Smart Buildings

Haystack’s Tagging Framework Bringing Order to Chaotic World of BIoT

Haystacks can be round or rectangular depending on local traditions or modern tools but always designed to store and protect hay (grass) from the elements in harsh farmland environments. The grass is collected, sorted and structured to ensure it is accessible when required. Haystack’s regular shapes contrast with the natural landscape - like beacons of order in a chaotic world of mud, machines, and manure. In the cleaner but equally chaotic world of the Building Internet of Things (BIoT), buildings flooded with sensors create cascades of information flowing towards big data analytics engines. If unsorted or badly sorted, it accumulates into a thick data mud, which makes it slow and complex for systems to find the insights they are looking for. However, an open source initiative named Project Haystack is streamlining the process of working with data from the IoT. “Macro trends in technology are making it increasingly cost-effective to instrument and collect data about […]

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Haystacks can be round or rectangular depending on local traditions or modern tools but always designed to store and protect hay (grass) from the elements in harsh farmland environments. The grass is collected, sorted and structured to ensure it is accessible when required. Haystack’s regular shapes contrast with the natural landscape - like beacons of order in a chaotic world of mud, machines, and manure.

In the cleaner but equally chaotic world of the Building Internet of Things (BIoT), buildings flooded with sensors create cascades of information flowing towards big data analytics engines. If unsorted or badly sorted, it accumulates into a thick data mud, which makes it slow and complex for systems to find the insights they are looking for. However, an open source initiative named Project Haystack is streamlining the process of working with data from the IoT.

“Macro trends in technology are making it increasingly cost-effective to instrument and collect data about the operations and energy usage of buildings. We are now awash in data and the new problem is how to make sense of it. Today most operational data has poor semantic modeling and requires a manual, labor intensive process to "map" the data before value creation can begin,” explains the Project Haystack mission.

Project Haystack believes that pragmatic use of naming conventions and taxonomies is the best way to make data more cost-effective to analyze and visualize, which will ultimately help us derive value from our operations. The impact of making data easier to use will be most significantly felt in the smart building industry, alongside other “intelligent” sectors, but it has implications across all of industry and society as the fourth industrial revolutions ushers in the Data Age.

“As the existing protocol standards do not communicate the metadata or context associated with all the measured and controlled parameters in a common way, human engineering effort is still needed to “connect the dots” and enable the systems to interact in a meaningful way. What has been missing is data tagging, which can provide the context needed for software applications to understand the meaning of the data. Recognizing the significance of tagging led the founders of the Project Haystack to create this open source project back in 2011,” said Chris Irwin, VP of Sales for EMEA and Asia for J2 Innovations, the developers of the FIN open framework.

Before the arrival of tagging, in the building automation world at least, engineers had to rely on data labels - typically a single text field of 16-32 characters - in order to quickly understand where a specific device fits into the system. Remembering abbreviations and coded labelling comes naturally to the human mind, which attaches meaning to the characters to represent the full description. However, this process is somewhat personal, so each project uses a different syntax depending on the specific consultants and engineers working on the job, then issues occur with any change in personnel.

Automation software, on the other hand, provides a huge advantage by natively supporting data tagging using digital structures. This enables most of the otherwise manually engineered tasks associated with configuring a system to be automated, which can save as much as 80% of the time engineers spend on some tasks. In a system where all data is tagged, the opportunities for automation, optimization, real-time monitoring, as well as performance analytics across the BMS and disparate functional systems, become easily attainable. Project Haystack has developed one of the most popular tagging methodology frameworks.

“The use of Haystack tagging has been instrumental in our ability to provide meaningful information to our clients, as well as simplifying our workflow when processing building data,” said Aidan Pickard the CTO and Co-Founder of Nube iO, a smart building automation company based in Australia. “As more and more assets are being introduced to smart buildings, Haystack tagging is becoming an industry standard for sorting data.”

Approaching its 8th birthday, Project Haystack is gaining traction globally. Formal discussions with ASHRAE (the originators of the BACnet standard) and Brick (a Uniform Metadata Schema for Buildings) have also begun to co-develop data strategies for the future. As the use of Haystack tagging continues to grow, the scope of the agreed tags could extend well beyond core building services systems and reach into areas like parking, even asset and facility management.

“Haystack methodology has become the most widely adopted and fully developed approach to “marking up” device data, but that doesn’t mean our efforts are complete,” state John Petze, Executive Director, and Marc Petock, Executive Secretary, of Project Haystack in a joint statement that kicked-off Project Haystacks Connect publication’s Winter 2019 issue.

“The building automation industry and society in general, are just beginning to learn how to use data and exploit the value it contains. New challenges, deeper understandings, more input from different viewpoints and diverse applications, will continue to drive the work of the organization.”

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