Integration of ifc objects and facility management work information using Semantic Web
The management of information throughout a building's lifecycle is becoming increasingly important, and building information modeling (BIM) is often used to ensure the interoperability of data. However, BIM-based facility information from the construction phase is difficult to access and use du...
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Veröffentlicht in: | Automation in construction 2018-03, Vol.87, p.173-187 |
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Sprache: | eng |
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Zusammenfassung: | The management of information throughout a building's lifecycle is becoming increasingly important, and building information modeling (BIM) is often used to ensure the interoperability of data. However, BIM-based facility information from the construction phase is difficult to access and use during the operation and maintenance phase. This occurs because the BIM information is not utilized well in facility management (FM). In this research, we propose an approach to effectively manage BIM-based FM information by linking the BIM-based building elements and FM work information in an FM system database. We present a Semantic Web-based FM information system that semantically links BIM data to relevant historical work records. The proposed ontology was evaluated using a sample dataset of the architectural maintenance work records of an office building. Using the proposed approach, facility managers will be able to increase their efficiency in searching related work records that consider shared BIM objects by enhancing the interoperability and accessibility of FM data via the Semantic Web.
•This paper proposes a Semantic Web-based FM information management approach.•The approach finds IFC objects related on the historical relevant maintenance work records.•The core of our approach is to define ontologies capturing the concepts associated with work types.•The ontology semantically links an IFC object and FMS DB as a requirement of a FM work.•This paper developed the automatic process of linking concepts among BIM-based FM information. |
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ISSN: | 0926-5805 1872-7891 |
DOI: | 10.1016/j.autcon.2017.12.019 |