There's More to Tagging Than Searching for Data

In the world of Smart Buildings and the ever increasing amount of big data, we have been seeking easier ways to derive benefits from our connected equipment and devices. With the proliferation of data standards such as Project Haystack, we have made great advances in both informational technology (IT) and operational technology (OT) use of data to gain efficiencies and performance. Here are some insights that I have seen on both the traditional and innovative uses of tagging and data modeling.

Information 

When we think of big data we are often on a mission to "find" information about our building's performance, energy usage, and ways to optimize efficiency. One of the ways that tagging data has significantly helped is by enabling analytic applications to automatically bind data to their rules engine. For example, a common rule is to identify when both heating and cooling are on at the same time. Historically, this could be done manually by scanning trend data but is now done programmatically by linking a model of an air handler and its associated points (heating and cooling outputs) to the rule (simultaneous heating and cooling).  

Another great example where tagging makes it easy to "share" information is when integrating data from a building automation system (BAS) to an enterprise application such as work order management. For example, the run time of a piece of equipment that is controlled by the BAS can become a dynamic property in the CMMS (computerized maintenance management system). 

Operations

It may not be obvious, but there are powerful and somewhat mundane uses for tagging and data modeling that significantly impact the operational aspects of creating a smart building. One of the most time-consuming aspects of a project is to build a bespoke user experience. Traditionally, this is done with manual placement of UI elements that are then linked to the data points by what we affectionately called "the link monkey." 

In modern software applications that utilize tagged data and data models, the information is self-describing, meaning the application automatically plugs the relevant operational data into the right user experience. In effect, all the information contained in the models is dynamically linked to the user's apps: navigation, point graphics, equipment graphics, summary graphics, and schedules. 

Another operational aspect of creating a smart building is programming the control routines and fault detection and diagnostics (FDD) sequences. Historically this was implemented by an application engineer who would copy and paste control routines, then link each one individually to its corresponding equipment. This is both tedious and error-prone. By using Haystack for this operational step, you simply tag data models for the equipment that needs to be controlled and tag the corresponding control sequences so that the inputs and outputs automatically match up. This drastically reduces the traditional amount of time, labor, and cost required to implement control strategies across the building.

The benefits of implementing tags, data modeling, and data standards such as Project Haystack go beyond finding and sharing data. There is a whole world of operational efficiencies and optimized workflows that greatly reduce cost and human error. As more manufacturers adopt software frameworks that incorporate standards-based metadata, we become closer to the democratization of smart building technology. Learn more about the benefits of tagging here.