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Introduction to RealEstateCore


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Introduction to RealEstateCore

RealEstateCore (REC) is a foundational element in developing advanced, interoperable real estate applications and services. By employing REC, developers can leverage a comprehensive ontology designed to facilitate the creation, management, and exchange of real estate data across various systems. This document outlines the core concepts of REC, its structure, and its advantages for developers working on the Relynk platform.

What is an Ontology?

At its core, an ontology is a standardized schema that defines the types of entities (nodes) that exist in a domain, how these entities relate to one another, and the types of data (values) that these entities can possess. RealEstateCore is such an ontology, tailored for the real estate industry. It serves as a blueprint for constructing knowledge graphs that represent real-world properties, their characteristics, and relationships.

Advantages of Using REC

Utilizing RealEstateCore within your applications offers two significant benefits:

  1. Efficiency in Data Modeling: REC eliminates the need for extensive resource investment in designing a custom data model, as it provides a ready-made, comprehensive schema.
  2. Interoperability: Data structured according to REC can easily be integrated with data from other REC-compliant sources, such as suppliers or customers. This compatibility is further enhanced by REC's support for open API specifications and edge message payload formats, ensuring seamless data exchange.

Structure of RealEstateCore

RealEstateCore organizes real estate data into a structured hierarchy of types, each representing different aspects of the physical and operational characteristics of properties. Below is a brief overview of the primary REC types:

  • Space: Represents a physical area with a three-dimensional extent, such as regions, sites, buildings, levels, and rooms. Spaces can be architecturally designed or natural.
  • BuildingElement: Components of a building's structure, like facades, walls, and roofs.
  • Asset: Objects within a building not integral to its structure, classified into hierarchies like architectural features and furniture. The equipment asset hierarchy is detailed through collaboration with Brick Schema.
  • Point: Denotes the data interaction capabilities of entities, including sensors, commands, and setpoints.
  • Collection: Administrative groupings of entities addressed as a single unit, regardless of spatial arrangement.
  • Agent: Stakeholders, including people, companies, and departments, involved in real estate management and operations.

API and Data Exchange

API Definition (OpenAPI Specification)

The REC REST API is generated from the ontology, creating REST endpoints and JSON-LD schemas for entity types, relationships, and properties. This approach ensures that the API remains consistent with the REC ontology and facilitates easy data exchange.

Edge Messages

RealEstateCore edge messages are designed for efficient communication between edge devices and the cloud. These messages use a compact JSON format tailored for message brokers and other messaging types. The edge messages are also used as a way to communicate sensor readings and actuation (commands and setpoints) between different cloud systems that communicate over messaging systems like MQTT.

Why Use RealEstateCore?

Relynk adopts RealEstateCore for its ability to standardize and streamline data models in the real estate domain. By integrating REC, Relynk ensures that its platform is built on a solid, interoperable foundation, simplifying data integration and enhancing the overall developer experience.

For detailed documentation on each component of RealEstateCore, including examples and schema definitions, developers are encouraged to explore the RealEstateCore GitHub repository and the accompanying reference documentation.