The provision of geometric and semantic information is among the most fundamental tasks in BIM-based building design. As the design is constantly developing along with the design phases, there is a need for a formalism to define its maturity and detailing. In practice, the concept of Level of Development (LOD) is used to specify what information must be available at which time. Such information is contractually binding and crucial for different kinds of evaluations. Numerous commercial and open-source BIM tools currently support the automatic validation of semantic information. However, the automatic validation of the modeled geometry for fulfilling the expected detailing requirements is a complex and still unsolved task. In current practice, domain experts evaluate the models manually based on their experience. Hence, this paper presents a framework for formally analyzing and automatically checking the Level Of Geometry (LOG) of building information models. The proposed framework first focuses on generating a LOG dataset according to the popular LOD specifications. Afterwards, multiple geometric features representing the elements’ complexity are extracted. Finally, two tree-based ensemble models are trained on the extracted features and compared according to their accuracy in classifying building elements with the correct LOG. Measuring the modeling time showed a 1.88–2.80-fold increase between subsequent LOGs, with an 8–15-fold increase for LOG 400 compared to LOG 200. The results of classifying the LOG indicated that the combination of 16 features can represent the LOG complexity. They also indicated that the trained ensemble models are capable of classifying building elements with an accuracy between 83% and 85%.

The iterative and developing nature of designing a building involves the specification and handling of vague, imprecise, and incomplete information. A crucial factor for mitigating the impact of these uncertainties on the decision-making process is to effectively quantify and communicate them among the project stakeholders. The interactive visualization of 3D building models provides great support for evaluating building designs. However, the currently available visualization methods of the available authoring tools do not incorporate the potential uncertainties associated with the geometric and semantic information of building elements. Currently, building models appear precise and certain, even in the early design stages, which can lead to false assumptions and model evaluations, affecting the decisions made throughout the design stages. Hence, this paper presents a set of visualization approaches, including intrinsic, extrinsic, animation, and walkthroughs, that have been developed to present the uncertainties associated with the building elements’ information. The efficiency of the approaches developed in this study was evaluated through an online survey and interviews. More specifically, the approaches were compared in terms of intuitiveness, applicability, and acceptance. The evaluation results positively indicated the participants’ ability to understand the amount and impact of the uncertainties on the design by using the developed approaches.