Data Governance in Practice: Disentangling the Socio‐legal and Technical Dimension of Transportation Data

ABSTRACT Data governance in practice is shaped by a complex interplay of socio‐legal frameworks, institutional arrangements, cultural attitudes, and technological capabilities. Understanding these interlinked dimensions is essential for effective management of information systems, particularly in sectors that are highly data‐dependent for forecasting and delivering social services, like transportation. This study explores these dynamics through the specific case of vehicle speed data governance. Employing a mixed‐methods approach, the research combines computational topic modeling using Latent Dirichlet Allocation (LDA) on a corpus of 237 policy and institutional documents with qualitative analysis to identify key governance themes. Findings reveal the prominence of national reporting mandates and technological adoption at the local level, alongside notable gaps in data lifecycle management and stewardship. To complement these insights, forthcoming interviews with data managers aim to clarify governance processes and challenges not evident in policy texts. This work advances our understanding of how socio‐technical and legal factors collectively influence the governance and effectiveness of urban data infrastructures.