KODE Labs is releasing a big update on KODE Ontology!
This represents a new way of defining devices based on operations and functionality. KODE Ontology is structured after and inspired by Google Ontology as an effort to create a uniform schema and toolset for representing structured information about buildings and building-installed equipment.
KODE Ontology identifies a device's main function and defines the required fields and components the device must have to successfully perform that function. KODE Ontology will serve as a backbone for data analysis and automation of analysis-related features, such as Fault Detection & Diagnosis, Functional Testing Tool, Optimized Start Stop, and Insights.
The old KODE Ontology was inspired by Project Haystack tags. Google Ontology utilizes Haystack tags into the subfields and adds a structure in how the tags are used in combination with each other and how the devices are compiled. So we can say that Haystack is a small ideological subset of Google Ontology.
How does this improve KODE OS?
Point Apply Template
We transitioned from our previously defined ontology (Project Haystack tags) into the Google-inspired ruling to better structure our data. The previous ontology allowed you to choose the device type and to continue with the templating process, but the device template didn’t have any mechanism to:
These reasons led us in creating a new way of validating the device tagging process.
Ontology Report
The Ontology Report validates if a device is complete by showing if points are tagged and identified properly. It shows you which devices are missing points and what points are missing.
This Report can be found on the Points Apply Template page after selecting the Ontology Report button. The same button can be found on the Device Details page on its lower right-hand side menu and it will show you the Ontology Report for a single device.
Insights Chart Creation and Audit Template Creation
With KODE Ontology, the point selection process for Audit dashboards and Insights chart is easier and feels more natural. We have three levels of filtering: Canonical Types, Entities, Fields which are described below:
Filter selection is dynamic, meaning that while you select them, they will filter each other. If you choose ZTS, which stands for “Zone Temperature Monitoring”, it will filter the Canonical Types and show you those that actually have Zone Temperature as a point.
We hope you have enjoyed this announcement as much as we did working on making this happen! Let us know how we can make KODE OS better! And, remember, you can always share the feedback in KODE OS or by emailing us at [email protected].
Thank you for reading!