Table 2

Ideal-typical continuum of epistemic configurations in research data lifecycle practices

Lifecycle phase/dimensionMore communitarianHybridMore individualised
Processing and analysisShared infrastructures, collective or distributed division of labour, established pipelines; data often treated as a communal resourceShared standards or quality requirements combined with project- or group-specific datasets and bounded multidisciplinary workLocal tools and methods, individual or small-project responsibility; data constituted primarily as the material of one’s own project
DocumentationStandardised, code-, instrument- or pipeline-based documentation integrated into the workflowShared standards combined with contextual or project-specific additionsNarrative, local or manual documentation, often oriented to internal intelligibility and interpretive work
SharingExpected or routine sharing through established infrastructures or repositoriesControlled, conditional or permission-based sharingNegotiated, case-specific or request-based sharing; data often remain internal to the project
Source(s): Author’s own work

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