Digital twins are expected to facilitate the digital transformation of the architecture, construction, engineering, management, operation, and conservation industry. One of their main applications in the field of bridge engineering is the possibility of real-time damage detection. To achieve this, advanced anomaly detection algorithms need to be validated to alert bridge operators on the risks related to the detected anomalies. A synthetic data generation framework has been proposed to generate benchmark databases for testing and validation as a cheaper and faster alternative to the collection of real monitoring data. In this paper we present the S101 Bridge, which has been selected as first case study for the generation of the proposed synthetic database. A finite element model of the bridge was developed and calibrated based on the reported natural frequencies and mode shapes of the actual structure available in the literature. The calibration process is described in detail along with the sensitivity analysis of the considered parameters. The results indicate a strong agreement between the first four natural frequencies and mode shapes of the experimental and numerical bridge model. It is concluded that the calibrated model is suitable for the generation of bride digital twins what-if scenarios, which will be of great significance for both practitioners and the research community.@en