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Data Model

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You are currently looking at a work in progress version of the Relynk API documentation. Consider the underlying APIs and messaging formats as stable, but we strive to make the documentation as developer friendly as possible. If you feel anything is missing please reach out to hello@relynk.io, any feedback would be much appreciated.

The Relynk platform leverages RealEstateCore (REC) ontology to structure data, focusing on Spaces, Assets, Building Elements, and Points. These REC entities represent the physical and operational aspects of real estate properties, including the devices that monitor and control these environments. This guide elucidates the relationships between REC-defined entities and Points, illustrating their application in the Relynk ecosystem.

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Prerequisites​

This guide assumes a basic understanding of the RealEstateCore (REC) ontology. For a an intruduction to REC, refer to the REC Ontology section.

Introduction​

In Relynk, the physical and functional aspects of real estate are represented through Real Estate Core entities: Spaces, Assets, and Building Elements. These entities capture the essence of the physical world, from buildings and rooms to structural components and items within a space. Points, or sensors, measure and provide data on various physical parameters within these entities. REC introduces a flexible, relationship-based data structure, ensuring interoperability and data richness.

Real Estate Core Entities​

Real Estate Core entities are interconnected through relationships, reflecting the complex, real-world interactions between spaces, structures, furniture and equipment.

Examples of REC Entities:​

  • Spaces: A Building, Level, or Room, defining the physical areas.
  • Building Elements: Structural components such as Walls, Roofs, and Facades.
  • Assets: Objects within a space, including furniture and equipment like HVAC.

Points (Sensors)​

Points represent the sensory, setpoint, status and command capabilities within the REC framework, for example temperature, humidity, and presence sensors. Each Point is usually associated with specific Real Estate Core entities, providing data relevant to their location and function.

Relationships between REC Entities and Points​

In Relynk, the relationship between REC entities and Points is defined by direct associations, establishing a flexible and dynamic link that mirrors the actual deployment and operation of sensors within physical spaces.

Relationship Examples:​

  • A Temperature Sensor associated with a Room (Space) provides real-time temperature data for that room.
  • A Temperature Setpoint associated with an Heat Exchanger (Asset) connected to a specific HVAC system provides setpoint information and write back capabilites for the system.
  • A Occupancy Count Sensor associated with a Level (Asset) provides real-time occupancy count for the level.

Querying Data​

When querying data in Relynk, the REC ontology provides a rich set of relationships and properties to navigate and filter data. This allows for complex queries that can both filter on specific REC entities and traverse the relationships to Points, or query points directly.

Writing data​

Writing data is done through the Points, which are associated with REC entities. This allows to first get an overview of the Setpoints and Commands that are available and how they relate to the REC entities, then using the Points to write data back to the system.