The uncertainty associated with basement construction presents a significant challenge to sustainable underground construction. Monitoring during and after construction plays a crucial role in addressing these uncertainties by refining design methods and promoting a more efficient, performance-based design approach. Effective data management and analysis, facilitated by long-term monitoring, are essential for successful monitoring practices. However, the construction industry frequently struggles to fully leverage the vast amounts of data generated, owing to fragmented sources, non-standard formats, and high operational costs. Consequently, the industry finds itself in a paradox of being data-rich but information-poor. Digital twin is an emerging solution within the industry 4.0 framework, which refers to a set of virtual information representations that mimics the structure, context, and behaviour of a natural, engineered, or social system which is dynamically updated with data from its physical counterpart and has a predictive capability to inform decisions for realising value. A reflective twin considered as a subset of digital twin, reflects in-time status of entities i.e. “What is happening”. In this paper a BIM-based workflow that enables seamless integration, processing, and visualisation of sensor monitoring data is proposed as a minimum viable product for a reflective twin for long-term basement monitoring. The methodology includes pre-processing of sensor data, archiving in BIM, and visualising complex datasets within a 3D context using computational BIM tools. The proposed workflow is tested on a case study involving long-term monitoring of a basement structure. The study demonstrates the effectiveness of the reflective twin in enhancing data management, providing a scalable, software-agnostic solution for long-term monitoring. By addressing industry challenges such as data fragmentation and lack of standardisation, this workflow enhances both the accuracy and efficiency of data management, offering a scalable solution for future projects and facilitating project-to-project learning. The case study implementation offered important insights into the long-term behaviour of tension piles in basements impacted by soil heave, helping to improve design methods and support more sustainable and resilient underground construction.