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Strong Data Modeling Approaches and the Benefits They Offer Your Building

Image of Patrick Gilhooly
Patrick Gilhooly

In smart buildings, devices, software, and building equipment must work together seamlessly. This requires unifying several naming and tagging standards currently used for building automation. While a seemingly simple issue, many data modeling approaches create roadblocks to real-world application of building data. But there is a better way. The Ontology Alignment Project lets you harness the full potential of building data, allows smart solutions to evolve and grow, and supports better performance and efficiency.

Common Data Modeling Approaches

A uniform approach to data modeling is critical to ensure that innovative new technologies don’t face unnecessary roadblocks once installed. It helps you integrate new software applications or equipment into buildings and allows cutting-edge solutions to be added seamlessly, regardless of their manufacturer. But with numerous data modeling approaches available, how do you know which is best? 

Before considering the answer to this question, let’s look at how data modeling works. 

When applied to buildings, data modeling refers primarily to the tagging or naming standards applied to a source system. A systemic data modeling approach helps different products work together and allows for better tracking of the various physical and digital aspects of smart buildings. It also offers a better view of relationships between software applications, equipment, and systems.  

Common data modeling approaches used for building automation include: 

  • Brick Schema: An open-source system used to name logical, physical, and virtual building assets, along with their relationships to each other
  • Google’s Digital Building Ontology (DBO): An open-source system that creates a uniform schema using Apache-based tools to represent structured building and equipment data
  • Project Haystack: A flexible, open-source system used to standardize data modeling and web services in order to best utilize building data
  • RealEstateCore: An open-source system that utilizes Microsoft’s Azure, along with DTDL (Digital Twins Definition Language) to integrate building technology. 

Of these, Brick Schema and Project Haystack are most widely used.

The Ontology Alignment Project

The Ontology Alignment Project (OAP) is setting a new standard for data modeling. Developed as an open-source taxonomy, it uses distinctive coding based on Haystack tagging to model elements within the built environment, including HVAC equipment, lighting infrastructure, IoT devices, and underlying points.  

The OAP is excellent for:

  • Connecting elements of the built environment via standardization of naming and tagging
  • Connecting tools to implement the connection of building systems, transfers of data, and application of tags
  • Continually verifying and enhancing the ontology 
  • Creating a data modeling approach that supports diagnostics, fault detection, data accessibility, and digitization 
  • Making tagging and developing ontologies easier
  • Methodically adding implementations within a building to existing ontologies 
  • Mitigating the effects of future conditions or events to ensure continuing usability 
  • Normalizing data from a central locations via a smart building management system 
  • Receiving OAP definitions in real-time via API
  • Tracking energy flows for diagnostic purposes through the use of analytics 
  • Translating between different data modeling approaches in systems and equipment

The OAP automatically translates other ontologies, allowing building owners to take advantage of technologies that work under different protocols. Users then needn’t conform to specific variants when leveraging different data modeling approaches. The OAP also allows data models to be created to define relationships within building systems. This means you can designate data models for such functions as airflow, water usage, heating water, Internet connectivity, electricity usage, and utility metering. 

Advantages of the OAP


check-mark-yellow-2Adds documentation instantly to the ontology

check-mark-yellow-2Allows efficient use of system-based and root cause analytics

check-mark-yellow-2Available via API

check-mark-yellow-2Evolves quickly

check-mark-yellow-2Offers better transparency 

check-mark-yellow-2Provides real-world tagging documentation 

check-mark-yellow-2Shows how to apply models

check-mark-yellow-2Simplifies classification ontology


Ultimately, the OAP seeks to sustain and expand data modeling approaches like Brick and Haystack to encourage the compatibility of building data when integrating new equipment or software into existing systems. Using OAP standards, these tags should be applied to equipment, electrical points, and other elements being integrated. And because the OAP is essentially an API, users can also build interconnected applications employing OAP’s data model. 

Expanding the Possibilities of Smart Buildings

Buildings IOT knows smart buildings. From master systems integration to custom software to digital services, our end-to-end solutions are redefining what smart buildings can do. We developed the OAP to support and extend existing standards to make data models compatible with real-world integration projects. With our leading-edge approach, building data becomes a powerful force for change and your building becomes more agile, responsive, and efficient than ever before.  

Buildings IOT’s innovative data modeling approach ensures seamless building integrations. Contact our team of experts to learn more about what we can do for you.

 

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