One of the resources available from the Project Haystack website is a spreadsheet that documents a State of Utah job from a few years ago. This spreadsheet details the various types of equips and how they should be tagged. It also lists all the points in each equip type and documents the proper Haystack tags used.  This is a great resource for anyone who is new to Haystack and trying to build their first Haystack compatible BAS database.

When Haystack 4 was released, some previously defined tags were changed or deprecated. The downloadable spreadsheet has now been updated to reflect the tag changes made in Haystack 4.  If you are a Project Haystack novice and looking for help tagging a new project, you can use this file to see how to tag entities correctly.

Here are just some of the exciting presentations you can expect to see at this year's Haystack Connect...

Track 1 – Haystack in Practice

The End-User Perspective & Real-World Applications

Transforming Building Operations
Jessica Granderson, Lawrence Berkeley National Laboratory

Building fault detection and diagnostics technologies (FDD) are already saving owners millions of dollars per year in their buildings, with less than two-year paybacks. Berkeley Lab has joined forces with members of the Haystack community and FDD industry to newly integrate control capability with analytics, moving beyond FDD into automated fault correction and control optimization. This presentation will share the developed solutions, results from their use in diverse field applications, and their open-source Haxall dissemination. The presentation will also discuss the extensions of the work to automated functional testing and demand flexibility, and available technical assistance to transfer these methods industry technology and service providers, concluding with observations on the role of advanced analytics and controls in scaling building decarbonization, and semantic modeling as a key enabler.

One word, DATA. 

Data. It’s transforming everything.  Data has changed the way companies in every industry do business and manage performance. Data is now an irreplaceable asset. And data has never been more important in delivering today’s smart buildings.

However, a challenge that continues within smart buildings involves the vast differences in how data is identified and named. Definitions are often different, depending on the manufacturer, vendor, or other stakeholders describing the building data.

Data can be bewildering and meaningless. We have so much data available at our fingertips, what are the real pieces of data we truly need and what is just noise? When it comes to data, we need to move past “data drowning” and get to a point where we are automating the collecting, sorting, and exchanging of critical information that directly correlates to improving our operations and meets our business outcomes.