Paper Type
Complete
Paper Number
PACIS2025-1663
Description
As data has become a critical asset in today’s digital economies, the sharing and reuse of data has received high attention from researchers. New concepts of data intermediaries have evolved, addressing the strategic goal of greater digital sovereignty while ensuring compliance with European legal frameworks. This paper introduces an initial concept for a reference architecture for Data Trusts, which act as intermediaries facilitating secure and trustworthy data stewardship and sharing within relevant ecosystems. Through a structured analysis of existing literature, we identify and evaluate four distinct Data Trust architectures using qualitative and quantitative criteria. Our analysis reveals notable diversity in application domains, core components, and candidate technologies. Building on this, we derive a foundational and overarching schema for developing a holistic, integrated reference architecture. As our research particularly targets SMEs aspiring to establish themselves as Data Trusts, we spot specific challenges and requirements they face in fulfilling this role.
Recommended Citation
Rieder, Florian; Aldenhoff, Timon T.; Acev, David; Biyani, Sankalp; Riehle, Dennis M.; and Wimmer, Maria A., "SMEs aiming to operate as Data Trusts: A Reference Architecture" (2025). PACIS 2025 Proceedings. 5.
https://aisel.aisnet.org/pacis2025/dig_plat/di/5
SMEs aiming to operate as Data Trusts: A Reference Architecture
As data has become a critical asset in today’s digital economies, the sharing and reuse of data has received high attention from researchers. New concepts of data intermediaries have evolved, addressing the strategic goal of greater digital sovereignty while ensuring compliance with European legal frameworks. This paper introduces an initial concept for a reference architecture for Data Trusts, which act as intermediaries facilitating secure and trustworthy data stewardship and sharing within relevant ecosystems. Through a structured analysis of existing literature, we identify and evaluate four distinct Data Trust architectures using qualitative and quantitative criteria. Our analysis reveals notable diversity in application domains, core components, and candidate technologies. Building on this, we derive a foundational and overarching schema for developing a holistic, integrated reference architecture. As our research particularly targets SMEs aspiring to establish themselves as Data Trusts, we spot specific challenges and requirements they face in fulfilling this role.
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