Paper Type
Complete
Abstract
Data spaces provide the environment for sovereign inter-organizational data sharing. However, data sharing in practice remains hampered, as data is perceived as a strategic resource and organizations lack approaches to assess the criticality, protection needs, or value of data assets. As a result, organizations struggle to describe their datasets, and data trustees face difficulties in connecting data providers and consumers. Based on a literature review and expert interviews, this paper proposes a process model for assessing data assets beyond technical metadata. Drawing on boundary object theory, the model provides a structured approach for standardized communication through enriched data catalogs. It enables the alignment of expectations and boundary conditions between data providers and consumers and supports data trustees in facilitating more efficient and trust-based matchmaking. The model thus addresses key challenges in broker-based data spaces and contributes to advancing structured and transparent data sharing practices.
Paper Number
2221
Recommended Citation
Werling, Maxmilian; Stuber, Kim; Merz, Sarah; Petrik, Dimitri; and Lachenmaier, Jens F., "Bridging Boundaries: A Process Model for Assessing Data Assets and Products in Broker-Based Data Sharing Environments" (2025). AMCIS 2025 Proceedings. 7.
https://aisel.aisnet.org/amcis2025/data_eco/data_eco/7
Bridging Boundaries: A Process Model for Assessing Data Assets and Products in Broker-Based Data Sharing Environments
Data spaces provide the environment for sovereign inter-organizational data sharing. However, data sharing in practice remains hampered, as data is perceived as a strategic resource and organizations lack approaches to assess the criticality, protection needs, or value of data assets. As a result, organizations struggle to describe their datasets, and data trustees face difficulties in connecting data providers and consumers. Based on a literature review and expert interviews, this paper proposes a process model for assessing data assets beyond technical metadata. Drawing on boundary object theory, the model provides a structured approach for standardized communication through enriched data catalogs. It enables the alignment of expectations and boundary conditions between data providers and consumers and supports data trustees in facilitating more efficient and trust-based matchmaking. The model thus addresses key challenges in broker-based data spaces and contributes to advancing structured and transparent data sharing practices.
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