Paper Number
ECIS2026-1652
Paper Type
CRP
Abstract
This study introduces a conceptualization of data journeys, addressing a prevailing gap in research that has emphasized downstream dynamics of data use while overlooking the processes through which data are mobilized and how their own meaning is constructed, shaping their later economic value in use. Drawing on relational perspectives, the study conceptualizes data journeys as socio-technical trajectories shaped by interactions among actors, infrastructures, and governance arrangements. A meta-synthesis of 39 qualitative case studies reveals three data journey configurations - bounded, boundary-crossing, and unbounded - distinguished by the degree to which data remain tied to their original context and purpose. The analysis traces data journeys through four elements - start, ride, stay, and end - and shows how their configurations generate path dependencies for meaning-making and value realization. The study thus offers a conceptual framework for examining how heterogeneous data journeys shape how data are interpreted across contexts.
Recommended Citation
Ulschmid, Stefanie, "Reconstructing Data Journeys: A Meta-Synthesis Of Qualitative Case Studies" (2026). ECIS 2026 Proceedings. 7.
https://aisel.aisnet.org/ecis2026/datasc_isresearch/datasc_isresearch/7
Reconstructing Data Journeys: A Meta-Synthesis Of Qualitative Case Studies
This study introduces a conceptualization of data journeys, addressing a prevailing gap in research that has emphasized downstream dynamics of data use while overlooking the processes through which data are mobilized and how their own meaning is constructed, shaping their later economic value in use. Drawing on relational perspectives, the study conceptualizes data journeys as socio-technical trajectories shaped by interactions among actors, infrastructures, and governance arrangements. A meta-synthesis of 39 qualitative case studies reveals three data journey configurations - bounded, boundary-crossing, and unbounded - distinguished by the degree to which data remain tied to their original context and purpose. The analysis traces data journeys through four elements - start, ride, stay, and end - and shows how their configurations generate path dependencies for meaning-making and value realization. The study thus offers a conceptual framework for examining how heterogeneous data journeys shape how data are interpreted across contexts.
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