Narrowing the performance deficit between design intent and real-time environmental and energy performance of buildings is a complex and involved task, impacting on all building stakeholders. Buildings are designed, built and operated with the use of increasingly complex technology and throughout their building life-cycle, produce vast quantities of data. However, many commercial buildings do not perform as originally intended.This paper presents a a dual strand approach to the performance gap problem, describing how heterogeneous building data sources can be transformed into semantically enriched information. This data can serve as a data service for a structured performance analysis approach, at the enterprise level. A performance management framework is described which builds on the semantically enriched information. The performance framework is an approach to performance management which describes performance in a series of objectives which can be evaluated against performance data. The demonstrator illustrates how heterogeneous data can be published semantically and then interpreted using a cross life-cycle performance framework approach.
A pronounced gap often exists between expected and actual building performance. The multi-faceted and cross lifecycle causes of this performance gap are found in design assumptions, construction issues and commissioning and operational compromises. Some important factors are firmly rooted in the lack of interoperability around building information. New solutions to the interoperability challenge offer the potential to leverage and reuse available heterogeneous data in a manner that can significantly assist building performance assessment. Linked data provides an open, modular and extensible solution for the challenge. However, in the buildings domain, the integration of rule-based performance metrics and contextual information has yet to be formally established. This paper describes an approach to the provision of in-depth building performance assessment through the integration of OpenMath and linked data. An ontology describing performance metrics in RDF is presented, together with an automated metric evaluation solution using multi-silo queries and computer algebra systems, providing a flexible, automated and extensible mechanism for the assessment of building performance. Building managers and engineers can simultaneously analyse time-series building performance
efficiency of the architecture against a purely RDF-based solution that also stores all of the time-series data in RDF for a virtual building. The hybrid architecture also avoids the duplication of time-series data and overcomes some of the differences found in database schemas and database platforms.
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