Haystack Data Model

Tipify makes use of the Project Haystack tagging and data model to add the semantic descriptions to data so it has structure and context in a uniform, normalized manner.

Haystack tagging and modeling lets us understand what each piece of data means and how it fits into the overall building system. It works by creating a model of data around items of equipment and describes how these items interact in the overall building System.

With Haystack semantics the data for any building is represented in a consistent, meaningful manner that allows analytics, control and visualization functions to be directly reused across equipment, sites and projects.

Haystack Data Modeling lets us deliver and manage large projects with diverse systems and data sources.

Consider an example: The system reads a sensor value of 77.5, but that value has no meaning unless it is qualified with units of measurement, the variable it is measuring, the equipment that it is connected to.

We create this Semantic Metadata by adding Tags to the variable.
Temperature and DegC define the units;  Tags of Air and Supply define the function Tags of AHU tell us the type of equipment that the data point is connected to.

The AHU will use further Tags (Fresh Air, make up, Chiller1, VT Circuit 4) to characterize it and its interaction with the rest of the building system
Then more tags (manufacturer type, supply date, capacity, serviced by) can be used to characterize the AHU even further.
The Building can also be characterized by its own set of Tags (name, Address, Geo Location: Lat and Long, Size: Square feet).

We can select and filter based on any tags or combination of tags.
For example to find all Chillers of a certain type that are serviced by one organization, and use that to compare chiller efficiency with those from another supplier.

Building energy can be normalized by degree days with weather data that is automatically associated with that building based on its Geolocation
and compute energy consumption per square foot by dividing Totalized Energy Tag by Size Tag values.

An Analytic function created for this AHU can automatically bind itself to another similar AHU because it has the same Tag Descriptions and Variables.
The Structure of the Folio Data Base allows additional Tags to be added directly so descriptions and characteristics can be added over time.