Computational taxonomy development for digital passports using semantic topic modelling to advance circular construction

As circular economy principles become increasingly embedded in regulations, digital passports are being recognised as key enablers of circular construction. Although several digital passport concepts have been proposed, their implementation remains constrained by the lack of standardised, hierarchically structured data requirements. This paper presents a computational workflow that combines semantic topic modelling and unsupervised clustering to derive a common digital passport taxonomy from the state-of-the-art literature. To address inconsistencies in property names across data requirements, large language models are used to generate contextual property descriptions from the literature. Expert evaluation aligns moderately with cluster cohesion and diverges on hierarchical fit, indicating that statistically optimal taxonomies require manual moderation. The workflow can be used to semi-automatically generate and moderate taxonomies that structure disparate data requirements. This application can assist construction professionals in developing standardised digital passport data templates aligned with evolving regulations.