The digital twin is often used in the context of structural health monitoring, but at the same time as a concept it is vaguely defined. In this contribution we will show how we incorporated the concept of digital twin into OWI-lab’s research on structural health monitoring of offshore wind turbines. For the monitoring of offshore wind turbine we consider a digital twin as an aid to interpret the results of structural health monitoring data or as a tool to expand its scope. In particular we consider the digital twin is an essential tool to translate changes in monitoring metrics into physical and actionable information. A lot of energy is often spent in the automatic updating of the digital twin, but in our experience it is far more vital to question modelling assumptions to begin with. Using data from over 100 turbines we discovered that the as-designed soil-structure interaction model and therefore the boundary conditions were suboptimal. And therefore any inference on the amount scouring, would have been erroneous without changing the model’s boundary conditions and modelling assumptions to begin with. A similar conclusion emerged in virtual sensing where the mode shapes are used to predict the strain histories at locations where no sensors are installed, and also here the predictions are only as good as the model is. In this contribution we’ll share examples from experiences in merging monitoring and modelling of offshore wind turbines over the past years. With a particular focus on damage identification and virtual sensing for fatigue life assessment.