Within the European TURNkey project, a knowledge-based exposure-modelling framework was developed enabling the consideration of different levels of investigation and data availability. In particular, the proposed framework recognizes various levels and origins of uncertainties as well as the completeness of a building stock catalogue. Despite enormous efforts, the main question remains unanswered: How reliable could be the developed tools and instruments if they are not tested and confirmed by real events. The L’Aquila 2009 earthquake has been subject of several analysis strategies to enrich the knowledge of earthquake engineering. In the present, the information provided by Italian Observed Damage Database is analyzed, specifically the data related to the L’Aquila 2009 seismic sequence, within the delimited area of the historical center of the city. A second source where the European Macroseismic Scale was used as reference is hereby integrated to the study and results are compared. A methodology is implemented for a systematic evaluation of database, taking as basis the EMS-98. From the data analysis a proposal is given to define a comparable EMS-98 building typology and for the assignments of vulnerability classes considering an optimistic, pessimist and most likely criteria. The reliability of the sample is then explored taking as basis the Knowledge-based exposure modelling framework established by the TURNkey Project, and the parameter is evaluated through an empirical inspection of frontal (lateral) views available in Google Street View (2022). Images before and after the event are collected and compared with the available data. Intrinsic encountered problems are then enlisted and discussed, with respect to the use of the database, the correlation of the information and the postprocessing needed to use the data in damage prognosis. This paper intends to demonstrate how reliable datasets for the building stock including structural types and corresponding vulnerability classes can be elaborated. Not at least, the exposure modelling has to transform the available data into a descriptive form that can be linked with the Fragility and/or Vulnerability Functions, directly with the expectation that these assignments are the best suited or representative ones. The data layers provided by the study enable the test and train the applicability of the exposure modelling techniques for the selected event and target region.