Ontology-Based Framework for Construction Cost Management Using BIM for Small-Scale Public Infrastructure Projects

Abstract

Effective cost management in the Architecture, Engineering, and Construction (AEC) sector faces persistent challenges due to fragmented data environments, inconsistent information structures, and limited semantic interoperability among stakeholders. Although Building Information Modelling (BIM) is widely applied for cost estimation (5D BIM), its integration into comprehensive cost management remains constrained by data discontinuities and limited reuse of structured knowledge.

This study proposes an ontology-based framework for managing cost-related information in small-scale public infrastructure projects, focusing on standardized railway stations. The research methodology combines an empirical analysis of current 5D BIM practices in Germany, a narrative literature review of ontology-based approaches for construction cost estimation, and a case study of a representative railway station project. Established ontology engineering methods were adapted to define classes, properties, and taxonomies integrating product- and process-oriented perspectives.

The results indicate that cost development can be structured into four phases aligned with the Level of Development (LOD) concept: Level of Geometry (LoG), Level of Information Need (LoIN), Level of Cost Item (LoCI), and Level of Work Item (LoWI). The proposed framework enables a granular allocation of costs to building components and construction works, supports structured comparisons of tendered, budgeted, and executed costs, and promotes the systematic reuse of cost-related information. To assess its practical applicability, the proposed model for cost-information and knowledge structuring was implemented for the definitive cost estimate (LOD 3).

The novelty of this research lies in extending and adapting established AEC ontologies to the largely unexplored domain of small-scale railway stations. By bridging component- and activity-based cost perspectives, the research contributes to semantically enriched, interoperable cost management in public infrastructure delivery.