IRIS is a digital tool designed to support data-driven decision-making for retrofitting domestic properties by identifying homes that could benefit from energy efficiency improvements. It enables stakeholders to assess housing stock based on energy performance data to help target funding schemes and policy interventions more effectively.
Current status:
Scaling across England and Wales – IRIS now covers all domestic properties in England and Wales (over 25 million) with EPC data, extended from its initial Isle of Wight pilot. The dataset has also been expanded to include fuel type information, enabling richer analysis of housing stock and energy use.
Future development:
Expanding functionality and usability – ongoing work includes integrating additional datasets, improving interoperability, and enhancing performance at national scale. Future updates will focus on usability improvements, linking with more policy-relevant datasets, and enabling new forms of analysis and scenario modelling.
IRIS is a digital tool designed to support data-driven decision-making for retrofitting domestic properties by identifying homes that could benefit from energy efficiency improvements. It enables stakeholders to assess housing stock based on energy performance data to help target funding schemes and policy interventions more effectively.
Current status:
Scaling across England and Wales – IRIS now covers all domestic properties in England and Wales (over 25 million) with EPC data, extended from its initial Isle of Wight pilot. The dataset has also been expanded to include fuel type information, enabling richer analysis of housing stock and energy use.
Future development:
Expanding functionality and usability – ongoing work includes integrating additional datasets, improving interoperability, and enhancing performance at national scale. Future updates will focus on usability improvements, linking with more policy-relevant datasets, and enabling new forms of analysis and scenario modelling.
Many homes in the UK require retrofitting, but identifying the right properties for intervention is challenging. Current funding schemes like Energy Company Obligation (ECO) often struggle with lead generation and coordination, leading to inefficiencies and delays. IRIS simplifies this process, allowing policymakers, local authorities, and industry to prioritise homes based on available data and improve funding allocation, planning, and implementation.
IRIS demonstrates how digital models and interoperable data-sharing can enhance decision-making, improve market visibility, and enable scalable solutions. The tool currently ingests and visualises data from Energy Performance Certificate (EPC) records and Ordnance Survey mapping, providing an initial framework for more advanced policy analysis and impact assessment. Its pipelines have also been used to extend the Information Exchange Standard (IES) through the development of IES:Building, ensuring that housing and retrofit data can be structured consistently for use across sectors.
Local authorities
Isle of Wight Council, Newport City Council
Retrofit companies
JJ Crump
Third sector organisations
The Footprint Trust, Future Isle of Wight, Green Isle of Wight
The IRIS demonstrator serves two core purposes—one is programme-driven, focused on developing key NDTP assets, and the other is use case-driven, addressing a significant real-world challenge in energy efficiency of buildings and retrofitting.
IRIS is a key testbed for developing and refining the National Digital Twin Programme (NDTP) core programme assets, ensuring the robustness, scalability, and interoperability of the digital twin ecosystem. Through this demonstrator, we are:
Delivering reusable programme resources, including playbooks that:
Demonstrating the potential of interoperable data, showcasing how scaling ingestion, mapping data to IES, and adding features over time enhances value exponentially.
While this demonstrator plays a key role in developing NDTP assets, it was also chosen as energy efficiency of domestic properties has a significant impact on the UK’s carbon footprint, making retrofitting a national priority. This demonstrator:
By combining technical development with real-world impact, IRIS demonstrates both the power of interoperable data and the tangible benefits digital twin technologies can unlock when applied at scale.
IRIS now covers all 25 million domestic properties in England and Wales, making it the first tool of its kind to consolidate EPC data at national scale and visualise it down to the individual dwelling. This granularity provides a strong evidence base for retrofit planning and policy, supporting goals such as warm homes, fuel poverty alleviation, and more efficient deployment of schemes like ECO. While not currently configured for compliance management, IRIS also offers the foundations to strengthen oversight and integrity of retrofit funding in the future.
The IRIS stack is composed of four interrelated repositories:
This is the client-side application that users interact with. Built using Angular, it renders geospatial housing data, overlays EPC and material information, and provides interactive filtering and selection tools. Designed with performance and clarity in mind, it presents IA-fed data in a way that supports quick insight and decision-making.
The backend service for the visualisation layer. This Python-based API provides REST endpoints to read from and write to the IA Node, enabling dynamic queries and state changes. It also supports OpenAPI documentation and routes all visualisation data calls through a secure and scalable middleware layer.
An ETL pipeline that pulls raw data from public APIs (e.g. EPC and Ordnance Survey), cleans and transforms it using dbt, and stores it in a structured format (CSV in S3) ready for further processing. The pipeline is managed using Airbyte and is intended to be reproducible, modular, and extendable.
This repository contains two core data pipelines that transform energy performance and geographic datasets into RDF format aligned with the Information Exchange Standard (IES). Specifically, it uses IES:Building, a domain ontology developed through this demonstrator to represent data about the built environment—particularly energy performance characteristics.
The pipelines include:
Both pipelines integrate with Kafka for ingestion and publishing, and are intended to serve as reference implementations for structured, interoperable data exchange using the IES framework.
The IRIS stack is composed of four interrelated repositories:
This is the client-side application that users interact with. Built using Angular, it renders geospatial housing data, overlays EPC and material information, and provides interactive filtering and selection tools. Designed with performance and clarity in mind, it presents IA-fed data in a way that supports quick insight and decision-making.
The backend service for the visualisation layer. This Python-based API provides REST endpoints to read from and write to the IA Node, enabling dynamic queries and state changes. It also supports OpenAPI documentation and routes all visualisation data calls through a secure and scalable middleware layer.
An ETL pipeline that pulls raw data from public APIs (e.g. EPC and Ordnance Survey), cleans and transforms it using dbt, and stores it in a structured format (CSV in S3) ready for further processing. The pipeline is managed using Airbyte and is intended to be reproducible, modular, and extendable.
This repository contains two core data pipelines that transform energy performance and geographic datasets into RDF format aligned with the Information Exchange Standard (IES). Specifically, it uses IES:Building, a domain ontology developed through this demonstrator to represent data about the built environment—particularly energy performance characteristics.
The pipelines include:
Both pipelines integrate with Kafka for ingestion and publishing, and are intended to serve as reference implementations for structured, interoperable data exchange using the IES framework.
There are multiple ways to engage with IRIS, whether you are part of government, industry, academia, or the technical community:
If you’re interested in collaborating, adopting, or contributing, get in touch via ndtp@businessandtrade.co.uk or explore the open-source codebase on GitHub.
