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Paper Type
Complete
Description
In the data economy, data has become an essential strategic resource for gaining a competitive advantage. Data spaces represent a relatively new phenomenon aimed at encouraging businesses to fully leverage the potential of data. Despite various approaches for definitions there remains a lack of clarity surrounding the conceptualization of data space, its perceived value, and the factors that drive its adoption. The conceptual ambiguity and synonymous usage of the term in academic and business literature present significant obstacles to targeted conceptualization and use. This paper addresses these issues by proposing primary properties of data space and contributes to the field by applying a semantic decomposition. Through this approach, we identified data space as having the following conceptual aspects Nature, Element, Function, Utility and Governance. These primitives highlight the growing need for security and privacy when sharing interorganizational data. In addition, we offer an initial definition of data spaces.
Paper Number
1816
Recommended Citation
Hutterer, Andreas; Krumay, Barbara; and Muehlburger, Manuel, "What Constitutes a Dataspace? Conceptual Clarity beyond Technical Aspects" (2023). AMCIS 2023 Proceedings. 5.
https://aisel.aisnet.org/amcis2023/eco_systems/eco_systems/5
What Constitutes a Dataspace? Conceptual Clarity beyond Technical Aspects
In the data economy, data has become an essential strategic resource for gaining a competitive advantage. Data spaces represent a relatively new phenomenon aimed at encouraging businesses to fully leverage the potential of data. Despite various approaches for definitions there remains a lack of clarity surrounding the conceptualization of data space, its perceived value, and the factors that drive its adoption. The conceptual ambiguity and synonymous usage of the term in academic and business literature present significant obstacles to targeted conceptualization and use. This paper addresses these issues by proposing primary properties of data space and contributes to the field by applying a semantic decomposition. Through this approach, we identified data space as having the following conceptual aspects Nature, Element, Function, Utility and Governance. These primitives highlight the growing need for security and privacy when sharing interorganizational data. In addition, we offer an initial definition of data spaces.
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