maatouk@ukbonn.de. Healthcare Transformation with Informatics and Artificial Intelligence J. Mantas et al. (Eds.) © 2023 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/SHTI230472 238