A data management perspective on building material classification: A systematic review

Material information, such as properties and indicators, is essential for building performance assessment. The interoperability between applications and the harmonisation of data related to buildings, materials, energy consumption, environmental performance, etc., has been widely discussed in research. Building Information Modelling (BIM) has enabled a more transparent and accurate data exchange between tools. Semantic data modelling and web technologies have significantly impacted building and material modelling domains, as they allow data structures to be linked based on their formal semantic representations. Yet, there is a missing link between material modelling, data modelling and building simulation, and reliable and scalable material information is often neglected. This study introduces a data management perspective on building material data, property definition and classification. The article presents an extensive systematic review of the intersection of BIM, Material Information Modelling, material databases and the respective material data exchange capabilities of existing Building Performance Simulation tools. Finally, the article proposes a material classification and mapping mechanism that relies on concepts and standards from the building and material domains. The findings indicate (i) inconsistent classification taxonomies throughout various simulation software, (ii) inconsistent aggregation of material information, and (iii) missing link between high and low aggregation levels of material information. The proposed material classification and mapping schema aims to harmonise material information definition from multiple sources and help access and retrieve such information in an accurate and scalable manner. As such, the study contributes to a deeper understanding of how material property data should be defined and modelled to enable more accurate and efficient material data exchange and performance assessment.