Key Data Tagging Best Practices for Smart Buildings
Smart buildings require data to operate at their most efficient. The more data gathered, the more...
Smart buildings require communication. Open-source data tagging standards make that communication seamless and ensure interoperability of components, regardless of who developed the software or manufactured the devices. Introducing standard ways in which to describe various elements within a building, along with their relationships to each other, makes integration of new technologies easier—and more useful—than ever before.
As smart technology within built environments becomes increasingly common, the amount of building data produced increases exponentially. To be truly useful, this data needs to be easily available to all a building’s connected systems and devices. Standardized tagging makes this possible by defining every element within a building uniquely and creating a common language.
Data tagging standards make data flow more quickly and efficiently, not only from their sources but also back to controllers and between interrelated equipment. Through the use of open-source data models, standardized tagging enables better interoperability between subsystems and external data sources while facilitating data flow.
Data tagging standards:
Standardized data tagging unifies the way in which systems connect to and communicate with each other. It makes data more manageable and accurate, which helps you make informed decisions to optimize a building’s performance.
The true value of building data comes from analysis, and effective analytics requires standardized data tagging methods. Yet, building automation systems (BAS) typically don’t employ data tagging standards for metadata. Though standards like Brick Schema and Project Haystack were developed to handle such issues, those data tagging standards have to be applied manually. This labor-intensive method is both costly and prone to error.
Now, there is a solution: the Ontology Alignment Project (OAP).
As an open-source data model, the OAP is a taxonomy that models the built environment and seeks to automate this process. It provides data tagging and naming standards that facilitate integration and allows data— including that gathered by IoT devices—to be easily normalized and standardized. This enhances the functionality of analytics software, supervisory controls, fault detection and diagnostics, and other elements that utilize building data. Because it’s also an API, users can build software applications that mesh with OAP’s data model.
The OAP has immediate and meaningful benefits for a wide range of stakeholders. In an interview with Automated Buildings, I explained it as such:
Having a standard allows building controls contractors and integrators to deliver building automation systems more consistently. This results in easier commissioning and troubleshooting while improving understanding of the type and purpose of data in the building systems. For building owners and investors, the OAP provides confidence in the practicality of their building system’s data. The data model can be understood by building automation platforms without significant investment in custom solutions. And, operators and service managers can gain meaningful insights into commissioning and maintenance activities.
Ultimately, the OAP contributes to a greater understanding of building data and its intended use, paving the way for better performance, greater efficiency, and more advanced automation.
Building IOT’s groundbreaking project at 800 West Fulton Street in Chicago is a prime example of the importance of integration in intelligent built environments. It’s also an excellent case study of how the OAP facilitates seamless integration.
At 800 Fulton, the Buildings IOT team deployed onPoint, a smart building management platform and user interface, to continuously monitor system data to improve building performance and optimize efficiency. With the insights provided by onPoint, our integration experts were then able to plan the relationships between the building’s automated systems and how they would function together.
During implementation, Buildings IOT:
The application of the OAP allowed applications that relied on data to leverage system models and enabled those outside Building IOT’s integration team to easily interpret data. This ease of communication was instrumental in unlocking the powerful capabilities that give 800 Fulton the distinction of being Chicago’s smartest building.
When it comes to smart building technology, Buildings IOT leads the way. From cutting-edge software to master systems integration to the OAP, we are constantly expanding the boundaries of what is possible. With our expertise, you can transform your portfolio and stay at the forefront of a quickly changing technological landscape.
Buildings IOT offers the state-of-the-art services and products that operate in conjunction with cutting-edge data tagging standards. Contact our team of experts to learn more about what we can do for you.
Patrick Gilhooly is a Customer Onboarding Engineer at Buildings IOT and a member of the OAP working group and advisory council. Patrick is based out of Ontario, Canada, and a graduate of the University of Waterloo. Before joining Buildings IOT, Patrick held project engineering positions at Bombardier Inc, SAP, and HTS Engineering.