Please join us for the full-day event – live streaming across Australia on Thursday, July 22. Participants will have the opportunity to connect with industry leaders from across the built environment as we discuss emerging trends in big data and explore how we, as an industry, can improve operational efficiencies – in buildings and beyond.
Conserve It's Richard McElhinney will be presenting in workshop presentation, ‘Data tagging’ at 11:50am-12:50am AEST alongside Airmaster’s Rob Huntington and Bueno’s Tristan Webber. McElhinney will also be participating in a panel session, ‘Data ontology’ at 3:35pm-4:35pm alongside Schneider Electric’s Evren Korular and A.G. Coombs’s Carl Agar.
Despite tagging being included in most BMS specifications for the last five-plus years, it is rare that it is ever done. This means when any third party (analytics, digital twin, building operating system, etc.) tries to make use of the data, a significant amount of time and effort is spent to identify the data and tag it in their own system. The issue is that the root cause – tagging at the BMS level – is not solved. If and when another person tries to connect to this same data, the existing tagging is in the overlay rather than base layer. The primary adopter of tagging to-date has been “third party” providers who tag the data in their system once they have discovered and made sense of it. Through a live demo format, the group will demonstrate three scenarios on how tagging (or lack thereof) can affect the value chain. The opener will also demystify some of the terminology surrounding tagging and explain its true purpose to provide meaning (structure) to the raw underlying dataset.
As smart building technology expands, there is a greater challenge and need of acquiring a standardised method for organising the data and information.
Within a building environment, data ontology defines the different pieces of equipment and elements, how they connect, and the data they produce. With this, it provides context to help us understand what data is related to and its meaning.
The group will explore the questions and provide insight around data ontologies.