Matthew Taylor

Data models and ontologies at the centre of smart building enterprise

Data models and ontologies are an often-avoided topic but are foundational to the future of smart buildings. Data modelling provides a machine-readable model for what building systems are and how they relate. They give us a rich vocabulary with which to describe a building and its many functions, with a rigour allowing machine learning algorithms to start gaining the same context as a human expert. The data model can automate many of the things we do anew every project – giving us the full benefit of cloud-enabled enterprise systems in our industry.

Because it’s rooted in data science rather than buildings, the topic is quite unfamiliar for many in HVAC&R and building services, including traditional control system contracting companies. It certainly shouldn’t be avoided, though it also shouldn’t be a focus for end-clients. It’s the glue in the middle that smart building consultants and contractors should understand the importance of and approach with care.

This talk demystifies ontologies, discusses the importance of data modelling in the future of smart buildings, and discusses some of the different ontology options available.

About Taylor:
Taylor is a senior engineer with Norman, Disney & Young and holds a master’s degree in engineering from the University of Oxford. Recently moving to Australia from London, he is experienced in delivering smart building projects across the EMEA region – including extensive work with a major tech company and early implementation of evolving open standards around data normalisation, ontologies, and cloud telemetry.