Abstract
Background: The concept of building information management (BIM) is based on its holistic nature. This idea pays off, if all relevant information is fused into one consistent data set. As a consequence, the completeness of data is vital and the research question on how to complete data automatically remains open. Methods: In this article we present a data completion technique based on knowledge management. We encode expert and domain knowledge in a generative system that represents norms and standards in a machine-readable manner. The implementation of this approach be used to automatically determine a hypothesis on the location of electrical lines within indoor range scans. Results: The generative paradigm can encode domain expert knowledge in a machine-readable way. In this article we demonstrate its usage to represent norms and standards. Conclusions: The benefit of our method is the further completion of digital building information models – a necessary step to take full advantage of building information modeling.
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Krispel, U., Evers, H. L., Tamke, M., & Ullrich, T. (2017). Data completion in building information management: electrical lines from range scans and photographs. Visualization in Engineering, 5(1). https://doi.org/10.1186/s40327-017-0042-5
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