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.
| Language | English |
|---|---|
| Number of pages | 11 |
| Journal | Visualization in Engineering |
| Volume | 5 |
| Issue number | 1 |
| DOIs | |
| Status | Published - 21 Mar 2017 |
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Keywords
- Data completion
- Formal language
- Shape grammars
- Knowledge Management
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
Cite this
Data completion in building information management: electrical lines from range scans and photographs. / Krispel, Ulrich; Evers, Henrik Leander; Tamke, Martin; Ullrich, Torsten.
In: Visualization in Engineering, Vol. 5, No. 1, 21.03.2017.Research output: Contribution to journal › Article › Research › peer-review
}
TY - JOUR
T1 - Data completion in building information management: electrical lines from range scans and photographs
AU - Krispel, Ulrich
AU - Evers, Henrik Leander
AU - Tamke, Martin
AU - Ullrich, Torsten
PY - 2017/3/21
Y1 - 2017/3/21
N2 - BackgroundThe 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.MethodsIn 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.ResultsThe generative paradigm can encode domain expert knowledge in a machine-readable way. In this article we demonstrate its usage to represent norms and standards.ConclusionsThe benefit of our method is the further completion of digital building information models – a necessary step to take full advantage of building information modeling.
AB - BackgroundThe 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.MethodsIn 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.ResultsThe generative paradigm can encode domain expert knowledge in a machine-readable way. In this article we demonstrate its usage to represent norms and standards.ConclusionsThe benefit of our method is the further completion of digital building information models – a necessary step to take full advantage of building information modeling.
KW - Data completion
KW - Formal language
KW - Shape grammars
KW - Knowledge Management
U2 - 10.1186/s40327-017-0042-5
DO - 10.1186/s40327-017-0042-5
M3 - Article
VL - 5
JO - Visualization in Engineering
T2 - Visualization in Engineering
JF - Visualization in Engineering
SN - 2213-7459
IS - 1
ER -