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Semantic data models for built environment applications
Funded by the Engineering and Physical Sciences Research Council (EPSRC)
An increasing demand in social & professional connectivity fueled by the pressures of rapidly evolving technological advances is placing great demands on current Facilities Management (FM) information and communications technologies to deliver more interactive data and knowledge management to facilitate decision making processes. The heterogeneous characteristics of the diverse data formats used across FM data environments has however presented a challenge for the industry. The underlying premise is that current asset information / data management processes have remained largely unstructured and siloed leading to incredibly time-consuming and inefficient day-to-day maintenance practices. Interoperability among heterogeneous systems depends critically on the capability of their relational databases to reuse schema and uniquely identify data elements globally across databases. Annotation of data makes it easier to connect and leverage the right data without the need to integrate disparate data silos. Studies suggest that ontologies can provide the structure for the representative domain by defining concepts and properties that relate them and by increasing the semantic level. The aim of this research study is to investigate how an asset information system based linked data and semantic technologies can be used to discover data stored across FM multiple systems to effectively remove data silos to improve internal day-to-day asset maintenance processes.