Flexible Filtering of Heterogeneous Data Using the Example of the Design and Simulation of Building Integrated Photovoltaics

According to the Building Information Modeling (BIM) methodology, all participants must be provided with the information relevant to their tasks in the required level of detail at the appropriate time. In the future, the amount of detailed digital information will further increase. Therefore, we propose rule-based filtering beyond the purely class-based extraction of subsets of the overall model. The source of digital information can be a central data model, from digital product data of component manufacturers or generally from the worldwide web. After the rule-based filtering, automatic parsing into the target language takes place. As an application example, we demonstrate this methodology for the simulation of buildingintegrated photovoltaics as an example. According to the Building Information Modeling (BIM) methodology, all participants must be provided with the information relevant to their tasks in the required level of detail at the appropriate time. In the future, the amount of detailed digital information will further increase. Therefore, we propose rule-based filtering beyond the purely class-based extraction of subsets of the overall model. The source of digital information can be a central data model, from digital product data of component manufacturers or generally from the worldwide web. After the rule-based filtering, automatic parsing into the target language takes place. As an application example, we demonstrate this methodology for the simulation of buildingintegrated photovoltaics as an example.