RealEstateCore is a standardized way of naming and categorizing real estate data, making it possible to use the information of different building systems with each other. It also enables standardized communication from different technical real estate and external IT systems. This creates opportunities for advanced data analysis, intelligent control, and the monitoring of buildings, as well as visualization of property data in e.g. 3D models.

RealEstateCore is open source and free to use without costs, limitations, or license requirements. For instance, all relevant stakeholders, such as architects, property owners, property managers, system suppliers, and construction contractors, can use the RealEstateCore-standard to similarly describe the interaction, data reading, and central control of several different properties.

What is RealEstateCore ontology, and why is it important?

Property owners can use RealEstateCore to describe data of interaction inside the properties they manage, along with storage, management, and the sharing of this data. Modular ontologies, such as REC, are a collection of data schemas. These data schemas describe different concepts and relations, referring to data generated in spatial models and/or technical building systems. It can also refer to data from external sources such as weather services or energy grid demand.

Having a shared language allows property owners to connect their buildings with new services on a large scale. They will not have to worry about the details or formats of technology- or building-specific implementation.

RealEstateCore aims to bridge existing industry standards

The content of RealEstateCore is not entirely new but based in part on existing standards applied with a pragmatic approach to finding the least common denominator. In this way, the gap between different existing industry standards is bridged.

RealEstateCore focuses on binding together and bridging four different domains for standards:

  • Digital representation of the building’s construction elements (e.g., BIM/IFC)
  • The control and operation of the building (e.g., Brick Schema, Project Haystack)
  • IoT-technology (e.g., SSN, WoT)
  • Business data for processes and agreements (e.g., CDM/IBPDI)

Harmonization between RealEstateCore and Brick Schema

The Brick Consortium and RealEstateCore Consortium has been working together to create a harmonization between the two leading smart building standards.

Currently, at-scale digital transformation in the real estate industry, within and across organizational boundaries, is challenging because of the number of competing smart building metadata standards. These standards often have significant overlap in features, but are not directly compatible. Unfortunately, incompatible softwares is causing difficulties for building stakeholders to exchange data. Further, it is making it harder for application developers to be able to fully support all building systems. 

These integrated, complete standards allow the real estate industry to drive the digital transformation forward. Therefore, the outcome is being put in line with expectations from tenants, building owners, and society. Complete standards are crucial to achieve the objectives of lowering carbon emissions and contributing to a sustainable smart city.

Unlock value with RealEstateCore and Brick Schema

The Brick Schema and RealEstateCore harmonization enables real estate owners and other stakeholders to unlock the value of the data in their buildings. The data helps supporting many new applications used for:

  • More efficient and less wasteful use of energy
  • Contributes to the the buildings interacting with the energy grids
  • Enhancing the experience of the tenants
  • Enables automated facility management

A new standard for metadata in smart buildings

The new standard that now is ready to be used in real projects is a combination of the Brick Schema and RealEstateCore leading metadata standards for smart buildings. The two groups have carried out extensive work to harmonize the two projects, resulting in a new, clarified metadata solution. The users no longer need to choose beteen Brick Schema and RealEstateCore. The new standard makes it easier to create rich semantic models of smart buildings and real estate portfolios.

The Brick Schema 1.3 and RealEstateCore 4.0 includes much of the technological foundation necessary to make the harmonization possible. At the same time, it is letting each standard preserve backwards compatibility with the previous versions of their respective standards. Full harmonization will occur in future releases of the two standards, which is expected to occur quickly after the August release. The harmonization of the two standards is also being done with an eye towards compatibility with the upcoming ASHRAE 223 standard (BACnet).

Useful links:
You can find out more information about the standards and how to start using them here.

https://www.realestatecore.io/webinar-new-standard-brickrec/
RECcon page: https://proptechos.com/reccon22/
Rec-page: www.realestatecore.io
Dev page: dev.realestatecore.io

Benefits for property owners and property managers using RealEstateCore

Property owners can use RealEstateCore to describe the data of interaction within the buildings that they operate – as well as the management, storage, and sharing of this data. RealEstateCore is a modular ontology, a collection of data schemas that describe concepts and relations that can occur in data generated to model buildings and building management systems or that is sourced from such systems.

Environmentally friendly real estate management with RealEstateCore

RealEstateCore has a special focus on business processes, especially from the property owners’ perspective. This is the way we can bring in a different perspective of standardizing real estate data on a global scale.

Why does open matter?
As there are so many different systems besides a BMS that need to be connected using a master global standard, a plug-and-play functionality will give the property owners greater freedom. The system can easily be upgraded once you have the platform installed and rather than multiple buildings having different standards, once this new ontology is implemented, everyone in the network can contribute to the open standard. It becomes more cost-effective with a collective effort and will catapult the future of buildings to a new green industrial revolution of smart cities.

In essence, it’s a mainstream adoption of technology that we haven’t reached in buildings until now

Smart buildings / Smart cities ecosystem

Based on RealEstateCore, ProptechOS is a SaaS product that real estate owners can use to optimize and manage their property operations, develop applications for tenant services, manage the digital representation of their portfolio, and manage building system on-site.

Using ProptechOS’s platform, real estate owners can access integrated applications that help them unlock a host of smart building benefits, including greater sustainability, well-being, productivity, and better business. An example of an application is the fully automatic LEED certification in cooperation with U.S. Green Building Council.

An open-source SHACL- and DTDL-based ontology for the real estate industry

RealEstateCore is expressed in SHACL and Digital Twin Definition Language (DTDL) using the human knowledge of the physical world and translating that knowledge into a data ontology. Being a common language, it enables both flexibility and robustness required for creating digital twins.

Digital Twin

A digital twin is not only a schematic or a picture of how a device works. It’s a virtual representation of both the physical elements and dynamics of how the device operates, responds and functions, all the way throughout its expected lifetime. A digital twin understands the device’s dynamics, regardless of whether the electrons move or the device itself.

Knowledge graph

RealEstateCore is, as previously mentioned, an ontology that defines different classes of nodes that can be used in the knowledge graph, the object properties or relations between the nodes, and data properties that are linked to the nodes.

A knowledge graph consists of various amounts of statements. These statements are made up of three components.

  1. The subject
  2. The predicate that describes how the statement aims to describe the subject
  3. The object that makes sense of the claim of the predicate

One major advantage for property owners is the ability to customize the graph based on real-time changes. This means that you can add, change or remove data to respond to those changes, making the knowledge graph both flexible and adjustable. The knowledge graph also allows you to add your own logical rules, which can lead to new and improved insights.

Knowledge graphs and the connection with Digital Twins

Since digital twins can generate a considerable amount of data or information, the information provided needs to be stored in different kinds of systems, either due to security or functionality. These systems cannot intertwine with each other in a seamless way, which can lead to an incomplete picture and the real-world data that the entities measure.

RealEstateCore can then work as a connector between these systems, enabling data to connect between different platforms. Using the modular ontology that RealEstateCore is, you can create a schema that lets you combine data from these other systems since it can direct you on how and where the data should link. You can then use this to create your knowledge graph. By bundling data, you can connect the dots between the systems, get a 360 view and model your digital twin.

Useful links to get you started

https://www.realestatecore.io/getting-started/
https://enterprise-knowledge.com/digital-twins-and-knowledge-graphs/ (about digital twin and knowledge graphs)
https://dev.realestatecore.io/ontology/

Github RealEstateCore repository

Ontologies and code for the RealEstateCore project can be found here.

RealEstateCore useful glossary

Below we have gathered a glossary in relation to RealEstateCore.

  • Device = Often several different sensors and/or actuators that together create a function. For example, an air handling unit.
  • Actuator = A motor or something else that can be affected.
  • BMS (Building Management System) = See SC. Also known as BAS (Building Automation System).
  • Service system = The unit or system that serves a consumer. For example, an air handling unit that serves a room.
  • BIM (Building Information Modeling) = Often made in the IFC format.
  • External IT system = Systems that are connected to buildings and other technical property systems. For example, a cloud-based platform. Used to create an independent data layer of the underlying systems.
  • Real estate technician = A person who uses a technical property system to handle the technical management of a property.
  • HMI (Human Machine Interface) = Usually a graphical interface on a web page or in a smartphone application.
  • IoT (Internet of Things) = A collective name for connected sensor technology
  • Observation = A reading of a value. For example, temperature.
  • PLC = Programmable Logic Controller
  • REC = RealEstateCore.
  • SCADA (Supervisory Control and Data Acquisition) = A system that controls one or more underlying systems. Usually a graphical interface. Often used synonymously with HMI or another superior system.
  • Tag list = A list of the IDs for different sensors and actuators in a technical property system or PLC.
  • Technical property system = A superior system that gathers several systems or PLC:s.. Often has a graphical interface. Either BMS or BAS.

Over ride = To affect the steering of a PLC or a technical property system from an external IT system. Examples of this are controlling ventilation or influencing the heat supply to, e.g., achieve better energy efficiency.

For further reading we recommend the scientific paper , which is free to download, produced by the founders Erik Wallin and Per Karlberg. “The RealEstateCore Ontology” which enables data integration for smart buildings.
  • Hammar K., Wallin E.O., Karlberg P., Hälleberg D. (2019) The RealEstateCore Ontology. In: Ghidini C. et al. (eds) The Semantic Web – ISWC 2019. ISWC 2019. Lecture Notes in Computer Science, vol 11779. Springer, Cham
  • DOI: 10.1007/978-3-030-30796-7_9 (Free downloadable postprint)