An ontology-driven framework for digital transformation and performance assessment of building materials

• User-centric web application to benchmark material performance. • Semantic web and linked data supporting FAIR material properties. • Building material performance ontology. • Material classification and property definitions following international standards. Material Information Modelling (MIM) is a cornerstone of Building Performance Simulation (BPS). However, defining and exchanging data between building modelling and simulation tools is cumbersome due to notable deficiencies in the granularity of material information descriptions. The inadequacies in the data models and exchanges lead to faulty interpretations of material properties in building performance assessment. The material science domain strives to advance material research and expedite the market readiness of novel materials through intricate data modelling, performance computations, and interdisciplinary communication channels. In addition to the latter, adopting the Findable, Accessible, Interoperable, and Reusable principles holds significant potential in promoting accurate MIM within Architecture, Engineering and Construction. This study introduces an ontology-driven framework leveraging Semantic Web technologies and Linked Data to support MIM in the context of Building Information Modelling and BPS. The framework implementation is demonstrated in a web-based application that enables the dynamic assessment and benchmarking of building materials based on the Guggenheim, Anderson and de Boer model and thermal resistance computations. The development of the framework relies on ontology engineering principles to represent domain knowledge in a Building Material Performance ontology, as well as Systems Engineering coupled with test-driven development for requirement engineering, system design, implementation, and validation. The results include a novel MIM data model enabling material classification and property definitions in alignment with international standards. The implementation validates and assesses the logic of the proposed data model and software application by conducting hygric and thermal performance assessments applied on case studies.