In recent years, three-dimensional Digital Image Correlation (3D-DIC) has proven to be a reliable technique for Structural Health Monitoring (SHM) by allowing full line-of-sight, high-resolution, and contactless measurements of structures. The large amount of raw output resulting from 3D-DIC requires appropriate methods to visualise and analyse the data systematically. In this context, Building Information Modeling (BIM) emerges as a robust repository and data management tool to store, query, and assess long sequences of SHM data. Different sensors have been used to collect SHM data and digital sensors have been created in the BIM environment to mimic the behaviour of the physical ones on site. This research focuses on the BIM implementation of virtual sensors from information retrieved using 3D-DIC to store frequency and time domain data and monitor structural changes in a targeted system over time. The application of the Phase-based Motion Magnification (PMM) technique is proposed as a preprocessing tool for 3D-DIC analysis videos to obtain displacement information in specific frequency bands and make those values structurally effective. As a case study, a three-story aluminium frame structure with a damaged and undamaged configuration is used to validate the developed methodology.