Semantic metadata standards pave the way for interoperability by providing building operators and application developers with
common schemes to describe building resources. Applications can query building metadata models to retrieve the set of entities and relationships they need to operate, instead of hard-coding references to specific points and objects from the underlying data sources.
Currently, querying such models requires the developer to be very specific when formulating queries in order to obtain meaningful answers (or any answer). The developer is inevitably expected to be familiar with the systems and components of the buildings being queried, as well as the schema used to represent them. The variety of buildings — both in the composition of their subsystems and in how they happen to be modeled — means that the developer will need to use multiple queries in order to retrieve necessary results. This is complex, time-consuming and error-prone.
To address this limitation, we investigate query relaxation as a technique to facilitate discovery of meaningful building resources in a collection of ontology-based buildings data. We evaluate our query relaxation approach over a set of Brick models and demonstrate its use in the context of real-world building applications.