TRANSFORMING DISTRIBUTED DATA INTO REUSABLE INFORMATION: A CENTRALISED BIM STRATEGY FOR A COMMON DATA ENVIRONMENT IN THE A27 HOUTEN–HOOIPOLDER INFRASTRUCTURE PROJECT

Authors

Michiel Bienens
BESIX
Vera A. Aparício
GRID
Cora Van de Poppe
Utrecht University
https://orcid.org/0000-0002-1394-7354
José O. Pedro
Instituto Superior Técnico

Synopsis

The Architecture, Engineering, Construction and Operations (AECO) sector generates large volumes of project data, yet only a small fraction is systematically reused across disciplines and lifecycle stages. This fragmentation prevents data from becoming actionable information and inhibits progress towards a single source of truth and linked data ecosystems. Current BIM practices and standards have advanced interoperability and common data environments, but practical evidence on how to operationalise centralised data reuse remains limited. This study addresses the problem of distributed data sources in large infrastructure projects by investigating how a unified, centralised data source can drive multiple project processes and information domains, enabling reuse, synchronisation and validation of information across design, execution and disciplines. A case study of the A27 Houten-Hooipolder infrastructure project (The Netherlands) evaluates a methodology based on a unified information model and a shared metadata structure as the core data source. Through this hub, project development and planning, BIM models, and validation workflows were governed and updated. The results indicate that integrated data management reduces redundant modelling and information losses, improves traceability and enhances alignment between teams. Qualitative stakeholder reflections indicate that model-derived quantities alone are insufficient to explain later-phase cost outcomes, where execution method, temporary works and time-related drivers become dominant. The contribution is framed as improving cross-domain traceability and explainability, supported by a phase-dependent indicator set for subsequent quantitative validation. The study contributes insights into enabling data reuse in BIM workflows and outlines implications for standards and future research.

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Published

26 June 2026

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This work is licensed under a Creative Commons Attribution 4.0 International License.