Our research group presented two papers at the 20th International Conference on Business Information Systems (Wirtschaftsinformatik) in Münster, Germany. Both papers address the topic of Data Trusts, a data intermediary model that ensures responsible data stewardship and governance.

WI - Internationale Tagung Wirtschaftsinformatik

The Internationale Tagung Wirtschaftsinformatik (WI) is the premier academic conference for business information systems research in the German-speaking community. It brings together researchers, practitioners and students to present and discuss the latest findings in the field of information systems. The 20th edition of the WI took place from September 14 to 17, 2025, at the University of Münster.

Paper Abstracts

AI Agents as Governance Actors in Data Trusts – A Normative and Design Framework

Authors: Arnold F. Arz von Straussenburg, Joris J. Marga, Timon T. Aldenhoff & Dennis M. Riehle

Data trusts have emerged as structured mechanisms to ensure responsible data stewardship grounded in fiduciary duties, transparent oversight, and user-centered governance. Meanwhile, recent advances in Artificial Intelligence (AI) transform Information Systems by automating decisions and enabling novel data-driven applications while raising ethical, security, and trust challenges. This paper proposes a design theory that unifies fiduciary principles, institutional trust, and AI ethics to guide the integration of AI into data trusts. We introduce four design principles: fiduciary alignment, traceability and accountability, transparent explainability, and autonomy-preserving oversight. These principles protect the beneficiaries' interests and the owner's rights, mitigate opacity and conflicts of interest, and maintain robust human supervision. The framework contributes to emerging governance approaches that consider fairness, trustworthiness, and societal acceptance of AI-driven data ecosystems. We conclude with recommendations for empirical validation and sector-specific adaptations to ensure responsible AI use for the common good.

Systematizing Different Types of Interfaces to Interact with Data Trusts

Authors: David Acev, R. Rieder, Dennis M. Riehle & Maria A. Wimmer

The interactions between Data Trusts as fiduciary data sharing intermediaries and data actors communicating with Data Trusts need to be seamless and supported by guidelines and regulatory standards to ensure trustworthiness. To achieve such coherent data sharing, corresponding interfaces have to be designed on human-system as well as on system-system level. In a data trust ecosystem, human interaction of the data actors with the Data Trust is accomplished via user interfaces, ie the human-system interaction in the ecosystem. The interaction on the system-system level is manifested through technical interfaces established in Data Trusts. To ensure standardized data sharing, Data Trusts need to be competent in handling different data structures and to provide suitable connections with data storages. We conduct a systematic analysis of existing human and technical interfaces in literature, and we highlight gaps and insufficiently considered topics that are valuable for the implementation of Data Trusts.